2009One-way Hash Function Construction Based on Conservative Chaotic Systems

合集下载

IntroductionToNonlinearDynamicsAndChaos-Outline

IntroductionToNonlinearDynamicsAndChaos-Outline

Format: 2-2-3, EE4060 Introduction to Nonlinear Dynamics and Chaos1.DescriptionThis course introduces the student to the basic concepts of nonlinear dynamics and chaos via numerical simulations and electric circuits. The primary goal is to understand the bifurcations and steady-state behavior of nonlinear dynamical systems. The secondary goal is to study the phenomenon of chaos using Chua’s circuit and memristor-based chaotic circuits.2.PrerequisitesMA-235 [Differential Equations for Engineers]EE-2050 [Circuits I: Steady State] or EE-201 [Linear Networks: Steady State Analysis] 3.Materials (REQUIRED)1.Nonlinear Dynamics and Chaos With Applications to Physics, Biology, Chemistryand Engineering. Strogatz, Steven H. Perseus Books, Reading, Massachusetts.1994.2. A Route to Chaos Using Nonlinear Circuits. Muthuswamy, Bharathwaj. PDF will beprovided.4.Course Learning ObjectivesUpon successful completion of the course, the student will be able to:1.Describe the fundamental differences between linear and nonlinear dynamicalsystems and the importance of studying nonlinear dynamics.2.Define the different bifurcation phenomenon of nonlinear systems in one, two andthree dimensions3.Apply bifurcation analysis to study practical systems such as laser models, Josephsonjunctions, op-amp oscillator circuits and the nonlinear pendulum4.Understand limit cycles and Poincare Maps5.Understand basic concepts of chaos using Chua’s circuit6.Perform literature review7.Prepare short presentations5. Course Topics1.Introduction, differences between linear and nonlinear dynamics (1 class)2.Fixed Points and Stability (2 classes)3.Bifurcations in one dimensions (2 classes)4.Examples of bifurcations in one dimensions – laser models (1 class)5.Flows on a circle – oscillators (2 classes)6.Midterm review (1 class)7.Examples of oscillations–op-amp oscillator circuits,Josephson junctions andnonlinear pendulum (2 classes)8.The phase plane – linear systems, conservative systems, reversible systems, limitcycles and two-dimensional bifurcations (3 classes)9.Introduction to chaotic systems – Chua’s circuit (1 class)10.Memristor-based chaotic circuits (1 class)11.Tools for analyzing chaotic systems – period-doubling bifurcations, PoincareMaps revisit (1 class)12.Some properties of the strange attractor (1 class)13.Applications of Chaos (1 class)14.Final presentation guidelines and course wrap up (1 class)15.Group presentations (1 lab section)16.In-lab midterm (1 lab section)6.Prerequisites by Topic1.Understanding of linear constant coefficient ODEs2.Basic circuit analysisboratory Topicsboratory experiment details and requirements are described in [2].2.Students are expected to prepare for the lab by doing all required pre-lab activitiesand finishing all remaining requirements during the lab itself.3.Limited laboratory reports will be required.4.During weeks 9 and 10 of the course, students will have an opportunity to implementdifferent versions of Chua’s circuit. They will be required to perform a basic bifurcation analysis,visualize their system in Mathematica,simulate their circuit using MultiSim and implement their version of Chua’s circuit on a breadboard. They will also be required to give a final presentation on their work.Weekly Course Topics8.。

一阶时滞系统的鲁棒α-稳定性区域分析

一阶时滞系统的鲁棒α-稳定性区域分析
K) ] () 6
这里 是 方程 vo =a K( V 仃) ct T— 0< < 的唯一根 . v
为保 证 R ( < 一 , K=一 代入 ( ) , e A) 取 町 6式 可 得 ( ) 零解 的 O一稳定 区域 的边 界 、 3式 L 记其 边 界
其 仅一稳定 性 的鲁棒 区问.
1利用hayes定理分析一阶时滞系统的稳定性区域11问题的导出我们考虑下列超越方程abe0上式可看作abe0当1时的方1程而1式可同解变化为下式heaeb02文8中hayes第二定理为定理方程h0的根位于直线rek的左边当且仅当ak1及akekbekv2ak212这里v是方程vcotvak0v的唯一的根
献 [ ] 合文 [ , , ] 论 了一 般 时滞 系统 的 O 一 4结 567 讨 . r 稳定性 问题 , 且 得 到 了有效 的判别 方法 ; 合 实 并 结 际系统稳 定性对 参数变 化区域 的要求 , 面将 讨 论 下
a K<1 (T— e T— ,a K) <一b +( '— r<e[ a F
A—a—b 一 = e 0 () 4
令 s A , ( ) 可化为 = r则 4 式
S T~b e —a r・ ~= 0 () 5
根 据 Hae 第二 定理 , ys 可得结论 : 方程 ( ) 5 的根满 足
R ( )< e S K当且仅 当
定 范围 内对参 数 的任 意组 合 总是 稳 定 的¨ ]文 .
为 消去 f a b r ( , , )=0中 的 V 根 据 H ys 理 , ae 定
阶实 系数时滞微 分方程
2 0 -90 到第 1稿 ,0 91-7收 到 修 改稿 090 -4收 20 -22
第 2期

计算机安全-密码学(2)

计算机安全-密码学(2)

注意:M必须比N小
为什么RSA 可以加解密
因为 Euler 定理的一个推论: Mkø(n)+1 = M mod N RSA 中: N=p.q ø(N)=(p-1)(q-1) 选择 e & d 使得ed=1 mod ø(N) 因此 存在k使得e.d=1+k.ø(N) 因此 Cd = (Me)d = M1+k.ø(N) = M mod N
RSA 算法 由Rivest、Shamir和Adleman于 1978年提出。该算法的数学基础 是初等数论中的Euler(欧拉)定 理,并建立在大整数因子的困难 性之上。
公开密钥算法
2 RSA算法简介
1978年,美国麻省理工学院(MIT)的研究小组成员: 李 维 斯 特 (Rivest) 、 沙 米 尔 (Shamir) 、 艾 德 曼 (Adleman)提出了一种基于公钥密码体制的优秀加密 算法——RSA算法。 RSA算法是一种分组密码体制算 法,它的保密强度是建立在具有大素数因子的合数, 其因子分解是困难的。 RSA得到了世界上的最广泛的应用,ISO在1992年颁 布的国际标准X.509中,将RSA算法正式纳入国际标准。 1999年美国参议院已通过了立法,规定电子数字签 名与手写签名的文件、邮件在美国具有同等的法律效 力。
算法
加密/解密
数字签名
密钥交换
RSA
Diffie-Hellman DSA
Y
N N
Y
N Y
Y
Y N
对公钥密码算法的误解
公开密钥算法比对称密钥密码算法更安全?
任何一种算法都依赖于密钥长度、破译密码的工作 量,从抗分析角度,没有一方更优越
公开密钥算法使对称密钥成为过时了的技术?

密码杂凑函数

密码杂凑函数

密码杂凑函数
Prene.,B;文华英
【期刊名称】《密码与信息》
【年(卷),期】1995(000)002
【摘要】杂凑函数作为一种保护消息真实性的工具在密码学上是七十年代末期引进的,很快就变得很清楚,它们在建立分组密码以解决远程通信和计算机网络领域里的其它安全问题方面是非常有用的。

本文概述了杂凑函数概念的来历,讨论了杂凑函数的应用,并介绍了已经遵循的构造杂凑函数的方法,此外,我们试图提供选择实际的杂凑函数所必需的信息,我们给出了杂凑函实际的结构和它们的效率的综述,并讨论了一些攻击。

特别值得注意的是处理杂凑函数
【总页数】20页(P33-52)
【作者】Prene.,B;文华英
【作者单位】不详;不详
【正文语种】中文
【中图分类】TN918.2
【相关文献】
1.密码学杂凑函数及其应用 [J], 张栋;李梦东;肖鹏;彭程培
2.基于分组密码的杂凑函数一种综合计算法 [J], Prene.,B;杜三明
3.密码杂凑函数及其安全性分析 [J], 关振胜
4.基于密码杂凑函数的安全规则匹配优化算法 [J], 李冬;李明;陈琳;王云霄;郭小燕;张丞
5.基于密码杂凑函数的安全规则匹配优化算法 [J], 李冬[1];李明[1];陈琳[1];王云霄[1];郭小燕[1];张丞[1]
因版权原因,仅展示原文概要,查看原文内容请购买。

四大安全会议论文题目

四大安全会议论文题目

2009and2010Papers:Big-4Security ConferencespvoOctober13,2010NDSS20091.Document Structure Integrity:A Robust Basis for Cross-site Scripting Defense.Y.Nadji,P.Saxena,D.Song2.An Efficient Black-box Technique for Defeating Web Application Attacks.R.Sekar3.Noncespaces:Using Randomization to Enforce Information Flow Tracking and Thwart Cross-Site Scripting Attacks.M.Van Gundy,H.Chen4.The Blind Stone Tablet:Outsourcing Durability to Untrusted Parties.P.Williams,R.Sion,D.Shasha5.Two-Party Computation Model for Privacy-Preserving Queries over Distributed Databases.S.S.M.Chow,J.-H.Lee,L.Subramanian6.SybilInfer:Detecting Sybil Nodes using Social Networks.G.Danezis,P.Mittal7.Spectrogram:A Mixture-of-Markov-Chains Model for Anomaly Detection in Web Traffic.Yingbo Song,Angelos D.Keromytis,Salvatore J.Stolfo8.Detecting Forged TCP Reset Packets.Nicholas Weaver,Robin Sommer,Vern Paxson9.Coordinated Scan Detection.Carrie Gates10.RB-Seeker:Auto-detection of Redirection Botnets.Xin Hu,Matthew Knysz,Kang G.Shin11.Scalable,Behavior-Based Malware Clustering.Ulrich Bayer,Paolo Milani Comparetti,Clemens Hlauschek,Christopher Kruegel,Engin Kirda12.K-Tracer:A System for Extracting Kernel Malware Behavior.Andrea Lanzi,Monirul I.Sharif,Wenke Lee13.RAINBOW:A Robust And Invisible Non-Blind Watermark for Network Flows.Amir Houmansadr,Negar Kiyavash,Nikita Borisov14.Traffic Morphing:An Efficient Defense Against Statistical Traffic Analysis.Charles V.Wright,Scott E.Coull,Fabian Monrose15.Recursive DNS Architectures and Vulnerability Implications.David Dagon,Manos Antonakakis,Kevin Day,Xiapu Luo,Christopher P.Lee,Wenke Lee16.Analyzing and Comparing the Protection Quality of Security Enhanced Operating Systems.Hong Chen,Ninghui Li,Ziqing Mao17.IntScope:Automatically Detecting Integer Overflow Vulnerability in X86Binary Using Symbolic Execution.Tielei Wang,Tao Wei,Zhiqiang Lin,Wei Zou18.Safe Passage for Passwords and Other Sensitive Data.Jonathan M.McCune,Adrian Perrig,Michael K.Reiter19.Conditioned-safe Ceremonies and a User Study of an Application to Web Authentication.Chris Karlof,J.Doug Tygar,David Wagner20.CSAR:A Practical and Provable Technique to Make Randomized Systems Accountable.Michael Backes,Peter Druschel,Andreas Haeberlen,Dominique UnruhOakland20091.Wirelessly Pickpocketing a Mifare Classic Card.(Best Practical Paper Award)Flavio D.Garcia,Peter van Rossum,Roel Verdult,Ronny Wichers Schreur2.Plaintext Recovery Attacks Against SSH.Martin R.Albrecht,Kenneth G.Paterson,Gaven J.Watson3.Exploiting Unix File-System Races via Algorithmic Complexity Attacks.Xiang Cai,Yuwei Gui,Rob Johnson4.Practical Mitigations for Timing-Based Side-Channel Attacks on Modern x86Processors.Bart Coppens,Ingrid Verbauwhede,Bjorn De Sutter,Koen De Bosschere5.Non-Interference for a Practical DIFC-Based Operating System.Maxwell Krohn,Eran Tromer6.Native Client:A Sandbox for Portable,Untrusted x86Native Code.(Best Paper Award)B.Yee,D.Sehr,G.Dardyk,B.Chen,R.Muth,T.Ormandy,S.Okasaka,N.Narula,N.Fullagar7.Automatic Reverse Engineering of Malware Emulators.(Best Student Paper Award)Monirul Sharif,Andrea Lanzi,Jonathon Giffin,Wenke Lee8.Prospex:Protocol Specification Extraction.Paolo Milani Comparetti,Gilbert Wondracek,Christopher Kruegel,Engin Kirda9.Quantifying Information Leaks in Outbound Web Traffic.Kevin Borders,Atul Prakash10.Automatic Discovery and Quantification of Information Leaks.Michael Backes,Boris Kopf,Andrey Rybalchenko11.CLAMP:Practical Prevention of Large-Scale Data Leaks.Bryan Parno,Jonathan M.McCune,Dan Wendlandt,David G.Andersen,Adrian Perrig12.De-anonymizing Social Networks.Arvind Narayanan,Vitaly Shmatikov13.Privacy Weaknesses in Biometric Sketches.Koen Simoens,Pim Tuyls,Bart Preneel14.The Mastermind Attack on Genomic Data.Michael T.Goodrich15.A Logic of Secure Systems and its Application to Trusted Computing.Anupam Datta,Jason Franklin,Deepak Garg,Dilsun Kaynar16.Formally Certifying the Security of Digital Signature Schemes.Santiago Zanella-Beguelin,Gilles Barthe,Benjamin Gregoire,Federico Olmedo17.An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols.Ralf Kuesters,Tomasz Truderung18.Sphinx:A Compact and Provably Secure Mix Format.George Danezis,Ian Goldberg19.DSybil:Optimal Sybil-Resistance for Recommendation Systems.Haifeng Yu,Chenwei Shi,Michael Kaminsky,Phillip B.Gibbons,Feng Xiao20.Fingerprinting Blank Paper Using Commodity Scanners.William Clarkson,Tim Weyrich,Adam Finkelstein,Nadia Heninger,Alex Halderman,Ed Felten 21.Tempest in a Teapot:Compromising Reflections Revisited.Michael Backes,Tongbo Chen,Markus Duermuth,Hendrik P.A.Lensch,Martin Welk22.Blueprint:Robust Prevention of Cross-site Scripting Attacks for Existing Browsers.Mike Ter Louw,V.N.Venkatakrishnan23.Pretty-Bad-Proxy:An Overlooked Adversary in Browsers’HTTPS Deployments.Shuo Chen,Ziqing Mao,Yi-Min Wang,Ming Zhang24.Secure Content Sniffing for Web Browsers,or How to Stop Papers from Reviewing Themselves.Adam Barth,Juan Caballero,Dawn Song25.It’s No Secret:Measuring the Security and Reliability of Authentication via’Secret’Questions.Stuart Schechter,A.J.Bernheim Brush,Serge Egelman26.Password Cracking Using Probabilistic Context-Free Grammars.Matt Weir,Sudhir Aggarwal,Bill Glodek,Breno de MedeirosUSENIX Security2009promising Electromagnetic Emanations of Wired and Wireless Keyboards.(Outstanding Student Paper)Martin Vuagnoux,Sylvain Pasini2.Peeping Tom in the Neighborhood:Keystroke Eavesdropping on Multi-User Systems.Kehuan Zhang,XiaoFeng Wang3.A Practical Congestion Attack on Tor Using Long Paths,Nathan S.Evans,Roger Dingledine,Christian Grothoff4.Baggy Bounds Checking:An Efficient and Backwards-Compatible Defense against Out-of-Bounds Errors.Periklis Akritidis,Manuel Costa,Miguel Castro,Steven Hand5.Dynamic Test Generation to Find Integer Bugs in x86Binary Linux Programs.David Molnar,Xue Cong Li,David A.Wagner6.NOZZLE:A Defense Against Heap-spraying Code Injection Attacks.Paruj Ratanaworabhan,Benjamin Livshits,Benjamin Zorn7.Detecting Spammers with SNARE:Spatio-temporal Network-level Automatic Reputation Engine.Shuang Hao,Nadeem Ahmed Syed,Nick Feamster,Alexander G.Gray,Sven Krasser8.Improving Tor using a TCP-over-DTLS Tunnel.Joel Reardon,Ian Goldberg9.Locating Prefix Hijackers using LOCK.Tongqing Qiu,Lusheng Ji,Dan Pei,Jia Wang,Jun(Jim)Xu,Hitesh Ballani10.GATEKEEPER:Mostly Static Enforcement of Security and Reliability Policies for JavaScript Code.Salvatore Guarnieri,Benjamin Livshits11.Cross-Origin JavaScript Capability Leaks:Detection,Exploitation,and Defense.Adam Barth,Joel Weinberger,Dawn Song12.Memory Safety for Low-Level Software/Hardware Interactions.John Criswell,Nicolas Geoffray,Vikram Adve13.Physical-layer Identification of RFID Devices.Boris Danev,Thomas S.Heydt-Benjamin,Srdjan CapkunCP:Secure Remote Storage for Computational RFIDs.Mastooreh Salajegheh,Shane Clark,Benjamin Ransford,Kevin Fu,Ari Juels15.Jamming-resistant Broadcast Communication without Shared Keys.Christina Popper,Mario Strasser,Srdjan Capkun16.xBook:Redesigning Privacy Control in Social Networking Platforms.Kapil Singh,Sumeer Bhola,Wenke Lee17.Nemesis:Preventing Authentication and Access Control Vulnerabilities in Web Applications.Michael Dalton,Christos Kozyrakis,Nickolai Zeldovich18.Static Enforcement of Web Application Integrity Through Strong Typing.William Robertson,Giovanni Vigna19.Vanish:Increasing Data Privacy with Self-Destructing Data.(Outstanding Student Paper)Roxana Geambasu,Tadayoshi Kohno,Amit A.Levy,Henry M.Levy20.Efficient Data Structures for Tamper-Evident Logging.Scott A.Crosby,Dan S.Wallach21.VPriv:Protecting Privacy in Location-Based Vehicular Services.Raluca Ada Popa,Hari Balakrishnan,Andrew J.Blumberg22.Effective and Efficient Malware Detection at the End Host.Clemens Kolbitsch,Paolo Milani Comparetti,Christopher Kruegel,Engin Kirda,Xiaoyong Zhou,XiaoFeng Wang 23.Protecting Confidential Data on Personal Computers with Storage Capsules.Kevin Borders,Eric Vander Weele,Billy Lau,Atul Prakash24.Return-Oriented Rootkits:Bypassing Kernel Code Integrity Protection Mechanisms.Ralf Hund,Thorsten Holz,Felix C.Freiling25.Crying Wolf:An Empirical Study of SSL Warning Effectiveness.Joshua Sunshine,Serge Egelman,Hazim Almuhimedi,Neha Atri,Lorrie Faith Cranor26.The Multi-Principal OS Construction of the Gazelle Web Browser.Helen J.Wang,Chris Grier,Alex Moshchuk,Samuel T.King,Piali Choudhury,Herman VenterACM CCS20091.Attacking cryptographic schemes based on”perturbation polynomials”.Martin Albrecht,Craig Gentry,Shai Halevi,Jonathan Katz2.Filter-resistant code injection on ARM.Yves Younan,Pieter Philippaerts,Frank Piessens,Wouter Joosen,Sven Lachmund,Thomas Walter3.False data injection attacks against state estimation in electric power grids.Yao Liu,Michael K.Reiter,Peng Ning4.EPC RFID tag security weaknesses and defenses:passport cards,enhanced drivers licenses,and beyond.Karl Koscher,Ari Juels,Vjekoslav Brajkovic,Tadayoshi Kohno5.An efficient forward private RFID protocol.Come Berbain,Olivier Billet,Jonathan Etrog,Henri Gilbert6.RFID privacy:relation between two notions,minimal condition,and efficient construction.Changshe Ma,Yingjiu Li,Robert H.Deng,Tieyan Li7.CoSP:a general framework for computational soundness proofs.Michael Backes,Dennis Hofheinz,Dominique Unruh8.Reactive noninterference.Aaron Bohannon,Benjamin C.Pierce,Vilhelm Sjoberg,Stephanie Weirich,Steve Zdancewicputational soundness for key exchange protocols with symmetric encryption.Ralf Kusters,Max Tuengerthal10.A probabilistic approach to hybrid role mining.Mario Frank,Andreas P.Streich,David A.Basin,Joachim M.Buhmann11.Efficient pseudorandom functions from the decisional linear assumption and weaker variants.Allison B.Lewko,Brent Waters12.Improving privacy and security in multi-authority attribute-based encryption.Melissa Chase,Sherman S.M.Chow13.Oblivious transfer with access control.Jan Camenisch,Maria Dubovitskaya,Gregory Neven14.NISAN:network information service for anonymization networks.Andriy Panchenko,Stefan Richter,Arne Rache15.Certificateless onion routing.Dario Catalano,Dario Fiore,Rosario Gennaro16.ShadowWalker:peer-to-peer anonymous communication using redundant structured topologies.Prateek Mittal,Nikita Borisov17.Ripley:automatically securing web2.0applications through replicated execution.K.Vikram,Abhishek Prateek,V.Benjamin Livshits18.HAIL:a high-availability and integrity layer for cloud storage.Kevin D.Bowers,Ari Juels,Alina Oprea19.Hey,you,get offof my cloud:exploring information leakage in third-party compute clouds.Thomas Ristenpart,Eran Tromer,Hovav Shacham,Stefan Savage20.Dynamic provable data possession.C.Christopher Erway,Alptekin Kupcu,Charalampos Papamanthou,Roberto Tamassia21.On cellular botnets:measuring the impact of malicious devices on a cellular network core.Patrick Traynor,Michael Lin,Machigar Ongtang,Vikhyath Rao,Trent Jaeger,Patrick Drew McDaniel,Thomas Porta 22.On lightweight mobile phone application certification.William Enck,Machigar Ongtang,Patrick Drew McDaniel23.SMILE:encounter-based trust for mobile social services.Justin Manweiler,Ryan Scudellari,Landon P.Cox24.Battle of Botcraft:fighting bots in online games with human observational proofs.Steven Gianvecchio,Zhenyu Wu,Mengjun Xie,Haining Wang25.Fides:remote anomaly-based cheat detection using client emulation.Edward C.Kaiser,Wu-chang Feng,Travis Schluessler26.Behavior based software theft detection.Xinran Wang,Yoon-chan Jhi,Sencun Zhu,Peng Liu27.The fable of the bees:incentivizing robust revocation decision making in ad hoc networks.Steffen Reidt,Mudhakar Srivatsa,Shane Balfe28.Effective implementation of the cell broadband engineTM isolation loader.Masana Murase,Kanna Shimizu,Wilfred Plouffe,Masaharu Sakamoto29.On achieving good operating points on an ROC plane using stochastic anomaly score prediction.Muhammad Qasim Ali,Hassan Khan,Ali Sajjad,Syed Ali Khayam30.On non-cooperative location privacy:a game-theoretic analysis.Julien Freudiger,Mohammad Hossein Manshaei,Jean-Pierre Hubaux,David C.Parkes31.Privacy-preserving genomic computation through program specialization.Rui Wang,XiaoFeng Wang,Zhou Li,Haixu Tang,Michael K.Reiter,Zheng Dong32.Feeling-based location privacy protection for location-based services.Toby Xu,Ying Cai33.Multi-party off-the-record messaging.Ian Goldberg,Berkant Ustaoglu,Matthew Van Gundy,Hao Chen34.The bayesian traffic analysis of mix networks.Carmela Troncoso,George Danezis35.As-awareness in Tor path selection.Matthew Edman,Paul F.Syverson36.Membership-concealing overlay networks.Eugene Y.Vasserman,Rob Jansen,James Tyra,Nicholas Hopper,Yongdae Kim37.On the difficulty of software-based attestation of embedded devices.Claude Castelluccia,Aurelien Francillon,Daniele Perito,Claudio Soriente38.Proximity-based access control for implantable medical devices.Kasper Bonne Rasmussen,Claude Castelluccia,Thomas S.Heydt-Benjamin,Srdjan Capkun39.XCS:cross channel scripting and its impact on web applications.Hristo Bojinov,Elie Bursztein,Dan Boneh40.A security-preserving compiler for distributed programs:from information-flow policies to cryptographic mechanisms.Cedric Fournet,Gurvan Le Guernic,Tamara Rezk41.Finding bugs in exceptional situations of JNI programs.Siliang Li,Gang Tan42.Secure open source collaboration:an empirical study of Linus’law.Andrew Meneely,Laurie A.Williams43.On voting machine design for verification and testability.Cynthia Sturton,Susmit Jha,Sanjit A.Seshia,David Wagner44.Secure in-VM monitoring using hardware virtualization.Monirul I.Sharif,Wenke Lee,Weidong Cui,Andrea Lanzi45.A metadata calculus for secure information sharing.Mudhakar Srivatsa,Dakshi Agrawal,Steffen Reidt46.Multiple password interference in text passwords and click-based graphical passwords.Sonia Chiasson,Alain Forget,Elizabeth Stobert,Paul C.van Oorschot,Robert Biddle47.Can they hear me now?:a security analysis of law enforcement wiretaps.Micah Sherr,Gaurav Shah,Eric Cronin,Sandy Clark,Matt Blaze48.English shellcode.Joshua Mason,Sam Small,Fabian Monrose,Greg MacManus49.Learning your identity and disease from research papers:information leaks in genome wide association study.Rui Wang,Yong Fuga Li,XiaoFeng Wang,Haixu Tang,Xiao-yong Zhou50.Countering kernel rootkits with lightweight hook protection.Zhi Wang,Xuxian Jiang,Weidong Cui,Peng Ning51.Mapping kernel objects to enable systematic integrity checking.Martim Carbone,Weidong Cui,Long Lu,Wenke Lee,Marcus Peinado,Xuxian Jiang52.Robust signatures for kernel data structures.Brendan Dolan-Gavitt,Abhinav Srivastava,Patrick Traynor,Jonathon T.Giffin53.A new cell counter based attack against tor.Zhen Ling,Junzhou Luo,Wei Yu,Xinwen Fu,Dong Xuan,Weijia Jia54.Scalable onion routing with torsk.Jon McLachlan,Andrew Tran,Nicholas Hopper,Yongdae Kim55.Anonymous credentials on a standard java card.Patrik Bichsel,Jan Camenisch,Thomas Gros,Victor Shouprge-scale malware indexing using function-call graphs.Xin Hu,Tzi-cker Chiueh,Kang G.Shin57.Dispatcher:enabling active botnet infiltration using automatic protocol reverse-engineering.Juan Caballero,Pongsin Poosankam,Christian Kreibich,Dawn Xiaodong Song58.Your botnet is my botnet:analysis of a botnet takeover.Brett Stone-Gross,Marco Cova,Lorenzo Cavallaro,Bob Gilbert,MartinSzydlowski,Richard A.Kemmerer,Christopher Kruegel,Giovanni VignaNDSS20101.Server-side Verification of Client Behavior in Online Games.Darrell Bethea,Robert Cochran and Michael Reiter2.Defeating Vanish with Low-Cost Sybil Attacks Against Large DHTs.S.Wolchok,O.S.Hofmann,N.Heninger,E.W.Felten,J.A.Halderman,C.J.Rossbach,B.Waters,E.Witchel3.Stealth DoS Attacks on Secure Channels.Amir Herzberg and Haya Shulman4.Protecting Browsers from Extension Vulnerabilities.Adam Barth,Adrienne Porter Felt,Prateek Saxena,and Aaron Boodman5.Adnostic:Privacy Preserving Targeted Advertising.Vincent Toubiana,Arvind Narayanan,Dan Boneh,Helen Nissenbaum and Solon Barocas6.FLAX:Systematic Discovery of Client-side Validation Vulnerabilities in Rich Web Applications.Prateek Saxena,Steve Hanna,Pongsin Poosankam and Dawn Song7.Effective Anomaly Detection with Scarce Training Data.William Robertson,Federico Maggi,Christopher Kruegel and Giovanni Vignarge-Scale Automatic Classification of Phishing Pages.Colin Whittaker,Brian Ryner and Marria Nazif9.A Systematic Characterization of IM Threats using Honeypots.Iasonas Polakis,Thanasis Petsas,Evangelos P.Markatos and Spiros Antonatos10.On Network-level Clusters for Spam Detection.Zhiyun Qian,Zhuoqing Mao,Yinglian Xie and Fang Yu11.Improving Spam Blacklisting Through Dynamic Thresholding and Speculative Aggregation.Sushant Sinha,Michael Bailey and Farnam Jahanian12.Botnet Judo:Fighting Spam with Itself.A.Pitsillidis,K.Levchenko,C.Kreibich,C.Kanich,G.M.Voelker,V.Paxson,N.Weaver,S.Savage13.Contractual Anonymity.Edward J.Schwartz,David Brumley and Jonathan M.McCune14.A3:An Extensible Platform for Application-Aware Anonymity.Micah Sherr,Andrew Mao,William R.Marczak,Wenchao Zhou,Boon Thau Loo,and Matt Blaze15.When Good Randomness Goes Bad:Virtual Machine Reset Vulnerabilities and Hedging Deployed Cryptography.Thomas Ristenpart and Scott Yilek16.InvisiType:Object-Oriented Security Policies.Jiwon Seo and Monica m17.A Security Evaluation of DNSSEC with NSEC3.Jason Bau and John Mitchell18.On the Safety of Enterprise Policy Deployment.Yudong Gao,Ni Pan,Xu Chen and Z.Morley Mao19.Where Do You Want to Go Today?Escalating Privileges by Pathname Manipulation.Suresh Chari,Shai Halevi and Wietse Venema20.Joe-E:A Security-Oriented Subset of Java.Adrian Mettler,David Wagner and Tyler Close21.Preventing Capability Leaks in Secure JavaScript Subsets.Matthew Finifter,Joel Weinberger and Adam Barth22.Binary Code Extraction and Interface Identification for Security Applications.Juan Caballero,Noah M.Johnson,Stephen McCamant,and Dawn Song23.Automatic Reverse Engineering of Data Structures from Binary Execution.Zhiqiang Lin,Xiangyu Zhang and Dongyan Xu24.Efficient Detection of Split Personalities in Malware.Davide Balzarotti,Marco Cova,Christoph Karlberger,Engin Kirda,Christopher Kruegel and Giovanni VignaOakland20101.Inspector Gadget:Automated Extraction of Proprietary Gadgets from Malware Binaries.Clemens Kolbitsch Thorsten Holz,Christopher Kruegel,Engin Kirda2.Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors.Matt Fredrikson,Mihai Christodorescu,Somesh Jha,Reiner Sailer,Xifeng Yan3.Identifying Dormant Functionality in Malware Programs.Paolo Milani Comparetti,Guido Salvaneschi,Clemens Kolbitsch,Engin Kirda,Christopher Kruegel,Stefano Zanero4.Reconciling Belief and Vulnerability in Information Flow.Sardaouna Hamadou,Vladimiro Sassone,Palamidessi5.Towards Static Flow-Based Declassification for Legacy and Untrusted Programs.Bruno P.S.Rocha,Sruthi Bandhakavi,Jerry I.den Hartog,William H.Winsborough,Sandro Etalle6.Non-Interference Through Secure Multi-Execution.Dominique Devriese,Frank Piessens7.Object Capabilities and Isolation of Untrusted Web Applications.Sergio Maffeis,John C.Mitchell,Ankur Taly8.TrustVisor:Efficient TCB Reduction and Attestation.Jonathan McCune,Yanlin Li,Ning Qu,Zongwei Zhou,Anupam Datta,Virgil Gligor,Adrian Perrig9.Overcoming an Untrusted Computing Base:Detecting and Removing Malicious Hardware Automatically.Matthew Hicks,Murph Finnicum,Samuel T.King,Milo M.K.Martin,Jonathan M.Smith10.Tamper Evident Microprocessors.Adam Waksman,Simha Sethumadhavan11.Side-Channel Leaks in Web Applications:a Reality Today,a Challenge Tomorrow.Shuo Chen,Rui Wang,XiaoFeng Wang Kehuan Zhang12.Investigation of Triangular Spamming:a Stealthy and Efficient Spamming Technique.Zhiyun Qian,Z.Morley Mao,Yinglian Xie,Fang Yu13.A Practical Attack to De-Anonymize Social Network Users.Gilbert Wondracek,Thorsten Holz,Engin Kirda,Christopher Kruegel14.SCiFI-A System for Secure Face Identification.(Best Paper)Margarita Osadchy,Benny Pinkas,Ayman Jarrous,Boaz Moskovich15.Round-Efficient Broadcast Authentication Protocols for Fixed Topology Classes.Haowen Chan,Adrian Perrig16.Revocation Systems with Very Small Private Keys.Allison Lewko,Amit Sahai,Brent Waters17.Authenticating Primary Users’Signals in Cognitive Radio Networks via Integrated Cryptographic and Wireless Link Signatures.Yao Liu,Peng Ning,Huaiyu Dai18.Outside the Closed World:On Using Machine Learning For Network Intrusion Detection.Robin Sommer,Vern Paxson19.All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution(but might have been afraid to ask).Thanassis Avgerinos,Edward Schwartz,David Brumley20.State of the Art:Automated Black-Box Web Application Vulnerability Testing.Jason Bau,Elie Bursztein,Divij Gupta,John Mitchell21.A Proof-Carrying File System.Deepak Garg,Frank Pfenning22.Scalable Parametric Verification of Secure Systems:How to Verify Ref.Monitors without Worrying about Data Structure Size.Jason Franklin,Sagar Chaki,Anupam Datta,Arvind Seshadri23.HyperSafe:A Lightweight Approach to Provide Lifetime Hypervisor Control-Flow Integrity.Zhi Wang,Xuxian Jiang24.How Good are Humans at Solving CAPTCHAs?A Large Scale Evaluation.Elie Bursztein,Steven Bethard,John C.Mitchell,Dan Jurafsky,Celine Fabry25.Bootstrapping Trust in Commodity Computers.Bryan Parno,Jonathan M.McCune,Adrian Perrig26.Chip and PIN is Broken.(Best Practical Paper)Steven J.Murdoch,Saar Drimer,Ross Anderson,Mike Bond27.Experimental Security Analysis of a Modern Automobile.K.Koscher,A.Czeskis,F.Roesner,S.Patel,T.Kohno,S.Checkoway,D.McCoy,B.Kantor,D.Anderson,H.Shacham,S.Savage 28.On the Incoherencies in Web Browser Access Control Policies.Kapil Singh,Alexander Moshchuk,Helen J.Wang,Wenke Lee29.ConScript:Specifying and Enforcing Fine-Grained Security Policies for JavaScript in the Browser.Leo Meyerovich,Benjamin Livshits30.TaintScope:A Checksum-Aware Directed Fuzzing Tool for Automatic Software Vulnerability Detection.(Best Student Paper)Tielei Wang,Tao Wei,Guofei Gu,Wei Zou31.A Symbolic Execution Framework for JavaScript.Prateek Saxena,Devdatta Akhawe,Steve Hanna,Stephen McCamant,Dawn Song,Feng MaoUSENIX Security20101.Adapting Software Fault Isolation to Contemporary CPU Architectures.David Sehr,Robert Muth,CliffBiffle,Victor Khimenko,Egor Pasko,Karl Schimpf,Bennet Yee,Brad Chen2.Making Linux Protection Mechanisms Egalitarian with UserFS.Taesoo Kim and Nickolai Zeldovich3.Capsicum:Practical Capabilities for UNIX.(Best Student Paper)Robert N.M.Watson,Jonathan Anderson,Ben Laurie,Kris Kennaway4.Structuring Protocol Implementations to Protect Sensitive Data.Petr Marchenko,Brad Karp5.PrETP:Privacy-Preserving Electronic Toll Pricing.Josep Balasch,Alfredo Rial,Carmela Troncoso,Bart Preneel,Ingrid Verbauwhede,Christophe Geuens6.An Analysis of Private Browsing Modes in Modern Browsers.Gaurav Aggarwal,Elie Bursztein,Collin Jackson,Dan Boneh7.BotGrep:Finding P2P Bots with Structured Graph Analysis.Shishir Nagaraja,Prateek Mittal,Chi-Yao Hong,Matthew Caesar,Nikita Borisov8.Fast Regular Expression Matching Using Small TCAMs for Network Intrusion Detection and Prevention Systems.Chad R.Meiners,Jignesh Patel,Eric Norige,Eric Torng,Alex X.Liu9.Searching the Searchers with SearchAudit.John P.John,Fang Yu,Yinglian Xie,Martin Abadi,Arvind Krishnamurthy10.Toward Automated Detection of Logic Vulnerabilities in Web Applications.Viktoria Felmetsger,Ludovico Cavedon,Christopher Kruegel,Giovanni Vigna11.Baaz:A System for Detecting Access Control Misconfigurations.Tathagata Das,Ranjita Bhagwan,Prasad Naldurg12.Cling:A Memory Allocator to Mitigate Dangling Pointers.Periklis Akritidis13.ZKPDL:A Language-Based System for Efficient Zero-Knowledge Proofs and Electronic Cash.Sarah Meiklejohn,C.Chris Erway,Alptekin Kupcu,Theodora Hinkle,Anna Lysyanskaya14.P4P:Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users.Yitao Duan,John Canny,Justin Zhan,15.SEPIA:Privacy-Preserving Aggregation of Multi-Domain Network Events and Statistics.Martin Burkhart,Mario Strasser,Dilip Many,Xenofontas Dimitropoulos16.Dude,Where’s That IP?Circumventing Measurement-based IP Geolocation.Phillipa Gill,Yashar Ganjali,Bernard Wong,David Lie17.Idle Port Scanning and Non-interference Analysis of Network Protocol Stacks Using Model Checking.Roya Ensafi,Jong Chun Park,Deepak Kapur,Jedidiah R.Crandall18.Building a Dynamic Reputation System for DNS.Manos Antonakakis,Roberto Perdisci,David Dagon,Wenke Lee,Nick Feamster19.Scantegrity II Municipal Election at Takoma Park:The First E2E Binding Governmental Election with Ballot Privacy.R.Carback,D.Chaum,J.Clark,J.Conway,A.Essex,P.S.Herrnson,T.Mayberry,S.Popoveniuc,R.L.Rivest,E.Shen,A.T.Sherman,P.L.Vora20.Acoustic Side-Channel Attacks on Printers.Michael Backes,Markus Durmuth,Sebastian Gerling,Manfred Pinkal,Caroline Sporleder21.Security and Privacy Vulnerabilities of In-Car Wireless Networks:A Tire Pressure Monitoring System Case Study.Ishtiaq Rouf,Rob Miller,Hossen Mustafa,Travis Taylor,Sangho Oh,Wenyuan Xu,Marco Gruteser,Wade Trappe,Ivan Seskar 22.VEX:Vetting Browser Extensions for Security Vulnerabilities.(Best Paper)Sruthi Bandhakavi,Samuel T.King,P.Madhusudan,Marianne Winslett23.Securing Script-Based Extensibility in Web Browsers.Vladan Djeric,Ashvin Goel24.AdJail:Practical Enforcement of Confidentiality and Integrity Policies on Web Advertisements.Mike Ter Louw,Karthik Thotta Ganesh,V.N.Venkatakrishnan25.Realization of RF Distance Bounding.Kasper Bonne Rasmussen,Srdjan Capkun26.The Case for Ubiquitous Transport-Level Encryption.Andrea Bittau,Michael Hamburg,Mark Handley,David Mazieres,Dan Boneh27.Automatic Generation of Remediation Procedures for Malware Infections.Roberto Paleari,Lorenzo Martignoni,Emanuele Passerini,Drew Davidson,Matt Fredrikson,Jon Giffin,Somesh Jha28.Re:CAPTCHAs-Understanding CAPTCHA-Solving Services in an Economic Context.Marti Motoyama,Kirill Levchenko,Chris Kanich,Damon McCoy,Geoffrey M.Voelker,Stefan Savage29.Chipping Away at Censorship Firewalls with User-Generated Content.Sam Burnett,Nick Feamster,Santosh Vempala30.Fighting Coercion Attacks in Key Generation using Skin Conductance.Payas Gupta,Debin GaoACM CCS20101.Security Analysis of India’s Electronic Voting Machines.Scott Wolchok,Erik Wustrow,J.Alex Halderman,Hari Prasad,Rop Gonggrijp2.Dissecting One Click Frauds.Nicolas Christin,Sally S.Yanagihara,Keisuke Kamataki3.@spam:The Underground on140Characters or Less.Chris Grier,Kurt Thomas,Vern Paxson,Michael Zhang4.HyperSentry:Enabling Stealthy In-context Measurement of Hypervisor Integrity.Ahmed M.Azab,Peng Ning,Zhi Wang,Xuxian Jiang,Xiaolan Zhang,Nathan C.Skalsky5.Trail of Bytes:Efficient Support for Forensic Analysis.Srinivas Krishnan,Kevin Z.Snow,Fabian Monrose6.Survivable Key Compromise in Software Update Systems.Justin Samuel,Nick Mathewson,Justin Cappos,Roger Dingledine7.A Methodology for Empirical Analysis of the Permission-Based Security Models and its Application to Android.David Barrera,H.Gunes Kayacik,Paul C.van Oorschot,Anil Somayaji8.Mobile Location Tracking in Metropolitan Areas:malnets and others.Nathanial Husted,Steve Myers9.On Pairing Constrained Wireless Devices Based on Secrecy of Auxiliary Channels:The Case of Acoustic Eavesdropping.Tzipora Halevi,Nitesh Saxena10.PinDr0p:Using Single-Ended Audio Features to Determine Call Provenance.Vijay A.Balasubramaniyan,Aamir Poonawalla,Mustaque Ahamad,Michael T.Hunter,Patrick Traynor11.Building Efficient Fully Collusion-Resilient Traitor Tracing and Revocation Schemes.Sanjam Garg,Abishek Kumarasubramanian,Amit Sahai,Brent Waters12.Algebraic Pseudorandom Functions with Improved Efficiency from the Augmented Cascade.Dan Boneh,Hart Montgomery,Ananth Raghunathan13.Practical Leakage-Resilient Pseudorandom Generators.Yu Yu,Francois-Xavier Standaert,Olivier Pereira,Moti Yung14.Practical Leakage-Resilient Identity-Based Encryption from Simple Assumptions.Sherman S.M.Chow,Yevgeniy Dodis,Yannis Rouselakis,Brent Waters15.Testing Metrics for Password Creation Policies by Attacking Large Sets of Revealed Passwords.Matt Weir,Sudhir Aggarwal,Michael Collins,Henry Stern16.The Security of Modern Password Expiration:An Algorithmic Framework and Empirical Analysis.Yinqian Zhang,Fabian Monrose,Michael K.Reiter17.Attacks and Design of Image Recognition CAPTCHAs.Bin Zhu,JeffYan,Chao Yang,Qiujie Li,Jiu Liu,Ning Xu,Meng Yi18.Robusta:Taming the Native Beast of the JVM.Joseph Siefers,Gang Tan,Greg Morrisett19.Retaining Sandbox Containment Despite Bugs in Privileged Memory-Safe Code.Justin Cappos,Armon Dadgar,JeffRasley,Justin Samuel,Ivan Beschastnikh,Cosmin Barsan,Arvind Krishnamurthy,Thomas Anderson20.A Control Point for Reducing Root Abuse of File-System Privileges.Glenn Wurster,Paul C.van Oorschot21.Modeling Attacks on Physical Unclonable Functions.Ulrich Ruehrmair,Frank Sehnke,Jan Soelter,Gideon Dror,Srinivas Devadas,Juergen Schmidhuber22.Dismantling SecureMemory,CryptoMemory and CryptoRF.Flavio D.Garcia,Peter van Rossum,Roel Verdult,Ronny Wichers Schreur23.Attacking and Fixing PKCS#11Security Tokens.Matteo Bortolozzo,Matteo Centenaro,Riccardo Focardi,Graham Steel24.An Empirical Study of Privacy-Violating Information Flows in JavaScript Web Applications.Dongseok Jang,Ranjit Jhala,Sorin Lerner,Hovav Shacham25.DIFC Programs by Automatic Instrumentation.William Harris,Somesh Jha,Thomas Reps26.Predictive Black-box Mitigation of Timing Channels.Aslan Askarov,Danfeng Zhang,Andrew Myers27.In Search of an Anonymous and Secure Lookup:Attacks on Structured Peer-to-peer Anonymous Communication Systems.Qiyan Wang,Prateek Mittal,Nikita Borisov28.Recruiting New Tor Relays with BRAIDS.Rob Jansen,Nicholas Hopper,Yongdae Kim29.An Improved Algorithm for Tor Circuit Scheduling.Can Tang,Ian Goldberg30.Dissent:Accountable Anonymous Group Messaging.Henry Corrigan-Gibbs,Bryan Ford31.Abstraction by Set-Membership—Verifying Security Protocols and Web Services with Databases.Sebastian Moedersheim。

基于混沌系统的数字图像加密算法

基于混沌系统的数字图像加密算法

基于混沌系统的数字图像加密算法
罗军
【期刊名称】《计算机工程与设计》
【年(卷),期】2009(030)008
【摘要】提出了一种新的基于混沌系统的数字图像加密算法.首先对Lorenz系统产生的实值序列进行预处理得到伪随机的整数序列,然后利用预处理后的整数序列作为密钥流,对数字图像进行多轮的幻方变换和非线性变换,从而实现数字图像的加密,并对算法进行数字仿真和安全性分析.实验结果与理论分析表明,提出的数字图像加密算法具有较高的加密速度、良好的安全性能和抗攻击能力.
【总页数】3页(P1844-1845,1906)
【作者】罗军
【作者单位】重庆教育学院计算机与现代教育技术系,重庆400067
【正文语种】中文
【中图分类】TP309+.7
【相关文献】
1.基于一种广义Lorenz-Stenflo超混沌系统的数字图像加密算法的性能研究 [J], 徐扬;黄迎久;李海荣
2.基于五维混沌系统的数字图像加密算法 [J], 王晓飞;王光义
3.一种基于四维超混沌系统的数字图像加密算法 [J], 章秀君;吴志强;方正
4.基于优化的分数阶混沌系统的数字图像加密算法 [J], 朱林
5.一种基于五维超混沌系统的数字图像加密算法 [J], 庄志本;刘静漪;李军;邱达;陈世强
因版权原因,仅展示原文概要,查看原文内容请购买。

一类带有非线性摄动的时滞系统的鲁棒H∞控制


2 问题 的描 述
考 虑 带有非线 性摄 动 的时滞 系统
土( )= Az( )+Ad ( t t z t—h )+B ( )+f( t , t—h) t +E t , ut z( ) z( , ) w( )
zt ()= C t +Du() x( ) t,
z( )= () t t,
t∈ [ 一h’0 , ,]
尸( ()z t )tf z t ,( —h ,) z t, ( —h ,) ( ()z t )t ≤
口 z
T tGT x()+ z ( () G t T t—h )
( t—h , ) Vt∈ [ , c ) 0+ o,
() 2
其 中 , H 为 已知 的定 常 的结构 矩 阵 , 、 为 已知 的正 的常数 界 . G、 C t
第2 4卷
3 预备知识
引理 1 设 n0 ) n, 是 R 上 的两 个任意 的二 次型 函数 , 【 ( 和 ( ) 若存在 p , >0 使得 不等式 n0 ) (


( <0 ) 对任意非零向量 ER 都成立 , 则不等式 n ( <0 。 ) 对所有满足 n ( ≤0的任意 E , )
关键词 : 非线性摄动 ; 时滞系统 ; 线性矩 阵不等式 ; H 控制
中图 分 类 号 :2 1 0 3 文献标识码 : A
1 引 言
在各类工业系统中 , 时滞现象是极其普遍存在的 , 如造纸生产. 因此 , 时滞 系统 的控 制 问题 成 为 了近 年来 鲁棒 控制 研究 的热 点课 题 之一 . 多学 者 在理论 许
J n 2 0 u .0 7
V 12 o2 o.4 N .
第2 4卷 第 2期

基于Logistic映射和分段性映射的混沌Hash函数

r x / p , ∈[ 0 , P ]
1 Ha s h函数 及 混 沌 映 射
1 . 1 H a s h函数 特性
{ F ( p , )=( — P ) / ( 1 / 2一 P ) , ∈[ P , 1 2] /
A F ( P , 1一 ), ∈[ 1 / 2 , 1 ]
摘 要: 提 出一种基 于 L o g i s t i c 映射和分段性 映射 的混 沌 H a s h函数构 造。该算 法将 明文 信息分组并 转换 , 分别作为 L o g i s t i c 映射和分段性映射 的输入参数进行多次迭代 , 迭代生成 相应明文信 息的 中间 H a s h值 ,
第l 5卷 第 4期
重庆 科技 学 院学报 ( 自然 科学 版 )
2 0 1 3年 8月
基于 L o g i s t i c映射 和分 段 性 映射 的混沌 H a s h函数
冯艳茹 赵冬玲 李艳涛。
( 1 .济源职业技术学院, 河南 济源 4 5 9 0 0 0 ; 2 . 重庆大学计算机学院, 重庆 4 0 0 0 4 4 )
g i s t i c 映射 将产 生 混沌 效 应 。 与 映射 初 始 值 。构
成H a s h函数的密钥 , 它将被用于本算法的明文扩展
过程 中 。
1 . 3 分 段线 性混 沌映射
分 段 线性混 沌 映 射具 有 良好 的随机 统计 特 性 , 维 分段 线性 混沌 映射定 义如 下 :

H( ) 在 计算 上不可 行 ( 抗 强碰 撞性 ) 。 L o g i s t i c 混沌 映射 表达 式为 :
+ 1= ( 1一 ) ( 1 )
1 . 2 L o g i s t i c混沌映 射

施工计划的形容词

施工计划的形容词一、详细(detailed)- 单词释义:包含许多具体的部分、信息或元素。

- 单词用法:可用于描述施工计划涵盖众多细致的工作安排、时间节点、材料用量等方面。

例如“a detailed construction plan”。

- 近义词:thorough(彻底的、详尽的)- 短语搭配:detailed schedule(详细的日程安排),detailed blueprint(详细的蓝图)- 双语例句:- The contractor was impressed by the detailed construction plan. He said it was like a comprehensive guidebook for building a masterpiece.(承包商对详细的施工计划印象深刻。

他说这就像建造杰作的综合指南。

)二、合理(reasonable)- 单词释义:符合道理、逻辑或公平的标准。

- 单词用法:用于表示施工计划在资源分配、工期安排、工序衔接等方面合乎理性。

如“a reasonable construction plan”。

- 近义词:rational(理性的)- 短语搭配:reasonable budget(合理的预算),reasonable sequence(合理的顺序)- 双语例句:- This construction plan is reasonable. I mean, who would object to a plan that doesn't waste any resources? It's like finding a perfect balance on a seesaw.(这个施工计划是合理的。

我的意思是,谁会反对一个不浪费任何资源的计划呢?这就像在跷跷板上找到完美的平衡。

)- We all think the construction plan is reasonable. It's not too ambitious that it can't be achieved, nor too conservative that it wastes time.(我们都认为施工计划是合理的。

2012-57-9-TAC-采样一致+二阶积分器+非一致时变时延

A Sufficient Condition for Convergence of Sampled-DataConsensus for Double-Integrator Dynamics With Nonuniform and Time-Varying Communication Delays Jiahu Qin,Student Member,IEEE,andHuijun Gao,Senior Member,IEEEAbstract—This technical note investigates a discrete-time second-order consensus algorithm for networks of agents with nonuniform and time-varying communication delays under dynamically changing communica-tion topologies in a sampled-data setting.Some new proof techniques are proposed to perform the convergence analysis.It isfinally shown that under certain assumptions upon the velocity damping gain and the sampling pe-riod,consensus is achieved for arbitrary bounded time-varying commu-nication delays if the union of the associated digraphs of the interaction matrices in the presence of delays has a directed spanning tree frequently enough.Index Terms—Double-integrator agents,sampled-data consensus,span-ning tree,time-varying communication delays.I.I NTRODUCTIONIn recent years,consensus problems for agents with single-integrator dynamics have been studied from various perspectives(see,e.g.,[4], [7],[10],[11],[14],[16],[17],[26]).Taking into account that double-integrator dynamics can be used to model more complicated systems in reality,cooperative control for multiple agents with double-integrator dynamics has been studied extensively recently,see[12],[18]–[20], [23],[28]for continuous algorithms and[1]–[3],[5],[6],[8],[13]for discrete-time algorithms.In[8],a sampled-data algorithm is studied for double-integrator dy-namics through a Lyapunov-based approach.The analysis in[8]is lim-ited to an undirected network topology and cannot be extended to deal with the directed case.However,the informationflow might be directed in practical applications.In a similar sampled-data setting,[1]studies two sampled-data consensus algorithms,i.e.,the case with an absolute velocity damping term and the case with a relative velocity damping term,in the context of a directed network topology by extensively using matrix spectral analysis.Reference[2]extends the algorithms in[1]to deal with a dynamic directed network topology.References[5]and[6] mainly investigate sampled-data consensus for the case with a relative velocity damping term under a dynamic network topology.In[5],the network topologies are required to be both balanced and strongly con-nected at each sampling instant.On the other hand,considering that it might be difficult to measure the velocity information in practice,[6] Manuscript received November17,2009;revised September15,2010; August15,2011,and January24,2012;accepted January25,2012.Date of publication February17,2012;date of current version August24,2012.This work was supported in part by the National Natural Science Foundation of China under Grants60825303,60834003,and61021002,by the973Project (2009CB320600),and by the Foundation for the Author of National Excellent Doctoral Dissertation of China(2007B4).Recommended by Associate Editor H.Ito.J.Qin is with Harbin Institute of Technology,Harbin,China,and also with the Australian National University,Canberra,A.C.T.,Australia(e-mail:jiahu. qin@.au).H.Gao is with the Research Institute of Intelligent Control and Systems, Harbin Institute of Technology,Harbin150001,China(e-mail:hjgao@. cn).Color versions of one or more of thefigures in this paper are available online at .Digital Object Identifier10.1109/TAC.2012.2188425proposes a consensus strategy using the measurements of the relative positions between neighboring agents to estimate the relative velocities. In[13],consensus problems of second-order multi-agent systems with nonuniform time delays and dynamically changing topologies is investigated.However,the paper considers a discrete-time model es-timated by using the forward difference approximation method rather than a sampled-data model.In general,a sampled-data model is more realistic.Also,in[13],the weighting factors must be chosen from a finite set.With this background,we study the convergence of sam-pled-data consensus for double-integrator dynamics under dynamically changing topologies and allow the communication delays to be not only different but also time varying.Here,considering the weighting factors of directed edges between neighboring agents usually represent confi-dence or reliability of the transmitted information,it is more natural to consider choosing the weighting factors from an infinite set,which is more general than thefinite set case in[2]and[13].Moreover,dif-ferent from that in[13],A(k),the interaction matrix in the presence of delays at time t=kT,is introduced in this technical note and the dif-ference between A(k)and A(k),the adjacency matrix at time t=kT, is further explored as well.The reason for introducing A(k)is that it is more relevant than A(k)to the strategies investigated in this technical note.It is worth pointing out that the method employed to perform the convergence analysis is totally different from most of the existing liter-ature which heavily relies on analyzing the system matrix by spectral analysis.By using the similar transformation as that used in[13],we can treat the sampled-data consensus for double-integrator dynamics as the consensus for multiple agents modeled byfirst-integrator dynamics. Then,in order to make the transformed system dynamics mathemati-cally tractable,a new graphic method is proposed to specify the rela-tions between0(A(k)),the associated digraph of the interaction matrix in the presence of delays,and the the associated digraph of the trans-formed system matrix.Finally,motivated by the work in[22,Theorem 2.33]and[27],by employing the product properties of row-stochastic matrices from an infinite set,we present a sufficient condition in terms of the associated digraph of the interaction matrix in the presence of delays for the agents to reach consensus.Note here that the proving techniques employed in this technical note can be extended directly to derive similar results by considering the discrete-time model in[13]. The rest of the technical note is organized as follows.In Section II, we formulate the problem to be investigated and also provide some graph theory notations,while the convergence analysis is given in Section III.In Section IV,a numerical example is provided to show the effectiveness of the new result.Finally,some concluding remarks are drawn in Section V.II.B ACKGROUND AND P RELIMINARIESA.NotationsLet I n2n2n and0n;n2n2n denote,respectively,the identity matrix and the zero matrix,and1m2m be the column vector of all ones.Letand+denote,respectively,the set of nonnegative and positive integers.Given any matrix A=[a ij]2n2n,let diag(A) denote the diagonal matrix associated with A with the ith diagonal element equal to a ii.Hereafter,matrices are assumed to be compatible for algebraic operations if their dimensions are not explicitly stated.A matrix M2n2n is nonnegative,denoted as M 0,if all its entries are nonnegative.Let N2n2n.We write M N if M0N 0.A nonnegative matrix M is said to be row stochastic if all its row sums are1.Let k i=1M i=M k M k01111M1denote the left product of the matrices M k;M k01;111;M1.A row-stochastic matrix M is ergodic0018-9286/$31.00©2012IEEE(or indecomposable and aperiodic )if there exists a column vector f2nsuch that lim k !1M k =1n f T .B.Graph Theory NotationsLet G =(V ;E ;A )be a weighted digraph of order n with a finite nonempty set of nodes V =f 1;2;...;n g ,a set of edges E V 2V ,and a weighted adjacency matrix A =[a ij ]2n 2n with nonnegative adjacency elements a ij .An edge of G is denoted by (i;j ),meaning that there is a communication channel from agent i to agent j .The adjacency elements associated with the edges are positive,i.e.,(j;i )2E ,a ij >0.Moreover,we assume a ii =0for all i 2V .The set of neighbors of node i is denoted by N i =f j 2V :(j;i )2Eg .Denote by L =[l ij ]the Laplacian matrix associated with G ,where l ij =0a ij ,i =j ,and l ii=n k =1;k =i a ik .A directed path is a sequence of edges in a digraph of the form (i 1;i 2);(i 2;i 3);....A digraph has a directed spanning tree if there exists at least one node,called the root node,having a directed path to all the other nodes.A spanning subgraph G s of a directed graph G is a directed graph such that the node set V (G s )=V (G )and the edge set E (G s ) E (G ).Given a nonnegative matrix S =[s ij ]2n 2n ,the associated di-graph of S ,denoted by 0(S ),is the directed graph with the node set V =f 1;2;...;n g such that there is an edge in 0(S )from j to i if and only if s ij >0.Note that for arbitrary nonnegative matrices M;N2p 2p satisfying M N ,where >0,if 0(N )has a di-rected spanning tree,then 0(M )also has a directed spanning tree.C.Sampled-Data Consensus Algorithm for Double-Integrator DynamicsEach agent is regarded as a node in a digraph G of order n .Let T >0denote the sampling period and k2denote the discrete-time index.For notational simplicity,the sampling period T will be dropped in the sequel when it is clear from the context.We consider the following sampled-data discrete-time system which has been investigated in [1],[2],and [8]asr i (k +1)0r i (k )=T v i (k )+12T 2u i (k )v i (k +1)0v i (k )=T u i (k )(1)where x i (k )2p ,v i (k )2p and u i (k )2p are,respectively,the position,velocity and control input of agent i at time t =kT .For simplicity,we assume p =1.However,all results still hold for any p2+by introducing the notation of Kronecker product.In this technical note,we mainly consider the following discrete-time second-order consensus algorithm which takes into account the nonuniform and time-varying communication delays as u i (k )=0 v i (k )+j 2N (k )ij (k )(r j (k 0 ij (k ))0r i (k ))(2)where >0denotes the absolute velocity damping gain,N i (k )de-notes the neighbor set of agent i at time t =kT that varies with G (k )(i.e.,the dynamic communication topology at time t =kT ), ij (k )>0if agent i can receive the delayed position r j (k 0 ij (k ))from agent j at time t =kT while ij (k )=0otherwise,and 0 ij (k ) max ,where ij (k )2,is the communication delay from agent j to agent i .Here,we assume ii (t ) 0,that is,the time delays affect only the in-formation that is transmitted from one agent to another.Moreover,we assume that all the nonzero and hence positive weighting factors areboth uniformly lower and upper bounded,i.e., ij (k )2[ ;],where 0< < ,if j 2N i (k ).Remark 1:In general,(j;i )2E (G (k ))or a ij (k )>0,which cor-responds to an available communication channel from agent j to agent i at time t =kT ,does not imply ij (k )>0even if the reverse is true.This is mainly because the communication topologies are dynamicallychanging and the communication delays are time varying,which may destroy the continuity of information.Note that ij (k )>0requires a ij >0for the whole time between k 0 ij (k )and k .DefineA (k )= 11(k )111 1n (k )......... n 1(k )111 nn (k):To distinguish A (k )from the adjacency matrix A (k )at time t =kT ,we call A (k )the interaction matrix in the presence of delays to em-phasize that A (k )is closely related to not only the available commu-nication channel but also the information transmission in the presence of delays.Let L (k )be L (k )=D (k )0A (k ),where D (k )is a diag-onal matrix with the i th diagonal entrybeing n j =1;j =i ij (k ).In fact,0(A (k )),the associated digraph of A (k ),is a spanning subgraph of the communication topology G (k )at time t =kT .To illustrate,consider a team of n =3agents.The possible communication topologies are modeled by the digraph as shown in Fig.1.Assume the communica-tion delays 21(k )and 32(k ),k2,are all larger than 1T ,while the communication topology switches periodically between Ga and Gb at each sampling instant.Clearly,A (k )=03;3at each sampling instant.However,in the special case that there is no communication delay be-tween neighboring agents,0(A (k ))=G (k ).In the case that both the communication topology and the communication delays are time in-variant,0(A (k ))=G (k )after max time steps.We say that consensus is reached for algorithm (2)if for any initial position and velocity states,and any i;j 2Vlim k !1r i (k )=lim k !1r j (k )and lim k !1v i (k )=0:It is assumed that r i (k )=r i (0)and v i (k )=v i (0)for any k <0and i;j 2V .III.M AIN R ESULTSDenote G=f G 1;G 2;...;G m g as the finite set of all possible com-munication topologies for all the n agents.In the sequel,when we men-tion the union of a group of digraphs f G i ;...;G i g G,we mean a digraph with the node set V =f 1;2;...;n g and the edge set given by the union of the edge sets of G i ,j =1;...;k .Firstly,we perform the following model transformation,which helps us deal with the consensus problem for an equivalent trans-formed discrete-time system.Denote r (k )=[r 1(k );111;r n (k )]T ,v (k )=[v 1(k );111;v n (k )]T ,x (k )=(2= )v (k )+r (k ),andy (k )=[r (k )T x (k )T ]T.Then,applying algorithm (2)and by some manipulation,(1)can be written in a matrix form asy (k +1)=40(k )y (k )+`=14`(k )y (k 0`)(3)where we get the equation shown at the bottom of the next page,and 4`(k )=T2A `(k )0n;n2T +12T 2A `(k )0n;n;`=1;2;...; max :Here in 4p (k ),p =0;1;...; max ,the ij th element of A p (k )is either equal to ij (k )if ij (k )=p ,or equal to 0otherwise and L (k )is the Laplacian matrix of the digraph of A (k ).1ObviouslyA 0(k )+A 1(k )+111+A(k )=A (k ):The following lemma will allow us to perform the convergence anal-ysis by using the product properties of row-stochastic matrices.1NoteL (k )is different from the Laplacian matrix of the communicationtopology G(k).Fig.1.Two possible communication topologies for the three agents.Lemma 1:Let d (k )be the largest diagonal element of the Lapla-cian matrix L (k ),i.e.,d (k )=max if n j =1;j =i ij (k )g .If the ve-locity damping gain and the sampling period T satisfy the following condition:4 T 0 T >2and T 01 2T d (k )(4)then 4(k )=40(k )+41(k )+111+4(k );k2+,is a row-stochastic matrix with positive diagonal elements.Proof:It follows from A 0(k )+A 1(k )+111+A(k )=A (k )=diag L (k )0L (k )that4(k )=40(k )+41(k )+111+4(k )=411(k )412(k )421(k )422(k )(5)where 411(k )=(10( =2)T +( 2=4)T 2)I n 0(T 2=2)L (k ),412(k )=(( =2)T 0( 2=4)T 2)I n ,421(k )=(( =2)T +( 2=4)T 2)I n 0((2= )T +(1=2)T 2)L (k )422(k )=(10( =2)T 0( 2=4)T 2)I n .One can easily check from (4)that all the matrices 411(k ),412(k ),421(k ),and 422(k )are nonnegative with positive di-agonal elements.That is,4(k )is a nonnegative with positive diagonal elements.Finally,it follows straightforwardly from L (k )1n =1n that 4(k )is a row-stochastic matrix.Remark 2:By some manipulation,we can get that (4)is equivalent to the following condition:1+1+8T 2d (k )2T <p 501:(6)This is achieved by solving ( T )2+2 T 04<0and T 20 02T d (k ) 0,which can be considered the quadratic inequalities in T and ,respectively.In the sequel,4(k )will be used to denote the row-stochastic matrix as described in Lemma 1.In order to make the transformed system dynamics mathematically tractable in terms of 0(A (k )),the associated digraph of the interaction matrix in the presence of delays,we need to explore the relations be-tween 0(A (k ))and the associated digraph of the transformed system matrix 0(4(k )).To this end,a new graphic method is proposed as follows.Lemma 2:Given any digraph G (V ;E ).Let G 1(V 1;E 1)be a graph with n nodes and an empty edge set,that is,V 1=f n +1;n +2;...;2n g and E 1=.Let ~G(~V ;~E )be a digraph satisfying the fol-lowing conditions:(A)~V=V [V 1=f 1;...;n;n +1;...;2n g ;(B)there is an edge from node n +i to node i ,i.e.,(n +i;i )2~",for any i 2V ;(C)if (j;i )2E ,then (j;n +i )2~Efor any i;j 2V ;i =j .Then,G has a directed spanning tree if and only if ~Ghas a directed spanning tree.Proof:Necessity:Denote G s as a directed spanning tree of the digraph G .Assume,without loss of generality,`is the root node of G s .By rules (B )and (C ),split each edge (i;j )in G s into edges (i;n +j );(n +j;j )and add edge (n +`;`)for the root node `,then we canget a directed spanning tree for ~G.Sufficiency:Let ~Gs be a directed spanning tree of ~G .Note that by the definition of ~G,the digraph G can be obtained by contracting all the edges (n +i;i );i 2V in the digraph ~G.Thus,the operation of the edge contraction on ~Gs will result in a directed spanning tree,say G s ,of the digraph G .Based on the above lemma,now we have the following result.Lemma 3:Suppose that and T satisfy the inequality in (4).Let f z 1;z 2;...;z q g be any finite subsetof +.If the union of the digraphs 0(A (z 1));0(A (z 2));...;0(A (z q ))has a directed spanning tree,then the union of digraphs 0(4(z 1));0(4(z 2));...;0(4(z q ))also has a directed spanning tree.Proof:The union of the digraphs 0(4(z 1));0(4(z 2));...;0(4(z q ))hereby is exactly the digraph0(q l =14(z l )).Because and T satisfy (4),it follows that 4(z l ),l =1;2;...;q ,is a row-stochastic (and hence nonnegative)matrix with positive diagonal entries.Note that L (z l )=diag L (z l )0A (z l ).By observing the equation in (5),we get that there exists a positive number ,say =min f q (( =2)T 0( 2=4)T 2);(2= )T +(1=2)T 2g ,such that we get (7),as shown at the bottom of the page.It thus follows from ~M 12=I n that (n +i;i )20(q l =14(z l ))for any i 2V .On the other hand,~M 21=q l =1A (z l )implies that(j;i )20(q l =1A (z l ))if and only if (j;n +i )20(ql =14(z l ))for any i;j 2V ;i =j .Combining these arguments,we knowthat the digraphs0(q l =14(z l ))and0(ql =1A (z l ))correspondto the digraphs ~G and G ,respectively,as described in Lemma 2.Note that the digraph0(q l =1A (z l ))is just the union of digraphs 0(A (z 1));0(A (z 2));...;0(A (z q )).It then follows from Lemma 2that the digraph0(q l =14(z l ))has a directed spanning tree,which proves the Lemma.Let P be the set of all n by n row-stochastic matrices.Given any row-stochastic matrix P =[p ij ]2P ,define (P )=10mini;j k min f p ik ;p jk g [25].Lemma 4: (1)is continuous on P .40(k )=102T +4T2I n 0T2(diag L (k )0A 0(k))2T 04T2In2T +4T2I n 02T +12T 2(diag L (k )0A 0(k))102T 04T2I nql =14(z l )q2T 04T2I n2T +12T 2diag q l =1L (z l )0q l =1L (z l )0Inql =1A (z l )0= ~M 11~M12~M 21~M22:(7)Proof:2:P can be viewed as a subset of metricspace n .All the functions involved in the definition of (1)are continuous,and since the operations involved are sums and mins,it readily follows that (1)is continuouson n .The restriction of a continuous function is con-tinuous,so (1)is also continuous on P .Two nonnegative matrices M and N are said to be of the same type,denoted by M N ,if they have zero elements and positive elements in the same places.To derive the main result,we need the fol-lowing classical results regarding the infinite product of row-stochastic matrices.Lemma 5:([25])Let M =f M 1;M 2;...;M q g be a finite set of n 2n ergodic matrices with the property that for each se-quence M i ;M i ;...;M i of positive length,the matrix productM i M i111M i is ergodic.Then,for each infinite sequence M i ;M i ;...there exists a column vector c2n such thatlim j !1M i M i111M i =1c T :(8)In addition,when M is an infinite set, (W )<1,where W =S k S k 111Sk,S k 2M ,j =1;2;...;N (n )+1,and N (n )(which may depend on n )is the number of different types of all n 2n ergodic matrices.Furthermore,if there exists a constant 0 d <1satisfying (W ) d ,then (8)still holds.Let d=(n 01) .Assume,in the sequel,that ;T satisfy (4= T )0 T >2and T 01 (2= )T d.Then,by Lemma 1,all possible 4(k )must be nonnegative with positive diagonal elements.In addition,since the set of all 2n ( max +1)22n ( max +1)matrices can be viewed as the metricspace [2n (+1)],for each fixed pair ;T ,all possible 4(k )compose a compact set,denoted by 7( ;T ).This is because all the nonzero and hence positive entries of 4(k )are both uniformly lower and upper bounded,which can be seen by observing the form of 4(k )in (5).Let 3(A )=f B =[b ij ]22n 22n :b ij =a ij or b ij =0;i;j =1;2;...;2n g ,and denote by 5( ;T )the set of matricesM (40;41;...;4)=40411114014I 2n 0111000I 2n 11100 0111I 2nsuch that 40;41;...;423(4(k ))and 40+41+...+4=4(k ),where 4(k )27( ;T ).The set 5( ;T )is compact,since givenany 4(k )27( ;T ),all possible choices of 40;41;...;4are finite.Let (k )=[ 1(k ); 2(k );111; 2n (+1)(k )]T =[y T (k );y T (k 01);111;y T (k 0 max )]T22n (+1).Then,there exists a matrix M (40(k );41(k );...;4(k ))25( ;T )such that system (3)is rewritten as(k +1)=M (40(k );41(k );...;4(k )) (k ):(9)Clearly,the set 5( ;T )includes all possible system matrices of system (9).2Weare indebted to Associate Editor,Prof.Jorge Cortes,for his help with a simpler proof of this lemma.Given any positive integer K,define ~5(;T )=i =1M (4i 0;4i 1;...;4i):M (1)25( ;T )and there exists a integer ;1 K suchthat the union of digraphsj =04ij ;i =1;...; ;has a directed spanningtree :~5(;T )is also a compact set,which can be derived by noticing the following facts:1)5( ;T )is a compact set;2)all possible choices of are finite since is bounded by K;3)all possible choices of the directed spanning trees are finite;and 4)given the directed spanning tree and ,the followingset:i =1M (4i 0;4i 1;...;4i):M (1)25( ;T )and the union of the digraphsj =04ij;i =1;...; ;hasthe speci ed directed spanningtreeis compact (this can be proved by following the similar proof of [27,Lemma 10]).Note that the set ~5(;T )includes all possible products of ; K ,consecutive system matrices of system (9).The following lemma is presented to prove that all the possible prod-ucts of consecutive system matrices of system (9)satisfy the result as stated in Lemma 5,which in turn allow us to use the properties of in-finite products of row-stochastic matrices from an infinite set to derive our main result.Lemma 6:If 81;...;8k 2~5(;T ),where k =N (2n ( max +1))+1,then there exists a constant 0 d <1such that(k i =18i ) d .Proof:We first prove that for any 82~5(;T );8is an er-godic matrix.According to the definition of ~5(;T ),there exist pos-itive integer (1 K),M (4i 0;4i 1;...;4i )25( ;T ),i =1;...; ,such that 8= i =1M (4i 0;4i 1;...;4i)and the union of digraphs0(j =04ij ),i =1;...; ,has a directed span-ning tree.Since M (4i 0;4i 1;...;4i )25( ;T ),j =04ij must be nonnegative matrices with positive diagonal elements.Furthermore,there exists a positive number 1such that diag(j =04ij ) I 2n ,for any M (4i 0;4i 1;...;4i )25( ;T ).Specifically,by observing (5),we can choose as=min 1;10 2T + 24T20T 22(n 01) ;10 2T 0 24T2:Combining this with the condition that the union of digraphs0(j =04ij ),i =1;...; ,has a directed spanning tree,we can prove that matrix 8is ergodic by following the proof of [26,Lemma 7].Letd =max 82~5(;T )ki =18i :From Lemma 5,we know that(k i =18i )<1.This,together withthe fact that ~5( ;T )is a compact set and (1)is continuous (Lemma4),implies d must exist and 0 d <1,which therefore completing the proof.For notational simplicity,we shall denote M (40(k );41(k );...;4(k ))by M (k )if it is self-evident from the context.Based on the preceding work,now we can present our main result as follows.Theorem 1:Assume that and T satisfy (4= T )0 T >2andT 01 (2= )T d.Then,employing algorithm (2),consensus is reached for all the agents if there exists an infinite sequence of con-tiguous,nonempty,uniformly bounded time intervals [k j ;k j +1),j =1;2;...,starting at k 1=0,with the property that the union of the di-graphs 0(A (k j ));0(A (k j +1));...;0(A (k j +101))has a directed spanning tree.Proof:We first prove that consensus can be reached for system (9)using algorithm (2).Let 8(k;k )=I 2n (+1),k 0,and 8(k;l )=M (k 01)111M (l +1)M (l ),k >l 0.Assume,without loss of generality,that the lengths of all the time intervals [k j ;k j +1),j =1;2;...,are bounded by K.It follows from Lemma 3and the condition that the union of the digraphs 0(A (k j ));0(A (k j +1));...;0(A (k j +101))has a directed spanning tree that the union of the digraphs 0(4(k j ));0(4(k j +1));...;0(4(k j +101))also has a directed spanning tree for each j2+,which,together with the proof ofLemma 6,implies that 8(k j +1;k j )=k 01k =k M (k )2~5(;T ).Since 8(k j ;0)=8(k j ;k j 01)8(k j 01;k j 02)1118(k 2;k 1),it then follows from Lemma 5and Lemma 6thatlim j !18(k j ;0)=12n (+1)wT(10)where w22n (+1)and w 0.For each m >0,let k l be the largest nonnegative integer such that k l m .Note that matrix 8(m;k l )is row stochastic,thus we have8(m;0)012n w T =8(m;k l)8(k l ;0)012n wT :The matrix 8(m;k l )is bounded because it is the product of fi-nite matrices which come from a bounded set ~5(;T ).By using (10),we immediately have lim m !18(m;0)=12n (+1)w T .Combining this with the fact that (m )=8(m;0) (0)yields lim m !1 (m )=(w T (0))12n (+1)which,in turn,implies lim m !1x (m )=(w T (0))1n and lim k !1v (m )=0,and there-fore completing the proof.Remark 3:Matrix A (k )is a somewhat complex object to study compared with the adjacency matrix A (k )(see Remark 1).It is worth noting that more general results in which the sufficient conditions for guaranteeing the final consensus are presented in terms of G (k )instead of the interaction matrix in the presence of delays can be provided if some additional conditions are imposed.For example,if in addition to the conditions on and T as that required in Theorem 1,it is further required that a certain communication topology which takes effect at some time will last for at least max +1time steps,then we can get that consensus can be reached if there exists an infinite sequence of contiguous,nonempty,uniformly bounded time intervals [k j ;k j +1),j =1;2;...,starting at k 1=0,with the property that the union of the digraphs G (k j );G (k j +1);...;G (k j +101)has a directed spanning tree.This can be observed by reconstructing a new sequence of con-tiguous,nonempty and uniformly bounded time intervals which satis-fies the condition in Theorem 1by using similar technique as that in in [26,Theor.3].IV .I LLUSTRATIVE E XAMPLEConsider a group of n =6agents interacting between the possible digraphs f Ga;Gb;Gc g (see Fig.2),all of which have 0–0.2weights.Fig.2.Digraphs which model all the possible communicationtopologies.Fig.3.Position and velocity trajectories for agents.Take and T as =2and T =0:6respectively.Assume that the communication delays ij (k )satisfies 21(k )= 32(k )= 43(k )=1T s , 52(k )= 54(k )=2T s ,while 65(k )= 61(k )=3T s ,for any k2+.Moreover,we assume the switching signal is periodically switched,every 3T s in a circular way from Ga to Gb ,from Gb to Gc ,and then from Gc to Ga .Obviously,the union of the digraphs 0(A (k ))across each time in-terval of 9T s is precisely the digraph G d in Fig.2,which therefore has a directed spanning tree.Fig.3shows that consensus is reached for algorithm (2),which is consistent with the result in Theorem 1.V .C ONCLUSIONS AND F UTURE W ORKIn this technical note,we have investigated a discrete-time second-order consensus algorithm for networks of agents with nonuniform and time-varying communication delays under dynamically changing com-munication topologies in a sampled-data setting.By employing graphic method,state argumentation technique as well as the product proper-ties of row-stochastic matrices from an infinite set,we have presented a sufficient condition in terms of the associated digraph of the interac-tion matrix in the presence of delays for the agents to reach consensus.Finally,we have shown the usefulness and advantages of the proposed result through simulation results.It is worth noting that the case with input delays is an interesting topic which deserves further investigation in our future work.。

  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。

One-way Hash Function Construction Based on Conservative Chaotic Systems ZHANG Qing-huaˈ ZHANG Hanˈ LI Zhao-hui College of Information Technical Science Nankai University Tianjin 300071, China qhzhang@mail.nankai.edu.cn

Abstract—An algorithm for one-way hash function construction based on conservative chaotic system is proposed. The plaintext is divided into a group of message blocks by a fixed length and each message block is iterated some times through standard map. Both the iterations results of every round and the plaintext block determine the two initial values and the steps of iterations in next round. Some items of the result in the final round are chosen to be transformed into Hash value of 128 bits. Theoretical analysis and computer simulation show that this algorithm has good effect in irreversibility, weak collision and sensitivity to initial values. The method is safer in security than the Hash function based on low- dimensional dissipative chaotic maps and it is easy to realize.

Keywords:conservative chaotic systems;standard map;Hash function

I. INTRODUCTION After the conventional Hash function such as MD5, SHA was successfully attacked, research on the design of safe and efficient Hash function remains a hotspot. Chaos system is ergodic, mixed and sensitive; these characteristics make chaos theory have an important application value in modern cryptography [1]. At present,

some algorithms for one-way Hash function based on chaotic map have already been brought forward [2 - 4]. Most Hash algorithms using chaos in existing literatures are based on dissipative chaotic systems. But in some conditions if the attacker gets a continuous of plaintext-ciphertext pairs and the length of ciphertext meets certain conditions, phase space of the chaotic system can be reconstructed through a set of chaotic sequence’s consecutive points. Thus, chaos equation form may be constructed to get information of plaintext, which will result in the failure of encryption [5-7]. While, The Standard map as

a kind of conservative system in the emergence of chaotic behavior, has the good characteristics of the chaotic systems, and doesn’t have the so-called chaotic attractor. For the conservative chaotic systems, the attacker can not predict by reconstructing through ciphertext without attractor structure. So, the conservative chaotic systems with high security are ideal model in cryptography application . Some parallel algorithms for chaos-based Hash function construction are proposed in [2][3], which means each group of the plaintext operates independently. The parallel

algorithms are characterized by quick speed, but they have their fatal defects due to lack of enough diffusion and confusion of the plaintext. In [8], the collision problem of one kind of methods for constructing chaos-based hash function is described. Some key problems are pointed out which should be taken care of, and a number of good principles of algorithm for constructing one-way hash function based on chaotic map was proposed. In this paper, an algorithm for one-way Hash function construction based on Merkle-Damgard framework [9][10] is

introduced. In this algorithm, the entire message blocks perform some rounds of iteration through Standard map. One output of the iterations of each round determines one of the initial values of the next round, and the other output determines the steps of the next round. And the other initial value of the next round was given by the corresponding message block. The method of this design enhances the diffusion of Hash function, and overcomes the inherent defects of dissipative chaotic systems. So, the Hash algorithm has a higher security. Theoretical analysis and computer simulation show that this algorithm has good effect in anti-conflict and avalanche effect. The algorithm is easy to express and satisfies all the performance requirement of Hash function in an efficient and flexible manner. 󰀃

II. THE GENERALIZED STANDARD MAP

Standard map is one kind of typical conservative chaotic system defined as follows.

1112(sin)mod2()modiiiiii

xkH

yyH

H

xxyH

SS󰀎

󰀎󰀎

­ 󰀎°

®

° 󰀎

¯

(1)

Where [0,1),[0,1),0xyk󰂏󰂏!.

Hereinto, k is the controlled variable. When H=1, the certain critical value of k called kcrit is 0.971635406Ă [11].

When k is larger than the certain critical value, chaos motion in system is expanded from the part to the whole space and system demonstrates whole chaos. In order to make standard map in the whole chaos, H value is the maximum value of the ASCII, H=255, and 2kS in this algorithm.

相关文档
最新文档