A model for worldwide tracking of distributed objects

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Matlab GPU计算解决方案

M = ceil((numel(x)-W)/stride);%iterations needed o = cell(M, 1); % preallocate output for i = 1:M % What are the start points thisSP = (i-1)*stride:step: … (min(numel(x)-W, i*stride)-1); % Move the data efficiently into a matrix X = copyAndWindowInput(x, window, thisSP); % Take lots of fft's down the colmuns
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谢谢！
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Matlab 集群推荐配置
集群 AMAX Xn-1113G， Xn-4002G Tesla卡 • Tesla C2070 (6 GB) • Tesla C2075 (6GB) 新系统: • CPU: 2 x 4core Xeon E5645 • Memory: 48GB • Disk: 500 GB • GPU: 1~2 Tesla C2070/C2075 • 40Gb Infiniband
z = gather(x); % Bring back into MATLAB
+100 Functions support GPU Arrays
fft, fft2, ifft, ifft2
Matrix multiplication (A*B) Matrix left division (A\b)
LU factorization ‘ .’ abs, acos, …, minus, …, plus, …, sin, …

Panasonic GP-US932 3CCD HD摄像头系统说明书

Broadening the possibilities of video expression 1920 x 1080 True HD 3CCD cameraPanasonic ,s 3CCD camera with true 16 x 9 multi format high definition delivers sharp, pure color images. The camera is an ideal solution for microscopy, industrial endoscopy, special effects, and many other applications.Conventional imageGP-US932 imageT r u e m u l t i -f o r m a t H D I n a d d i t i o n t o t h e 1080i (1920 x 1080) t r u e H D m o d e , 720p (1280 x 720), 480p a n d 480i (720x 480) m o d e s a r e se l e c t a b l ef o r s h ar p , h i g h r e s o l u t i o n f l i c k e r -f r e e i m a g e s .*The images are samples.E x p a n d e d d y n a m i c r a n g e D e t a i l i n t h e b r i g h t a r e a s a n d c o n t r as ti n t h e d a r k a r e a s a r e r e p r o d u c e da s a w e l l -b a l a nc ed i m a ge .(T h e t w o i m a ge s t o t he r i g h ta r e a c tua l p i c t u r e s u s i n gt he e x p a n d e d d y n a mi c r a n g e fu n c t i o n.)T r u e -t o -l i f e c o l o r s T w e l v e i n d e p e nd e n t l y a d j u s t a b l e a x i s I n p a r t i c u l a r , t h ee x c el l e n t r e d -c o l o rr e p r o d u c i b i l i t yi s s u i t e d f o r b i o l o g i c a l a n d m ed i ca l a p p l i c a t i o n s .*Recommended lenses are optionally available.The new 1/3-type progressive CCD features exceptionally high sensitivity with a large light-receiving area for each pixel. Balanced high resolution and S/N ratio is achieved from the combination of high-performance image processing technology implemented by a new digital signal processor (DSP).New high-sensitivity progressive CCDProgressive capture is followed by 14-bit A/D conversion and newly developed DSP for 19-bit internal processing. The result is extraordinary high-precision 1920 x 1080 true HD image output.Newly developed DSP with 14-bit A/D conversionand 19-bit processing functionsHigh-sensitivity 3CCDFujinon* HD lensFujinon* SD lensSpecifications of Recommend LensesRecommend LensesHAF4.8DA-1XA4x7.5DA-1TF2.8DA-8TF4DA-8TF8DA-8TF15DA-8Model No.Manufacturer Focal Length (mm)Zoom RatioMaximum Aperture RatioAngle of View (˚)HorizontalVerticalMinimum Object Distance (m / ft)Filter Thread Mount FocusIrisLength (from focal plane)(mm / inch)Full Aperture (mm / inch)Weight (g / lbs)HAF4.8DA-1Fujinon*4.8 2.2 57.07˚34.05˚0.1 / 0.33M55C Manual Manual 53.126 / 2.092(in air)ø42 / ø1.65495 / 0.21XA4x7.5DA-1Fujinon*7.5 – 304 2.8 38.38˚ – 9.94˚22.18˚ – 5.61˚0.45 / 1.48M52C Manual Manual 178.926 / 7.044(in air)ø54 / ø2.126500 / 1.1TF2.8DA-8 Fujinon*2.8 2.2 85.98˚55.40˚0.1 / 0.33 N/A C Manual Manual 64.025 / 2.521(in air)ø34 / ø1.33975 / 0.17TF4DA-8 Fujinon*4 2.2 66.25˚40.36˚0.1 / 0.33 M27 x 0.5C Manual Manual 63.025 / 2.481(in air)ø29 / ø1.14270 / 0.15TF8DA-8 Fujinon*8 2.2 36.14˚20.82˚0.1 / 0.33M25.5 x 0.5C Manual Manual 56.526 / 2.225(in air)ø29 / ø1.14260 / 0.13TF15DA-8 Fujinon*15 2.2 19.74˚11.19˚0.1 / 0.33M25.5 x 0.5C Manual Manual 56.526 / 2.225(in air)ø29 / ø1.14260 / 0.13HD LensesSD Lenses* Fujinon Lenses: Please contact to your distributorPanasonic technology enables high definition image quality covering a wide range of applicationsThe lineup includes HDMI output and HD-SDI/SD-SDI output models for different applications and purposes.HDMI output model lineupHDMI, HDMI logo, and High-Definition Multimedia Interface are trademarks orregistered trademarks of HDMI Licensing LLC.Beautiful, true-to-life colors are reproduced. Each of the 12 axis can be independently adjusted without affecting the adjacent color vector. The excellent red-color reproduction is ideal for biological and medical applications.Excellent color performanceA higher-level vertical resolution is obtained from P/I conversion, line conversion, and down conversion of native images with high vertical resolution from full-frame 59.94 fps progressive scanning. High image quality unparalleled by electronically interpolated interlace scanning is obtained.High-resolution native progressive scanConventional imageGP-US932 image*The images are samples.Simply select the appropriate functions from the list of camera functions displayed on the monitor screen to complete the setting.Images can be adjusted easily and efficiently while observing the images.Easy set-up menuThe functions provide high-precision true HD outputs.14-bit A/D conversion and 19-bit processing DSPThe new proprietary expanded dynamic range function expands the contrast of the dark areas while maintaining detail in the bright areas. Objects with high contrast can be represented as natural images.Proprietary expanded dynamic range functionConventional imageExpanded dynamic range image*Actual camera images<Parameters>Each of the three independent scene files has twelve parameters that can be customized to suit any applications.Three scene filesDetail Red detail Gamma KneeBlack stretch Dynamic range White clipFlare compensationDigital noise reduction Color matrix Chroma gain Total pedestalElectronic zoom up to 2.5xFreeze function White balanceElectronic shutter Gain control Electronic zoom up to 2.5x allows checking finer detail.Motionless video images can be displayed while capturing video.ATW (auto-tracking white balance) mode,AWC (automatic white balance) mode, or manual white balancemode can be selected according to the illumination of the scene.ELC mode (automatic shutter speed control accordingto the object`s amount of light), STEP mode (selection from 1/100, 1/250, 1/500, 1/1000, 1/2000, 1/4000, or 1/10000 to obtain the optimal setting), or select MANU mode.AUTO (automatic gain control) will provide automatic adjustment of sensitivity. Manual adjustment of sensitivity is also available.Other features。

外文翻译---视频监控系统

A System for Video Surveillance andMonitoringThe thrust of CMU research under the DARPA Video Surveillance and Monitoring (VSAM) project is cooperative multi-sensor surveillance to support battlefield awareness. Under our VSAM Integrated Feasibility Demonstration (IFD) contract, we have developed automated video understanding technology that enables a single human operator to monitor activities over a complex area using a distributed network of active video sensors. The goal is to automatically collect and disseminate real-time information from the battlefield to improve the situational awareness of commanders and staff. Other military and federal law enforcement applications include providing perimeter security for troops, monitoring peace treaties or refugee movements from unmanned air vehicles, providing security for embassies or airports, and staking out suspected drug or terrorist hide-outs by collecting time-stamped pictures of everyone entering and exiting the building.Automated video surveillance is an important research area in the commercial sector as well. Technology has reached a stage where mounting cameras to capture video imagery is cheap, but finding available human resources to sit and watch that imagery is expensive. Surveillance cameras are already prevalent in commercial establishments, with camera output being recorded to tapes that are either rewritten periodically or stored in video archives. After a crime occurs – a store is robbed or a car is stolen – investigators can go back after the fact to see what happened, but of course by then it is too late. What is needed is continuous 24-hour monitoring and analysis of video surveillance data to alert security officers to a burglary in progress, or to a suspicious individual loitering in the parking lot, while options are still open for avoiding the crime.Keeping track of people, vehicles, and their interactions in an urban or battlefield environment is a difficult task. The role of VSAM video understanding technology in achieving this goa l is to automatically “parse” people and vehicles from raw video, determine their geolocations, and insert them into dynamic scene visualization. We have developed robust routines for detecting and tracking moving objects. Detected objects are classified into semantic categories such as human, human group, car, and truck using shape and color analysis, and these labels are used to improve tracking using temporal consistency constraints. Further classification of human activity, suchas walking and running, has also been achieved. Geolocations of labeled entities are determined from their image coordinates using either wide-baseline stereo from two or more overlapping camera views, or intersection of viewing rays with a terrain model from monocular views. These computed locations feed into a higher level tracking module that tasks multiple sensors with variable pan, tilt and zoom to cooperatively and continuously track an object through the scene. All resulting object hypotheses from all sensors are transmitted as symbolic data packets back to a central operator control unit, where they are displayed on a graphical user interface to give a broad overview of scene activities. These technologies have been demonstrated through a series of yearly demos, using a testbed system developed on the urban campus of CMU.Detection of moving objects in video streams is known to be a significant, and difficult, research problem. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving blobs provides a focus of attention for recognition, classification, and activity analysis, making these later processes more efficient since only “moving” pixels need be considered.There are three conventional approaches to moving object detection: temporal differencing ; background subtraction; and optical flow. Temporal differencing is very adaptive to dynamic environments, but generally does a poor job of extracting all relevant feature pixels. Background subtraction provides the most complete feature data, but is extremely sensitive to dynamic scene changes due to lighting and extraneous events. Optical flow can be used to detect independently moving objects in the presence of camera motion; however, most optical flow computation methods are computationally complex, and cannot be applied to full-frame video streams in real-time without specialized hardware.Under the VSAM program, CMU has developed and implemented three methods for moving object detection on the VSAM testbed. The first is a combination of adaptive background subtraction and three-frame differencing . This hybrid algorithm is very fast, and surprisingly effective – indeed, it is the primary algorithm used by the majority of the SPUs in the VSAM system. In addition, two new prototype algorithms have been developed to address shortcomings of this standard approach. First, a mechanism for maintaining temporal object layers is developed to allow greater disambiguation of moving objects that stop for a while, are occluded by other objects,and that then resume motion. One limitation that affects both this method and the standard algorithm is that they only work for static cameras, or in a ”stepand stare” mode for pan-tilt cameras. To overcome this limitation, a second extension has beendeveloped to allow background subtraction from a continuously panning and tilting camera . Through clever accumulation of image evidence, this algorithm can be implemented in real-time on a conventional PC platform. A fourth approach to moving object detection from a moving airborne platform has also been developed, under a subcontract to the Sarnoff Corporation. This approach is based on image stabilization using special video processing hardware.The current VSAM IFD testbed system and suite of video understanding technologies are the end result of a three-year, evolutionary process. Impetus for this evolution was provided by a series of yearly demonstrations. The following tables provide a succinct synopsis of the progress made during the last three years in the areas of video understanding technology, VSAM testbed architecture, sensor control algorithms, and degree of user interaction. Although the program is over now, the VSAM IFD testbed continues to provide a valuable resource for the development and testing of new video understanding capabilities. Future work will be directed towards achieving the following goals:l better understanding of human motion, including segmentation and tracking of articulated body parts;l improved data logging and retrieval mechanisms to support 24/7 system operations;l bootstrapping functional site models through passive observation of scene activities;l better detection and classification of multi-agent events and activities;l better camera control to enable smooth object tracking at high zoom; andl acquisition and selection of “best views” with the eventual goal of recognizing individuals in the scene.视频监控系统在美国国防部高级研究计划局，视频监控系统项目下进行的一系列监控装置研究是一项合作性的多层传感监控，用以支持战场决策。

多智能体系统自适应跟踪控制

多智能体系统自适应跟踪控制赵蕊;朱美玲;徐勇【摘要】The leader-follower tracking problems of second-order multi-agent systems with intrinsic nonlinear dynamics are studied. It assumes that each following agent can access the relative position and velocity information with its neigh-bors, the position and velocity information of the leader is only accessed by a subset of the following agents, and the leader's non-zero reference input cannot be available by any following agents. To track the active leader, a distributed adaptive consensus protocol is proposed for each following agent in the case that the interaction relationship among agents is undi-rected connected graph. The protocol effectively avoids the uncertainty of global information. The consensus tracking problem can be transformed into the stability problem of error system. Based on the theory of Lyapunov stability and matrix theory, it gets the sufficient conditions which guarantee the system to reach a leader-follower tracking consensus. Finally, a simulation example is given to verify the effectiveness of the obtained.%基于带有非线性动态的二阶多智能体系统,研究了在有动态领导者条件下的跟踪一致性问题.假设跟随者只能获取邻居智能体的相对状态信息,只有一部分跟随者可以获得领导者的位置和速度信息,领导者的控制输入非零且不被任何一个跟随者可知.在通信拓扑为无向连通图的条件下,为了避免全局信息的不确定性,设计了分布式自适应控制协议.将系统的一致性问题转化为误差系统的一致性问题,通过Lyapunov稳定性理论和矩阵理论分析得到了该协议使系统达到一致的充分条件.最后用仿真例子证明了设计方法的有效性.【期刊名称】《计算机工程与应用》【年(卷),期】2017(053)018【总页数】5页(P39-43)【关键词】多智能体系统;一致性;分布式控制;自适应控制;领导者【作者】赵蕊;朱美玲;徐勇【作者单位】河北工业大学理学院,天津 300401;河北工业大学理学院,天津300401;河北工业大学理学院,天津 300401【正文语种】中文【中图分类】TP13一致性，是智能体组成的网络系统的一类集体行为，近年来由于它广泛应用在生物系统、传感器网络、无人机编队控制等领域，引起了许多学者的关注，得到了大量研究成果[1-5]。

卫星定位理论与方法-第15次课-卫星定位误差源

1.10 0.91 0.91 1.14
0.48 0.42 0.4 0.5
0.59 0.5 0.48 0.59
1 0.83 0.83 1.04
1.2 1 0.91 1.18
1.2 1.1 1 1.27
0.96 0.85 0.79 1
Ex) 100m(2DRMS) accuracy ⇒ 42m(CEP)
Now has roughly the same accuracy as PPS Used by military receivers before Y-code lock is established
Scatter plot of horizontal accuracy 2 May 2000
Processing Algorithms, Operational Mode and Other Enhancements
1、Whether the user is moving or stationary. Clearly repeat observations at a stationary station would permit an improvement in precision due to the effect of averaging over time. A moving GPS receiver does not offer this possibility. 2、Whether the results are required in real-time, or if post-processing of the data is possible. Real-time positioning requires a “robust” but less precise technique to be used. The luxury of post-processing the data permits more sophisticated modelling and processing of GPS data to minimise the magnitude of residual biases and errors. 3、The level of measurement noise has a considerable influence on the precision attainable with GPS. Low measurement noise would be expected to result in comparatively high accuracy. Hence carrier phase measurements are the basis for high accuracy techniques, while pseudo-range measurements are used for low accuracy applications.

2021年北京市丰台区高三一模英语试题[附答案]

丰台区2021年高三年级第二学期综合练习（一）英语2021.03本试卷满分共100分考试时间90分钟注意事项：1.答题前，考生务必先将答题卡上的学校、年级、班级、姓名、准考证号用黑色字迹签字笔填写清楚，并认真核对条形码上的准考证号、姓名，在答题卡的“条形码粘贴区”贴好条形码。

2.本次考试所有答题均在答题卡上完成。

选择题必须使用2B铅笔以正确填涂方式将各小题对应选项涂黑，如需改动，用橡皮擦除干净后再选涂其它选项。

非选择题必须使用标准黑色字迹签字笔书写，要求字体工整、字迹清楚3.请严格按照答题卡上题号在相应答题区内作答，超出答题区域书写的答案无效，在试卷、草稿纸上答题无效。

4.请保持答题卡卡面清洁，不要装订、不要折叠、不要破损。

第一部分：知识运用(共两节，30分)第一节完形填空(共10小题；每小题1.5分，共15分)阅读下面短文，掌握其大意，从每题所给的A、B、C、D四个选项中，选出最佳选项，并在答题卡上将该项涂黑。

This was the fifth time I’d been to the National Annual Competition. Reporters had been saying that I looked unbeatable. Everyone expected me to __1__. But I knew something was __2__ because I couldn’t get this one picture out of my head; a picture of me, falling. “Go away,” I’d say, But the image wouldn’t __3__.It was time to skate. The music started, slowly, and I told myself, “Have fun, Michael! It’s just a(n) __4__.”Once the music picked up, I started skating faster, I’d practiced the routine so manytimes, and I didn’t have to think about __5__ came next. But when I came down from thejump, my foot slipped from under me. I put a hand on the ice to __6__ myself, but it didn’tdo any good.Things kept getting __7__. On a triple flip(三周跳) I spun through the air, and justas I landed, my whole body went down again. There I was, flat on the ice, with the whole world __8__.I didn’t think I’d be able to pull myself together. But as I got up, I heard an amazing __9__. People were clapping in time to the music. They were trying to give me courage.I wasn’t surprised by my scores. However, the audience’s clapping woke me up! I was so busy trying not to __10__ that I forgot to feel what was in my heart—the love for skating.1. A. win B. enjoy C. share D. relax2. A. challenging B. missing C. wrong D. dangerous3. A. return B. leave C. appear D. stay4. A. sport B. activity C. picture D. accident5. A. when B. why C. who D. what6. A. prepare B. catch C. comfort D. measure7. A. clearer B. easier C. heavier D. worse8. A. watching B. expecting C. ignoring D. changing9. A. voice B. story C. sound D. idea10. A. collapse B. resist C. fall D. escape第二节语法填空(共10小题；每小题1.5分，共15分)阅读下列短文，根据短文内容填空，在未给提示词的空白处仅填写1个适当的单词，在给出提示词的空白处用括号内所给词的正确形式填空。

外文文献常用句式

Useful expressions for paper-writing Notice:All of the following sentences are derived from papers and the internet.目录一、研究方法表述类： (2)二、摘要总结类： (9)三、公式表述类： (10)四、其他表达： (11)一、研究方法表述类：A great number of research results have been reported , for example[1]—[5]★A neural network based dynamics compensation method has been proposed for trajectory control of a robot system[11].A combined approach of neural network and sliding mode technology for both feedback linearization and control error compesation has been presented[12].1、研究目的的表示方法The purpose of this investigation is to ...The main focus of this study is ...The objective of the present work is to ...The aim of the present study is to ...The present study is aimed at ...The present study is designed to ...The present study is an attempt to ...We have embarked on research attempting to ...This study is undertaken with the intent of ...The present investigation is conducted to ...This study was undertaken to ...To gain a better understanding of ...The investigation concentrated on efforts to ...The present study is performed in an effort to ...2、研究动机的表示方法Since the early literature contained a few reports of ...Because of the potential importance of ..., we have investigaed ... Because of the economic potential of ..., we decided to study ... Current work in this laboratory ..., stimulated interest in determining some of ...Prompted by ..., we initiated an examination of ...In view of ..., this study was conducted to examine ...The finding of ..., led us to reinvestigate ...A recent report ..., encouraged us to ...Little attention/effort has been given to ...... are poorly understood ...... have been poorly characterized ...The question have been raised as to whether or not ...... the question arose...3、研究内容的表示方法This article examines ...This research assessed ...This study documents ...The present work has shown ...This report describes ...The paper presents ...Work presented here introduces ...Our forthcoming studies will establish ...In this report, we report ...Here we describe ...In this report we examine ...In this reprot we describe ...We report here ...... this is the first report of ...This is the first report ...This report contains the first ...Our results are the first report on ...We report here for the first time ...This ..., is the first to ..., reported for ...,This report documents the first ...... this is the first time that ,,,The novelty of this research lies in ...Of particular interest and novelty is ...The evidence presented in this communication demonstrtes ... The data presented in this report represent ...The major idea addressed in this studies ...The emphasis of this study is ...This study is an attempt to ...4、研究报告的数量表示方法..., much efforts has gone into the study of ...Many research groups have recently been involved with ... ... have received fairly intensive study... have done a considerable amount of work on ...Many studies have addressed ...There have been many investigations into ...There have been numerous studies ...A substantial amount of ... information is available on ... There are only a few reprots of ...Only a few studies have dealt with ...Only a few studies have bean performed on...... there are very few studies ...Few studies have involved ...Few studies have centered on ...Investigations ... are extremely few ...A surprisingly limited amount of information exists on ... Reports on ... are extremely scarce.... has been the subject of only a limited number of studies.Information ... is limited.We found no reprots of ...We know of no report concerning ......, no studies ... have been reported ...There are no reports on ...no ... have been documented ...... no information is available concerning ...No data have been published ...To date, no reports have appeared concerning ... no ... is reported ...None have been reported for ...... information ... is ... lacking ...Virtually nothing is known about ...Little is known of ...very little actually is known about ...There is little known about ...5、注意、兴趣的表示方法... has not received as much attention ...Less attention has been paid ...Relatively little attention has been directed ... ... have received very little attention ...Little attention has been given to ...Attention was focused on ...... has recently received increased attention.There is currently great interest in ...... has been the focus of intense research interest. ... has been become a subject of considerable interest.6、研究正在进行的表示方法Studies are under way to ...... are currently under study.Further work is in progress ...Further experiments are in progress to ...Further investigations are in progress to ...Attempts to ... are currently in progress.Efforts continue ...We are presently attempting to determine ...Further studies ... are being conducted ...Our laboratory presently is involved with ...... is being investigated.7、将来工作的建议的表示方法Further work is needed ...Further work is required ...... is worthy of further study.Much more research is needed ...... has to be elucidated.... have to be determined.... requires further testing ...... makes ... worthy of further study.Further studies are contemplated to ...Further research is planned to ...continuing studies will yield further insight into ... Further research ... may yield...Further research should explore ...Further studies should clarify ...... remains to be determined.... remain to be investigated, and ... remains to be tested. ... remains to be established.What remains to be resolved ...... remains to be shown.... remains unexplained...., it remains unknown.... remain unanswered ...8、结论的表示方法In conclusion, ...This conclusion is supported ... by ... finding that ... ... leads to the conclusion that ...二、摘要总结类：★Simulations and experiments are carried out on AdeptOne robot.★From the simulation and experimental results,the effectiveness and usefulness of the proposed control sysytem are confirmed.★This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators.In this paper,we present a new and simple control system consisting of a traditional controller for trajectory tracking control of industrial robot manipulators.★This paper describes a vision-based navigation method in an indoor environment for an autonomous mobile robot which can avoid obstacles.★★In this method, the self-localiation of the robot is done with a model-based vision system,and a non-stop navigation is realized by a retroactive position correction system.We present a robust and automatic method for evaluating the accurancy of weed discrimination algorithms. The proposed method is based onsimualated agronomic images and a crop weed discrimination algorithm can be dividided into the two following steps. Firstly,……. Afterwards,….In this research ,we aim at high precision trajectory tracking control of the industrial robot manipulators using simple and applicable contrl method.三、公式表述类：The dynamic model can be easily derived and expressed systematically with the formulation as follows:Formulation (1)The detail mathematical description of the network is given byFormulaion (2)四、其他表达：An industrial manipulator AdepOne is adopted as an experimental test bed.★Trajectory tracking control simulations and experiments are carried out. The results demonstrate effectiveness and usefulness of the proposed control system.★For this reason,we design the neural network controller such that it takes the important part on which the linear controller has shown its limitation and/or powerlessness.Other advantages of the neural networks often cited are parallel distributed structure,and learning ability.Theoretically speaking,System implementation,however,is difficult to perform because of the existence of the uncertainties of….。

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 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AModelforWorldwideTrackingofDistributedObjectsMaartenvanSteen,FranzJ.Hauck,AndrewS.TanenbaumVrijeUniversiteit,Amsterdam

AbstractWedescribeaserviceforlocatingdistributedobjectsidentiﬁedbylocation-independentobjectidentiﬁers.Anobjectinourmodelisphysicallydistributed,withmultipleactivecopiesondifferentmachines.Pro-cessesmustbindtoanobjectinordertoinvokeitsmethods.Partofthebindingprotocolisconcernedwithcontactingtheobject,whichoffersoneormorecontactpoints.Anobjectcanchangeitscontactpointsinthecourseoftime,thusexhibitingmigrationbehavior.Wepresentasolutiontoﬁndinganobject’scon-tactpointswhichisbasedonaworldwidedistributedsearchtreethatadaptsdynamicallytoindividualmigrationpatterns.

1IntroductionTheintroductionoftheWorldWideWebandtheeaseofaccesstotheInternetisradicallychang-ingourperceptionofworldwidedistributedsystems.Suchsystemsshouldallowustoeasilyshareandexchangeinformation.Thisalsomeansthatitshouldbeeasytotracksourcesofin-formation,evenifthesesourcesmovebetweendifferentlocations.(Wedonotaddresstheprob-lemofﬁndingrelevantsourcesofinformationasisdoneby,forexample,resourcediscoveryservices[11].)Akeyroleintrackingsourcesofinformationisplayedbynamingsystems.Animportantproblemwithcurrentnamingsystemsforwideareanetworksisthatnamesarelocation-dependent:anameistightlycoupledtothelocationoftheobjectitrefersto.Forexam-ple,aURLsuchashttp://www.ripn.net/nic/rfc/rfc1737.txtisthenameofaWebpagecontainingthetextofRFC1737.Thenamereﬂectsexactlywherethepageisstored.Ifthepageismovedorreplicated,thenamewillhavetochangeaswell.Whatisneededisanamingandidentiﬁca-tionfacilitythathidesallaspectsofanobject’slocation.Usersshouldnotbeconcernedwhereanobjectislocated,whetheritcanmove,whetheritisreplicated,andifitisreplicated,howconsistencybetweenreplicasismaintained.Thismechanismshouldbeavailabletoallapplica-tionsasastandardfacility.Aboveall,itshouldscaletotheentireworld,andbeabletohandletrillionsofobjects.Inthispaper,weoutlineasolutionforlocatingobjectsusinglocation-independentidenti-ﬁers.Ourapproachisbasedonamodelinwhichprocessesinteractandcommunicatethroughdistributedsharedobjects[5].Eachobjectoffersoneormoreinterfaces,eachconsistingofasetofmethods.Objectsarepassive;clientthreadsuseobjectsbyexecutingthecodefortheirmethods.Inorderforaprocesstoinvokeanobject’smethod,itmustﬁrstbindtothatobject.Thismeansthataninterfacebelongingtotheobject,aswellasanimplementationofthatin-terfacemustbeplacedintheprocess’addressspace.Tothisend,adistributedobjecthasoneormorecontactpoints.Acontactpointspeciﬁesthenetworkaddressandprotocolwithwhichinitialcommunicationwiththeobjectcantakeplace.Anobject’scontactpointsmaychangeinthecourseoftime.Forexample,anobjectcanbesaidtoexpandinto,orwithdrawfromaregionwhencontactpointsinthatregionareestablishedorremoved,respectively.Weproposeatwo-levelnaminghierarchyforﬁndingcontactpoints.Theﬁrstleveldealswithhierarchicallyorganized,user-deﬁnednamespaces.Thesenamespacesarehandledbyadistributednamingservice.However,wheretraditionalnameserviceimplementationsmain-tainname-to-addressbindings,namesinourapproacharemappedtoobjecthandles.Anobjecthandleisagloballyunique,andlocation-independentobjectidentiﬁer.(Theyhavealsobeencoinedpurenamesin[10].)Objecthandlesformthesecondlevelinthenaminghierarchy.Eachobjecthandleismappedtoanobject’scontactaddresses.Acontactaddressisadescriptionofacontactpoint,suchasanIPaddressortheaddressofthecurrentcellinthecaseofmobiletele-phones.Itisthetaskofalocationservicetomaintainthemappingbetweenobjecthandlesandcontactaddresses.Thedesignofapossiblelocationserveristhesubjectofthispaper.Oursolutioncomprisesasearchtreeinwhichanobject’scontactaddressesarestoredatrel-ativelystablelocations,neartotheplaceswheretheobjectcanbereached.Weshowhowthesestablelocationsareidentiﬁeddynamically,andthattheymaychangeasthemigrationbehav-ioroftheobjectchangesovertime.Storingcontactaddressesatstablelocationspermitsustoeffectivelycachelocationpointers.Thecombinationofdynamicallyidentifyingstablestoragelocationsforcontactaddresses,andcachingpointerstothoselocations,isnew.Theresultisalocationservicethatishighlyefﬁcientbyexploitinglocalityinlookupandupdateoperations.Locationservicesarenotnewandhaveshowntoberelativelyeasytoimplementinlocaldis-tributedsystems.However,theybecomemuchmorecomplicatedwhenscalabilityistakenintoaccount.WeﬁrstpresentthelogicalorganizationofourlocationserviceinSection2,andsomeimportantoptimizationsinSection3.ThescalabilityofourapproachisdiscussedinSection4.WeconcludewithacomparisontorelatedworkinSection5.