云计算-专业英语论文
A View of Cloud Computing
communicatio ns o f th e acm | apr i l 201 0 | vol. 5 3 | no. 4
hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. As a result, cloud computing is a popular topic for blogging and white papers and has been featured in the title of workshops, conferences, and even magazines. Nevertheless, confusion remains about exactly what it is and when it’s useful, causing Oracle’s CEO Larry Ellison to vent his frustration: “The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do…. I don’t understand what we would do differently in the light of cloud computing other than change the wording of some of our ads.” Our goal in this article is to reduce that confusion by clarifying terms, providing simple figures to quantify comparisons between of cloud and conventional computing, and identifying the top technical and non-technical obstacles and opportunities of cloud computing. (Armbrust et al4 is a more detailed version of this article.) Defining Cloud Computing Cloud computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the data centers that provide those services. The services themselves have long been referred to as Software as a Service (SaaS).a Some vendors use terms such as IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) to describe their products, but we eschew these because accepted definitions for them still vary widely. The line between “low-level” infrastructure and a higher-level “platform” is not crisp. We believe the two are more alike than different, and we consider them together. Similarly, the
关于云计算的英语作文
关于云计算的英语作文英文回答：Cloud computing has revolutionized the way businesses and individuals store, process, and access data and applications. As a result, there are multiple benefits of cloud computing, including improved flexibility, reduced costs, increased security, enhanced collaboration, and innovative services.Flexibility is one of the key advantages of cloud computing. It allows users to access their data and applications from anywhere with an internet connection. This makes it easier for businesses to operate remotely and for individuals to work from home.Reduced costs are another advantage of cloud computing. Businesses can avoid the upfront costs of purchasing and maintaining their own IT infrastructure. Instead, they can pay for cloud services on a pay-as-you-go basis.Increased security is another key benefit of cloud computing. Cloud providers have invested heavily insecurity measures to protect their customers' data. This makes cloud computing a more secure option than storingdata on-premises.Enhanced collaboration is another advantage of cloud computing. Cloud-based applications make it easier forteams to collaborate on projects. This is because cloud applications can be accessed from anywhere, and they allow users to share files and collaborate in real-time.Innovative services are another key benefit of cloud computing. Cloud providers are constantly developing new services, such as artificial intelligence, machine learning, and data analytics. These services can help businesses improve their operations and make better decisions.Overall, cloud computing offers a number of benefitsthat can help businesses and individuals improve their operations, reduce costs, and increase innovation.中文回答：云计算的优势。
云计算技术在大学英语教学中的应用研究
I nternet Education互联网+教育一、引言云计算是指用现代信息存储、处理设备和技术来收集、获取、存储和共享海量数据。
数据规模的变化导致数据存储和应用的变化，它改进了高校的运作方式及教师的教学方式。
以英语教学为研究案例，大数据云计算可以作为英语教学改革的基础，为其提供突破口。
数据的收集和处理越多，共享的能力就越大，能够有效缓解资源分配的不平等和教学缺乏多样性的问题。
在高校人才培养中，英语教学起着重要的作用。
而大数据与云计算的结合打破了大学英语教学课堂的界限，延伸了教学活动，使得教学活动不再受到时空的限制。
二、云计算在大学英语教学中的必要性云计算是通过互联网对计算资源的实时需求访问，这些资源包括应用程序、web服务器（物理服务器和虚拟服务器）、数据存储、评估工具等，它们存在于远程数据采集中心。
与传统的数字交互相比，云计算实现了以下目标：1.云计算具有更低的数字交换成本，不需要构建新的本地基础设施，并提供各种资源。
2.云计算可以提高敏捷性和价值实现时间，组织或机构可以同时开始使用信息交换，而不是等待几天或数周，信息接收者才对请求、购买和问题等做出回应。
3.云提供了弹性，用户可以根据流量的高峰和低谷上下调整容量，从而更轻松经济有效地扩大信息交换的范围。
用户还可以利用云供应商的全球网络（如IBM、百度云等），让应用程序更接近世界各地的用户。
术语“云计算”也指使云工作的技术方法，其中包括某些虚拟IT基础设施。
虚拟技术使云供应商和用户能够充分利用数据中心资源，因为许多公司和大学都在管理和教育过程中采用了云交付模式，以最大限度地提高利用率和节约成本。
然而，传统的IT基础设施却不能，如果用户在家里或工作中使用电脑等便携式智能设备，其每天都在使用某种形式的云计算，无论是百度云、IBM云这样的云应用程序，还是抖音这样的流媒体，又或是微信这样的社交媒体等。
根据最近的一项调查，目前中国有超过一半的组织都在使用云计算，其中大多数组织计划明年更多地使用云计算。
Google_云计算三大论文中文版
Google_云计算三大论文中文版Google公司是全球最大的搜索引擎和云计算服务提供商之一。
Google的云计算架构和算法在业界受到广泛关注，其通过一系列论文来介绍这些技术，并分享了它们的最佳实践。
本文将针对Google公司发表的三篇云计算论文（论文名称分别为《MapReduce：Simplified Data Processing on Large Clusters》、《The Google File System》、《Bigtable: A Distributed Storage System for Structured Data》），进行分类讲解，以帮助读者更好地了解云计算领域的相关技术。
一、MapReduce：Simplified Data Processing on Large ClustersMapReduce论文是Google公司云计算领域中的重要代表作之一，它的作者是Jeffrey Dean和Sanjay Ghemawat。
MAPREDUCE是一种大规模数据处理技术，其主要目的是在一个大型集群中分Distribute and Parallel Execution（分布式和并行执行）处理任务。
MapReduce将计算逻辑分解成两个部分- Map阶段和Reduce阶段。
在Map阶段，数据被按键提取；在Reduce阶段，数据被收集以计算结果。
这两个阶段可以在许多物理节点上并行执行，大大提高了计算效率。
此外，该论文引入了GFS分布式文件系统，为MapReduce提供了强大的文件系统支持。
二、The Google File SystemGFS是由Sanjay Ghemawat、Howard Gobioff和Shun-TakLeung共同编写的一篇论文。
它旨在解决分布式文件系统上的问题，以应对Google的大规模数据集和两台甚至三台以上的机器发生故障的情况。
GFS可以处理超过100TB以上的数据集，加速数据读取和写入，处理大规模数据存储集群。
大学英语计算机专业作文
大学英语计算机专业作文With the rapid development of information technology, computer science has become one of the most popular majors in universities. As a student majoring in computer science, I have gained a lot of knowledge and skills that will benefit me in my future career.First and foremost, studying computer science in university has equipped me with a solid foundation in programming languages. I have learned how to code in languages such as Java, C++, and Python, which areessential skills for any computer science professional. These programming languages have enabled me to develop software applications, websites, and other digital products that can solve real-world problems. In addition, I have also learned about data structures, algorithms, and software engineering principles, which are crucial for designing and building efficient and scalable software systems.Moreover, studying computer science has provided mewith opportunities to work on various projects and assignments that have challenged me to think critically and creatively. I have collaborated with my classmates on group projects, where we have designed and implemented software solutions for different problems. These projects have allowed me to apply the theoretical knowledge I havelearned in class to practical situations, and have helpedme develop my problem-solving skills and teamwork abilities.Furthermore, studying computer science has opened up a wide range of career opportunities for me. With a degree in computer science, I can pursue a career as a software developer, data analyst, cybersecurity specialist, or any other role in the tech industry. The demand for computer science professionals is high, and companies are constantly looking for talented individuals who can help them innovate and stay competitive in the digital age. By studying computer science, I have positioned myself for a successful and rewarding career in the technology sector.In conclusion, studying computer science in universityhas been a valuable and enriching experience for me. I have gained a strong foundation in programming languages, developed my problem-solving and teamwork skills, and opened up a world of career opportunities in the tech industry. I am confident that the knowledge and skills I have acquired through my computer science education will serve me well in my future career, and I am excited to see where this journey will take me.。
我对云计算的看法英语作文
我对云计算的看法英语作文英文回答：Cloud computing has revolutionized the way businesses operate in the digital age. It offers a wide range of benefits, including increased flexibility, scalability, and cost efficiency. By leveraging cloud-based services, businesses can access a virtually limitless pool of computing resources, tailored to their specific needs.However, cloud computing also presents certain challenges. Security is a primary concern, as organizations must ensure the protection of data stored and processed in the cloud. Data privacy is another consideration, as cloud providers may have access to sensitive information.Despite these challenges, cloud computing is poised to continue its rapid growth in the years to come. As businesses increasingly adopt cloud-based technologies, the demand for cloud services will only continue to soar.中文回答：云计算彻底改变了企业在数字时代中的运营方式。
云计算Cloud-Computing-外文翻译
毕业设计说明书英文文献及中文翻译学生姓名：学号：计算机与控制工程学院：专指导教师：2017 年 6 月英文文献Cloud Computing1。
Cloud Computing at a Higher LevelIn many ways，cloud computing is simply a metaphor for the Internet, the increasing movement of compute and data resources onto the Web. But there's a difference: cloud computing represents a new tipping point for the value of network computing. It delivers higher efficiency, massive scalability, and faster，easier software development. It's about new programming models，new IT infrastructure, and the enabling of new business models。
For those developers and enterprises who want to embrace cloud computing, Sun is developing critical technologies to deliver enterprise scale and systemic qualities to this new paradigm:（1) Interoperability —while most current clouds offer closed platforms and vendor lock—in, developers clamor for interoperability。
云计算外文翻译参考文献
云计算外文翻译参考文献(文档含中英文对照即英文原文和中文翻译)原文:Technical Issues of Forensic Investigations in Cloud Computing EnvironmentsDominik BirkRuhr-University BochumHorst Goertz Institute for IT SecurityBochum, GermanyRuhr-University BochumHorst Goertz Institute for IT SecurityBochum, GermanyAbstract—Cloud Computing is arguably one of the most discussedinformation technologies today. It presents many promising technological and economical opportunities. However, many customers remain reluctant to move their business IT infrastructure completely to the cloud. One of their main concerns is Cloud Security and the threat of the unknown. Cloud Service Providers(CSP) encourage this perception by not letting their customers see what is behind their virtual curtain. A seldomly discussed, but in this regard highly relevant open issue is the ability to perform digital investigations. This continues to fuel insecurity on the sides of both providers and customers. Cloud Forensics constitutes a new and disruptive challenge for investigators. Due to the decentralized nature of data processing in the cloud, traditional approaches to evidence collection and recovery are no longer practical. This paper focuses on the technical aspects of digital forensics in distributed cloud environments. We contribute by assessing whether it is possible for the customer of cloud computing services to perform a traditional digital investigation from a technical point of view. Furthermore we discuss possible solutions and possible new methodologies helping customers to perform such investigations.I. INTRODUCTIONAlthough the cloud might appear attractive to small as well as to large companies, it does not come along without its own unique problems. Outsourcing sensitive corporate data into the cloud raises concerns regarding the privacy and security of data. Security policies, companies main pillar concerning security, cannot be easily deployed into distributed, virtualized cloud environments. This situation is further complicated by the unknown physical location of the companie’s assets. Normally,if a security incident occurs, the corporate security team wants to be able to perform their own investigation without dependency on third parties. In the cloud, this is not possible anymore: The CSP obtains all the power over the environmentand thus controls the sources of evidence. In the best case, a trusted third party acts as a trustee and guarantees for the trustworthiness of the CSP. Furthermore, the implementation of the technical architecture and circumstances within cloud computing environments bias the way an investigation may be processed. In detail, evidence data has to be interpreted by an investigator in a We would like to thank the reviewers for the helpful comments and Dennis Heinson (Center for Advanced Security Research Darmstadt - CASED) for the profound discussions regarding the legal aspects of cloud forensics. proper manner which is hardly be possible due to the lackof circumstantial information. For auditors, this situation does not change: Questions who accessed specific data and information cannot be answered by the customers, if no corresponding logs are available. With the increasing demand for using the power of the cloud for processing also sensible information and data, enterprises face the issue of Data and Process Provenance in the cloud [10]. Digital provenance, meaning meta-data that describes the ancestry or history of a digital object, is a crucial feature for forensic investigations. In combination with a suitable authentication scheme, it provides information about who created and who modified what kind of data in the cloud. These are crucial aspects for digital investigations in distributed environments such as the cloud. Unfortunately, the aspects of forensic investigations in distributed environment have so far been mostly neglected by the research community. Current discussion centers mostly around security, privacy and data protection issues [35], [9], [12]. The impact of forensic investigations on cloud environments was little noticed albeit mentioned by the authors of [1] in 2009: ”[...] to our knowledge, no research has been published on how cloud computing environments affect digital artifacts,and on acquisition logistics and legal issues related to cloud computing env ironments.” This statement is also confirmed by other authors [34], [36], [40] stressing that further research on incident handling, evidence tracking and accountability in cloud environments has to be done. At the same time, massive investments are being made in cloud technology. Combined with the fact that information technology increasingly transcendents peoples’ private and professional life, thus mirroring more and more of peoples’actions, it becomes apparent that evidence gathered from cloud environments will be of high significance to litigation or criminal proceedings in the future. Within this work, we focus the notion of cloud forensics by addressing the technical issues of forensics in all three major cloud service models and consider cross-disciplinary aspects. Moreover, we address the usability of various sources of evidence for investigative purposes and propose potential solutions to the issues from a practical standpoint. This work should be considered as a surveying discussion of an almost unexplored research area. The paper is organized as follows: We discuss the related work and the fundamental technical background information of digital forensics, cloud computing and the fault model in section II and III. In section IV, we focus on the technical issues of cloud forensics and discuss the potential sources and nature of digital evidence as well as investigations in XaaS environments including thecross-disciplinary aspects. We conclude in section V.II. RELATED WORKVarious works have been published in the field of cloud security and privacy [9], [35], [30] focussing on aspects for protecting data in multi-tenant, virtualized environments. Desired security characteristics for current cloud infrastructures mainly revolve around isolation of multi-tenant platforms [12], security of hypervisors in order to protect virtualized guest systems and secure network infrastructures [32]. Albeit digital provenance, describing the ancestry of digital objects, still remains a challenging issue for cloud environments, several works have already been published in this field [8], [10] contributing to the issues of cloud forensis. Within this context, cryptographic proofs for verifying data integrity mainly in cloud storage offers have been proposed,yet lacking of practical implementations [24], [37], [23]. Traditional computer forensics has already well researched methods for various fields of application [4], [5], [6], [11], [13]. Also the aspects of forensics in virtual systems have been addressed by several works [2], [3], [20] including the notionof virtual introspection [25]. In addition, the NIST already addressed Web Service Forensics [22] which has a huge impact on investigation processes in cloud computing environments. In contrast, the aspects of forensic investigations in cloud environments have mostly been neglected by both the industry and the research community. One of the first papers focusing on this topic was published by Wolthusen [40] after Bebee et al already introduced problems within cloud environments [1]. Wolthusen stressed that there is an inherent strong need for interdisciplinary work linking the requirements and concepts of evidence arising from the legal field to what can be feasibly reconstructed and inferred algorithmically or in an exploratory manner. In 2010, Grobauer et al [36] published a paper discussing the issues of incident response in cloud environments - unfortunately no specific issues and solutions of cloud forensics have been proposed which will be done within this work.III. TECHNICAL BACKGROUNDA. Traditional Digital ForensicsThe notion of Digital Forensics is widely known as the practice of identifying, extracting and considering evidence from digital media. Unfortunately, digital evidence is both fragile and volatile and therefore requires the attention of special personnel and methods in order to ensure that evidence data can be proper isolated and evaluated. Normally, the process of a digital investigation can be separated into three different steps each having its own specificpurpose:1) In the Securing Phase, the major intention is the preservation of evidence for analysis. The data has to be collected in a manner that maximizes its integrity. This is normally done by a bitwise copy of the original media. As can be imagined, this represents a huge problem in the field of cloud computing where you never know exactly where your data is and additionallydo not have access to any physical hardware. However, the snapshot technology, discussed in section IV-B3, provides a powerful tool to freeze system states and thus makes digital investigations, at least in IaaS scenarios, theoretically possible.2) We refer to the Analyzing Phase as the stage in which the data is sifted and combined. It is in this phase that the data from multiple systems or sources is pulled together to create as complete a picture and event reconstruction as possible. Especially in distributed system infrastructures, this means that bits and pieces of data are pulled together for deciphering the real story of what happened and for providing a deeper look into the data.3) Finally, at the end of the examination and analysis of the data, the results of the previous phases will be reprocessed in the Presentation Phase. The report, created in this phase, is a compilation of all the documentation and evidence from the analysis stage. The main intention of such a report is that it contains all results, it is complete and clear to understand. Apparently, the success of these three steps strongly depends on the first stage. If it is not possible to secure the complete set of evidence data, no exhaustive analysis will be possible. However, in real world scenarios often only a subset of the evidence data can be secured by the investigator. In addition, an important definition in the general context of forensics is the notion of a Chain of Custody. This chain clarifies how and where evidence is stored and who takes possession of it. Especially for cases which are brought to court it is crucial that the chain of custody is preserved.B. Cloud ComputingAccording to the NIST [16], cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal CSP interaction. The new raw definition of cloud computing brought several new characteristics such as multi-tenancy, elasticity, pay-as-you-go and reliability. Within this work, the following three models are used: In the Infrastructure asa Service (IaaS) model, the customer is using the virtual machine provided by the CSP for installing his own system on it. The system can be used like any other physical computer with a few limitations. However, the additive customer power over the system comes along with additional security obligations. Platform as a Service (PaaS) offerings provide the capability to deploy application packages created using the virtual development environment supported by the CSP. For the efficiency of software development process this service model can be propellent. In the Software as a Service (SaaS) model, the customer makes use of a service run by the CSP on a cloud infrastructure. In most of the cases this service can be accessed through an API for a thin client interface such as a web browser. Closed-source public SaaS offers such as Amazon S3 and GoogleMail can only be used in the public deployment model leading to further issues concerning security, privacy and the gathering of suitable evidences. Furthermore, two main deployment models, private and public cloud have to be distinguished. Common public clouds are made available to the general public. The corresponding infrastructure is owned by one organization acting as a CSP and offering services to its customers. In contrast, the private cloud is exclusively operated for an organization but may not provide the scalability and agility of public offers. The additional notions of community and hybrid cloud are not exclusively covered within this work. However, independently from the specific model used, the movement of applications and data to the cloud comes along with limited control for the customer about the application itself, the data pushed into the applications and also about the underlying technical infrastructure.C. Fault ModelBe it an account for a SaaS application, a development environment (PaaS) or a virtual image of an IaaS environment, systems in the cloud can be affected by inconsistencies. Hence, for both customer and CSP it is crucial to have the ability to assign faults to the causing party, even in the presence of Byzantine behavior [33]. Generally, inconsistencies can be caused by the following two reasons:1) Maliciously Intended FaultsInternal or external adversaries with specific malicious intentions can cause faults on cloud instances or applications. Economic rivals as well as former employees can be the reason for these faults and state a constant threat to customers and CSP. In this model, also a malicious CSP is included albeit he isassumed to be rare in real world scenarios. Additionally, from the technical point of view, the movement of computing power to a virtualized, multi-tenant environment can pose further threads and risks to the systems. One reason for this is that if a single system or service in the cloud is compromised, all other guest systems and even the host system are at risk. Hence, besides the need for further security measures, precautions for potential forensic investigations have to be taken into consideration.2) Unintentional FaultsInconsistencies in technical systems or processes in the cloud do not have implicitly to be caused by malicious intent. Internal communication errors or human failures can lead to issues in the services offered to the costumer(i.e. loss or modification of data). Although these failures are not caused intentionally, both the CSP and the customer have a strong intention to discover the reasons and deploy corresponding fixes.IV. TECHNICAL ISSUESDigital investigations are about control of forensic evidence data. From the technical standpoint, this data can be available in three different states: at rest, in motion or in execution. Data at rest is represented by allocated disk space. Whether the data is stored in a database or in a specific file format, it allocates disk space. Furthermore, if a file is deleted, the disk space is de-allocated for the operating system but the data is still accessible since the disk space has not been re-allocated and overwritten. This fact is often exploited by investigators which explore these de-allocated disk space on harddisks. In case the data is in motion, data is transferred from one entity to another e.g. a typical file transfer over a network can be seen as a data in motion scenario. Several encapsulated protocols contain the data each leaving specific traces on systems and network devices which can in return be used by investigators. Data can be loaded into memory and executed as a process. In this case, the data is neither at rest or in motion but in execution. On the executing system, process information, machine instruction and allocated/de-allocated data can be analyzed by creating a snapshot of the current system state. In the following sections, we point out the potential sources for evidential data in cloud environments and discuss the technical issues of digital investigations in XaaS environmentsas well as suggest several solutions to these problems.A. Sources and Nature of EvidenceConcerning the technical aspects of forensic investigations, the amount of potential evidence available to the investigator strongly diverges between thedifferent cloud service and deployment models. The virtual machine (VM), hosting in most of the cases the server application, provides several pieces of information that could be used by investigators. On the network level, network components can provide information about possible communication channels between different parties involved. The browser on the client, acting often as the user agent for communicating with the cloud, also contains a lot of information that could be used as evidence in a forensic investigation. Independently from the used model, the following three components could act as sources for potential evidential data.1) Virtual Cloud Instance: The VM within the cloud, where i.e. data is stored or processes are handled, contains potential evidence [2], [3]. In most of the cases, it is the place where an incident happened and hence provides a good starting point for a forensic investigation. The VM instance can be accessed by both, the CSP and the customer who is running the instance. Furthermore, virtual introspection techniques [25] provide access to the runtime state of the VM via the hypervisor and snapshot technology supplies a powerful technique for the customer to freeze specific states of the VM. Therefore, virtual instances can be still running during analysis which leads to the case of live investigations [41] or can be turned off leading to static image analysis. In SaaS and PaaS scenarios, the ability to access the virtual instance for gathering evidential information is highly limited or simply not possible.2) Network Layer: Traditional network forensics is knownas the analysis of network traffic logs for tracing events that have occurred in the past. Since the different ISO/OSI network layers provide several information on protocols and communication between instances within as well as with instances outside the cloud [4], [5], [6], network forensics is theoretically also feasible in cloud environments. However in practice, ordinary CSP currently do not provide any log data from the network components used by the customer’s instances or applications. For instance, in case of a malware infection of an IaaS VM, it will be difficult for the investigator to get any form of routing information and network log datain general which is crucial for further investigative steps. This situation gets even more complicated in case of PaaS or SaaS. So again, the situation of gathering forensic evidence is strongly affected by the support the investigator receives from the customer and the CSP.3) Client System: On the system layer of the client, it completely depends on the used model (IaaS, PaaS, SaaS) if and where potential evidence could beextracted. In most of the scenarios, the user agent (e.g. the web browser) on the client system is the only application that communicates with the service in the cloud. This especially holds for SaaS applications which are used and controlled by the web browser. But also in IaaS scenarios, the administration interface is often controlled via the browser. Hence, in an exhaustive forensic investigation, the evidence data gathered from the browser environment [7] should not be omitted.a) Browser Forensics: Generally, the circumstances leading to an investigation have to be differentiated: In ordinary scenarios, the main goal of an investigation of the web browser is to determine if a user has been victim of a crime. In complex SaaS scenarios with high client-server interaction, this constitutes a difficult task. Additionally, customers strongly make use of third-party extensions [17] which can be abused for malicious purposes. Hence, the investigator might want to look for malicious extensions, searches performed, websites visited, files downloaded, information entered in forms or stored in local HTML5 stores, web-based email contents and persistent browser cookies for gathering potential evidence data. Within this context, it is inevitable to investigate the appearance of malicious JavaScript [18] leading to e.g. unintended AJAX requests and hence modified usage of administration interfaces. Generally, the web browser contains a lot of electronic evidence data that could be used to give an answer to both of the above questions - even if the private mode is switched on [19].B. Investigations in XaaS EnvironmentsTraditional digital forensic methodologies permit investigators to seize equipment and perform detailed analysis on the media and data recovered [11]. In a distributed infrastructure organization like the cloud computing environment, investigators are confronted with an entirely different situation. They have no longer the option of seizing physical data storage. Data and processes of the customer are dispensed over an undisclosed amount of virtual instances, applications and network elements. Hence, it is in question whether preliminary findings of the computer forensic community in the field of digital forensics apparently have to be revised and adapted to the new environment. Within this section, specific issues of investigations in SaaS, PaaS and IaaS environments will be discussed. In addition, cross-disciplinary issues which affect several environments uniformly, will be taken into consideration. We also suggest potential solutions to the mentioned problems.1) SaaS Environments: Especially in the SaaS model, the customer does notobtain any control of the underlying operating infrastructure such as network, servers, operating systems or the application that is used. This means that no deeper view into the system and its underlying infrastructure is provided to the customer. Only limited userspecific application configuration settings can be controlled contributing to the evidences which can be extracted fromthe client (see section IV-A3). In a lot of cases this urges the investigator to rely on high-level logs which are eventually provided by the CSP. Given the case that the CSP does not run any logging application, the customer has no opportunity to create any useful evidence through the installation of any toolkit or logging tool. These circumstances do not allow a valid forensic investigation and lead to the assumption that customers of SaaS offers do not have any chance to analyze potential incidences.a) Data Provenance: The notion of Digital Provenance is known as meta-data that describes the ancestry or history of digital objects. Secure provenance that records ownership and process history of data objects is vital to the success of data forensics in cloud environments, yet it is still a challenging issue today [8]. Albeit data provenance is of high significance also for IaaS and PaaS, it states a huge problem specifically for SaaS-based applications: Current global acting public SaaS CSP offer Single Sign-On (SSO) access control to the set of their services. Unfortunately in case of an account compromise, most of the CSP do not offer any possibility for the customer to figure out which data and information has been accessed by the adversary. For the victim, this situation can have tremendous impact: If sensitive data has been compromised, it is unclear which data has been leaked and which has not been accessed by the adversary. Additionally, data could be modified or deleted by an external adversary or even by the CSP e.g. due to storage reasons. The customer has no ability to proof otherwise. Secure provenance mechanisms for distributed environments can improve this situation but have not been practically implemented by CSP [10]. Suggested Solution: In private SaaS scenarios this situation is improved by the fact that the customer and the CSP are probably under the same authority. Hence, logging and provenance mechanisms could be implemented which contribute to potential investigations. Additionally, the exact location of the servers and the data is known at any time. Public SaaS CSP should offer additional interfaces for the purpose of compliance, forensics, operations and security matters to their customers. Through an API, the customers should have the ability to receive specific information suchas access, error and event logs that could improve their situation in case of aninvestigation. Furthermore, due to the limited ability of receiving forensic information from the server and proofing integrity of stored data in SaaS scenarios, the client has to contribute to this process. This could be achieved by implementing Proofs of Retrievability (POR) in which a verifier (client) is enabled to determine that a prover (server) possesses a file or data object and it can be retrieved unmodified [24]. Provable Data Possession (PDP) techniques [37] could be used to verify that an untrusted server possesses the original data without the need for the client to retrieve it. Although these cryptographic proofs have not been implemented by any CSP, the authors of [23] introduced a new data integrity verification mechanism for SaaS scenarios which could also be used for forensic purposes.2) PaaS Environments: One of the main advantages of the PaaS model is that the developed software application is under the control of the customer and except for some CSP, the source code of the application does not have to leave the local development environment. Given these circumstances, the customer obtains theoretically the power to dictate how the application interacts with other dependencies such as databases, storage entities etc. CSP normally claim this transfer is encrypted but this statement can hardly be verified by the customer. Since the customer has the ability to interact with the platform over a prepared API, system states and specific application logs can be extracted. However potential adversaries, which can compromise the application during runtime, should not be able to alter these log files afterwards. Suggested Solution:Depending on the runtime environment, logging mechanisms could be implemented which automatically sign and encrypt the log information before its transfer to a central logging server under the control of the customer. Additional signing and encrypting could prevent potential eavesdroppers from being able to view and alter log data information on the way to the logging server. Runtime compromise of an PaaS application by adversaries could be monitored by push-only mechanisms for log data presupposing that the needed information to detect such an attack are logged. Increasingly, CSP offering PaaS solutions give developers the ability to collect and store a variety of diagnostics data in a highly configurable way with the help of runtime feature sets [38].3) IaaS Environments: As expected, even virtual instances in the cloud get compromised by adversaries. Hence, the ability to determine how defenses in the virtual environment failed and to what extent the affected systems havebeen compromised is crucial not only for recovering from an incident. Also forensic investigations gain leverage from such information and contribute to resilience against future attacks on the systems. From the forensic point of view, IaaS instances do provide much more evidence data usable for potential forensics than PaaS and SaaS models do. This fact is caused throughthe ability of the customer to install and set up the image for forensic purposes before an incident occurs. Hence, as proposed for PaaS environments, log data and other forensic evidence information could be signed and encrypted before itis transferred to third-party hosts mitigating the chance that a maliciously motivated shutdown process destroys the volatile data. Although, IaaS environments provide plenty of potential evidence, it has to be emphasized that the customer VM is in the end still under the control of the CSP. He controls the hypervisor which is e.g. responsible for enforcing hardware boundaries and routing hardware requests among different VM. Hence, besides the security responsibilities of the hypervisor, he exerts tremendous control over how customer’s VM communicate with the hardware and theoretically can intervene executed processes on the hosted virtual instance through virtual introspection [25]. This could also affect encryption or signing processes executed on the VM and therefore leading to the leakage of the secret key. Although this risk can be disregarded in most of the cases, the impact on the security of high security environments is tremendous.a) Snapshot Analysis: Traditional forensics expect target machines to be powered down to collect an image (dead virtual instance). This situation completely changed with the advent of the snapshot technology which is supported by all popular hypervisors such as Xen, VMware ESX and Hyper-V.A snapshot, also referred to as the forensic image of a VM, providesa powerful tool with which a virtual instance can be clonedby one click including also the running system’s mem ory. Due to the invention of the snapshot technology, systems hosting crucial business processes do not have to be powered down for forensic investigation purposes. The investigator simply creates and loads a snapshot of the target VM for analysis(live virtual instance). This behavior is especially important for scenarios in which a downtime of a system is not feasible or practical due to existing SLA. However the information whether the machine is running or has been properly powered down is crucial [3] for the investigation. Live investigations of running virtual instances become more common providing evidence data that。
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Cloud ComputingChen PengSchool of Information Science and Technology, YanChenNormal College,YanChen ChinaEmail:Abstract--Cloud computing is a new computing model；it is developed based on grid computing．We introduced the development history of cloud computing and its application situation and gave a new definition；took google’s cloud computing techniques as an example，summed up key techniques，such as data storage technology(Google )，data management technology(BigTable)，as well as programming model and task scheduling model(Map—Reduce)，used in cloud computing；and analyzed the differences among cloud computing,grid computing and traditional super-computing，and fingered out the further development prospects of cloud computing．Key words:cloud computing；data storage；data management；programming modelⅠ. DefinitionCloud computing is the development of distributed computing, parallel processing, and grid computing, which represents an emerging business computing modelⅡ. Cloud Computing SummaryCloud computing is a kind of network service and is a trend for future computing Scalability matters in cloud computing technology Users focus on application development Services are not known geographicallyⅢ. The specific characteristics1)Data in the cloud: not afraid to lose, do not have to back up,you can restore at any point;2)Software in the cloud: You do not have to download and updateyourself ；3)Ubiquitous computing: at any time, any place, any device, login to enjoy computing services;4)Powerful computing: unlimited space, unlimited speedⅣ. The main forms of service1)Software as a Service(SaaS)2)SaaS service providers deploy application software on theserver, users on demand ordered from the manufacturer via the Internet, service providers charge based on customer's needs, and to provide customers with the software through a browser.3)Platform as a Service(PaaS)4)Manufacturers provide a development environment, serverplatforms, hardware resources services to customers, custom develop their own application and pass through its servers and the Internet to other customers5)Infrastructure services(IaaS)6)"Cloud" infrastructure consisting of multiple servers, providemeasurement services to customers.Ⅴ. Characteristics1)In general, cloud computing customers do not own the physicalinfrastructure, instead avoiding capital expenditure by renting usage from a third-party provider. They consume resources as a service and pay only for resources that they use. Many cloud-computing offerings employ the utility computing model, which is analogous to how traditional utility services (such as electricity) are consumed, whereas others bill on a subscription basis. Sharing "perishable and intangible" computing power among multiple tenants can improve utilization rates, as servers are not unnecessarily left idle (which can reduce costs significantly while increasing the speed of application development). A side-effect of this approach is that overall computer usage rises dramatically, as customers do not have to engineer for peak load limits. In addition, "increased high-speed bandwidth" makes it possible to receive the same response times from centralized infrastructure at other sites.2)The cloud is becoming increasingly associated with small andmedium enterprises (SMEs) as in many cases they cannot justify or afford the large capital expenditure of traditional IT. SMEs also typically have less existing infrastructure, less bureaucracy, more flexibility, and smaller capital budgets forpurchasing in-house technology. Similarly, SMEs in emerging markets are typically unburdened by established legacyinfrastructures, thus reducing the complexity of deployingcloud solutionsⅥ. Origins of cloud computingIn 2006,Google engineer Christophe suggest Google CEO Eric Schmidt the idea of "cloud computing“ at the first time, under the support of Schmidt, Google rollout "Google 101 plan "and formally proposed the concept of “cloud ".Google's concept of “cloud computing” is a picturesque phrase, to describe Google's business model and computing technology architecture in a romantic way.therefore, cloud computing consists two levels of meaning, in commercial level, just the "cloud“; in the technical level is "computing",combined the cloud and computing to illustrate that Google is different with traditional software and hardware companies in business models and computing architecture. This is just a very beautiful and very romantic metaphor.Ⅶ. Brief IntroductionApache Hadoop is a framework for running applications on large cluster built of commodity hardware. The Hadoop framework transparently provides applications both reliability and data motion. Hadoop implements a computational paradigm named Map/Reduce, where the application is divided into many small fragments of work, each of which may be executed or re-executed on any node in the cluster. In addition, it provides a distributed (HDFS) that stores data on the compute nodes, providing very high aggregate bandwidth across the cluster. Both MapReduce and the Hadoop Distributed are designed so that node failures are automatically handled by the framework.Ⅷ. Two Important Technical1)HDFS: Hadoop Distributed (HDFS) is designed to reliably storevery large files across machines in a large cluster. It is inspired by the Google.2)MapReduce: MapReduce is a programming model for processing largedata sets with a parallel, distributed algorithm on a cluster.Ⅸ. 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