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11th International Conference Security and Privacy in Communication Networks, SecureComm 2015

作者： Sun, Hao Wang, Xiaofeng Su, Jinshu Chen, Peixin College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9783319288642

Cybercrime caused by malware becomes a persistent and damaging threat which makes the trusted security solution urgently demanded, especially for resource-constrained ends. The existing industry and academic approaches provide available anti-malware systems based on different perspectives. However, it is hard to achieve high performance detection and data privacy protection simultaneously. This paper proposes a cloud-based anti-malware system, called RScam, which provides fast and trusted security service for the resource-constrained ends. In RScam, we present suspicious bucket filtering, a novel signature-based detection mechanism based on the reversible sketch structure, which provides retrospective and accurate orientations of malicious signature fragments. Then we design a lightweight client which utilizes the digest of signature fragments to sharply reduce detection range. Finally, we design balanced interaction mechanism, which transmits sketch coordinates of suspicious file fragments and transformation of malicious signature fragments between the client and cloud server to protect data privacy and reduce traffic volume. We evaluate the performance of RScam with campus suspicious traffic and normal files. The results demonstrate validity and veracity of the proposed mechanism. Our system can outperform other existing systems with less time and traffic consumption. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015.

关键词： Malware

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Network Traffic Generation Based on Statistical Packet-Level Characteristics

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China Communications 2015年第S2期12卷 144-148页

作者： WANG Dongbin ZHUO Weihan ZHANG Junhui WU Kexin OUYANG Wen School of Software Engineering Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Security (BUPT) Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

Network traffic is very important for testing network equipment, network services, and security products. A new method of generating traffic based on statistical packet-level characteristics is proposed. In every time unit, the generator determines the sent packets number, the type and size of every sent packet according to the statistical characteristics of the original traffic. Then every packet, in which the protocol headers of transport layer, network layer and ethernet layer are encapsulated, is sent via the responding network interface card in the time unit. The results in the experiment show that the correlation coefficients between the bandwidth, the packet number, packet size distribution, the fragment number of the generated network traffic and those of the original traffic are all more than 0.96. The generated traffic and original traffic are very highly related and similar.

关键词： network traffic generation packet-level traffic characteristics

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SYNC or ASYNC: Time to fuse for distributed graph-parallel computation 2015

SYNC or ASYNC: Time to fuse for distributed graph-parallel c...

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20th ACM SIGPLAN Symposium on Principles and Practice of parallel Programming, PPoPP 2015

作者： Xie, Chenning Chen, Rong Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332057

Large-scale graph-structured computation usually exhibits iterative and convergence-oriented computing nature, where input data is computed iteratively until a convergence condition is reached. Such features have led to the development of two different computation modes for graph-structured programs, namely synchronous (Sync) and asynchronous (Async) modes. Unfortunately, there is currently no in-depth study on their execution properties and thus programmers have to manually choose a mode, either requiring a deep understanding of underlying graph engines, or suffering from suboptimal performance. This paper makes the first comprehensive characterization on the performance of the two modes on a set of typical graph-parallel applications. Our study shows that the performance of the two modes varies significantly with different graph algorithms, partitioning methods, execution stages, input graphs and cluster scales, and no single mode consistently outperforms the other. To this end, this paper proposes Hsync, a hybrid graph computation mode that adaptively switches a graph-parallel program between the two modes for optimal performance. Hsync constantly collects execution statistics on-the-fly and leverages a set of heuristics to predict future performance and determine when a mode switch could be profitable. We have built online sampling and offline profiling approaches combined with a set of heuristics to accurately predicting future performance in the two modes. A prototype called PowerSwitch has been built based on PowerGraph, a state-of-the-art distributed graph-parallel system, to support adaptive execution of graph algorithms. On a 48-node EC2-like cluster, PowerSwitch consistently outperforms the best of both modes, with a speedup ranging from 9% to 73% due to timely switch between two modes. Copyright 2015 ACM.

关键词： Graphic methods

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Unified virtual memory support for deep CNN accelerator on soC FPGA 1

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15th International Conference on Algorithms and Architectures for parallel Processing, ICA3PP 2015

作者： Xiao, Tao Qiao, Yuran Shen, Junzhong Yang, Qianming Wen, Mei College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

Cooperation of CPU and hardware accelerator on SoC FPGA to accomplish computational intensive tasks, provides significant advantages in performance and energy efficiency. However, current operating systems provide little support for accelerators: the OS is unaware that a computational task can be executed either on a CPU core or an accelerator, and provides no assistance in efficient management of data sharing between CPU and accelerator on the DRAM, such as zero copy, data coherence. It’s also hard for current OS to allocate large contiguous physical memory space for accelerator. In this paper, we select the Xilinx ZYNQ as target and qualitatively analyze methods of sharing data. Besides using high-performance (HP) AXI interfaces of the ZYQN device, we develop a novel memory management system for FPGA-based accelerator. It provides a unified virtual space for CPU cores and accelerator so that they can access the same memory space in the operating systems user space. For a deep convolutional neural network task, our design gains up to speed-up of 5. 34x compared to traditional processoraccelerator cooperation. © Springer International Publishing Switzerland 2015.

关键词： Energy efficiency

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Tinman: Eliminating confidential mobile data exposure with security oriented offloading 15

Tinman: Eliminating confidential mobile data exposure with s...

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10th European Conference on Computer Systems, EuroSys 2015

作者： Xia, Yubin Liu, Yutao Tan, Cheng Ma, Mingyang Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems China Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332385

The wide adoption of smart devices has stimulated a fast shift of security-critical data from desktop to mobile devices. However, recurrent device theft and loss expose mobile devices to various security threats and even physical attacks. This paper presents TinMan, a system that protects confidential data such as web site password and credit card number (we use the term cor to represent these data, which is short for Confidential Record) from being leaked or abused even under device theft. TinMan separates accesses of cor from the rest of the functionalities of an app, by introducing a trusted node to store cor and offloading any code from a mobile device to the trusted node to access cor. This completely eliminates the exposure of cor on the mobile devices. The key challenges to TinMan include deciding when and how to efficiently and transparently offload execution;Tin-Man addresses these challenges with security-oriented offloading with a low-overhead tainting scheme called asymmetric tainting to track accesses to cor to trigger offloading, as well as transparent SSL session injection and TCP payload replacement to offload accesses to cor. We have implemented a prototype of TinMan based on Android and demonstrated how TinMan protects the information of user's bank account and credit card number without modifying the apps. Evaluation results also show that TinMan incurs only a small amount of performance and power overhead. Copyright © 2015 ACM.

关键词： Crime

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Ranking Open Source Software Based on Crowd Wisdom

Ranking Open Source Software Based on Crowd Wisdom

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2015 6th IEEE International Conference on Software Engineering and Service Science(ICSESS 2015)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing School of Computer National University of Defense Technology

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in Stack Overflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in Stack Overflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Software ranking Open Source Crowd Wisdom Open Source Community

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Looking for Information Source from Online Social Network with Incomplete Observation

Looking for Information Source from Online Social Network wi...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Peng Shi Lianhong Ding Tianle Zhang National Center for Materials Service Safety University of Science and Technology Beijing Beijing China School of Information Beijing Wuzi University Beijing China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781509035595

Online social network has become an important media for information spreading. To target the origin of rumors and well understand the cause of event, information source in social network should be found out. Unfortunately, because of the huge and complex structure of social network, it is nearly impossible to monitor the complete online social network. To solve this problem, the paper gives a method to look for information source with incomplete observation. The basis of the method is the correlation between activated time and network topology structure. Some experiments are executed and the effect of different sampling methods was analyzed as well. Experiments on BA, WS and Facebook show that the method can produce satisfied results with incomplete observation.

关键词： Observers Network topology Diffusion processes Facebook distributed computing

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Ranking open source software based on crowd wisdom

Ranking open source software based on crowd wisdom

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IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

ISBN: (纸本)9781479983544

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in StackOverflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in StackOverflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Open source software Data models Joining processes Software reusability Internet

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OSSEAN: Mining Crowd Wisdom in Open Source Communities

OSSEAN: Mining Crowd Wisdom in Open Source Communities

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2015 IEEE Symposium on Service-Oriented System Engineering

作者： Gang Yin Tao Wang Huaimin Wang Qiang Fan Yang Zhang Yue Yu Cheng Yang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

Nowadays open source software represents a successful crowd-based software production model and is becoming an ecosystem combining huge amounts of software producers (such as software developers) and consumers (such as software users and customers). Lots of research work has been conducted on analyzing software artifacts created by producers, but few of them reveal the power of feedback from consumers which we believe is very important for the evaluation and evolution of open source software. This paper introduces OSSEAN, a platform for Open Source Software Evaluating, Analyzing and Networking. OSSEAN divides the open source communities into two groups: software production communities and software consumption communities. The former contain structured software artifacts such as projects, source code and issues, while the latter are full of textual documents with rich semantics of user feedback. We show the power of OSSEAN with some interesting demos by analyzing more than 200 thousands of open source projects and 10 million documents.

关键词： Communities Production Data mining Crawlers Open source software Ecosystems

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Cooperative monitoring BGP among autonomous systems

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Security and Communication Networks 2015年第10期8卷 1943-1957页

作者： Hu, Ning Wang, BaoSheng Liu, Xin National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha Hunan China

As the de facto Internet inter-domain routing protocol, BGP protocol has a number of vulnerabilities and weakness. Monitoring BGP is an effective way to improve the security of inter-domain routing. This paper presents a cooperative BGP monitoring method, which is called cooperative information sharing model (CoISM). CoISM is based on self-organization and can be used to solve some problems during BGP monitoring, such as route validation and bogus route notification delivery. CoISM provides autonomous systems with a more comprehensive information view by introducing information diffuse reflection based on initiative inquiry and making use of the relativity of monitoring information. CoISM optimizes the information transmission by leveraging the data locality caused by BGP policy and implements ISP coordination with low communication and deployment cost. More specifically, CoISM provides a self-organizing and incentive mechanism, which drives autonomous systems to coordinate independently and shares information on-demand. CoISM supports incremental deployment and can also be applied to a wide range of inter-domain cooperative management applications such as inter-domain routing failure analysis and intrusion detection. © 2014 John Wiley & Sons, Ltd.

关键词： Monitoring

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