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Lecture Notes in Computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8651卷 108-122页

作者： Li, Nan Mu, Yi Susilo, Willy Guo, Fuchun Varadharajan, Vijay Centre for Computer and Information Security Research School of Computer Science and Software Engineering University of Wollongong Wollongong Australia Department of Computing Macquarie University Sydney Australia

Radio Frequency Identification (RFID) has been widely ad-opted for object identification. An RFID system comprises three essential components, namely RFID tags, readers and a backend server. Conventionally, the system is considered to be controlled by a single party who maintains all the secret information. However, in some practical scenarios, RFID tags, readers and servers could be operated by different parties. Although the private information should not be shared, the system should allow a valid tag to be authenticated by a legal reader. The challenge in designing the system is preserving the tag and reader’s privacy. In this paper, we propose a novel concept of authorized RFID authentication. The proposed protocols allow the tag to be merely identifiable by an authorized reader and the server cannot reveal the tag during the reader-server interaction. We provide a formal definition of privacy and security models of authorized authentication protocols under the strong and weak notions and propose three provably secure protocols. © Springer International Publishing Switzerland 2014.

关键词： Radio frequency identification (RFID)

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An efficient privacy-preserving compressive data gathering scheme in WSNs 1

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

作者： Xie, Kun Ning, Xueping Wang, Xin Wen, Jigang Liu, Xiaoxiao He, Shiming Zhang, Daqiang College of Computer Science and Electronics Engineering Hunan University Changsha410082 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommmunications Beijing100876 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York11790 United States Institute of Computing Technology Chinese Academy of Sciences Beijing100080 China State Grid HuNan Electric Power Company Research Insitute Changsha410000 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China School of Software Engineering Tongji University Shanghai201804 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

Due to the strict energy limitation and the common vulnerability of WSNs, providing efficient and security data gathering in WSNs becomes an essential problem. Compressive data gathering, which is based on the recent breakthroughs in compressive sensing theory, has been proposed as a viable approach for data gathering in WSNs at low communication overhead. Nevertheless, compressive data gathering is susceptible to various attacks due to the open wireless medium. To thwart traffic analysis/flow tracing and realize privacy preservation, this paper proposes a novel Efficient Privacy-Preserving Compressive Data Gathering Scheme which exploits homomorphic encryption functions in compressive data gathering. With homomorphic encryption on the compressive sensing encoded sensory reading messages, the proposed scheme offers two significant privacy-preserving features, message flow untraceability and message content confidentiality, for efficiently thwarting the traffic analysis attacks. Extensive performance evaluations and security analysis demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Compressed sensing

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Two squares canonical factorization 18

Two squares canonical factorization

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18th Prague Stringology Conference, PSC 2014

作者： Bai, Haoyue Franek, Frantisek Smyth, William F. Department of Computing and Software McMaster University HamiltonON Canada School of Computer Science and Software Engineering University of Western Australia Australia

ISBN: (纸本)9788001055472

We present a new combinatorial structure in a string: a canonical factorization for any two squares that occur at the same position and satisfy some size restrictions. We believe that this canonical factorization will have application to related problems such as the New Periodicity Lemma, Crochemore-Rytter Three Squares Lemma, and ultimately the maximum-number-of-runs conjecture. © Czech Technical University in Prague, Czech Republic.

关键词： Double square Factorization Primitive string Square String

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Cross-project build co-change prediction

Cross-project build co-change prediction

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IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Xin Xia David Lo Shane McIntosh Emad Shihab Ahmed E. Hassan College of Computer Science and Technology Zhejiang University Hangzhou China School of Information Systems Singapore Management University Singapore School of Computing Queen's University Kingston Canada Department of Computer Science and Software Engineering Concordia University Montreal Canada

Build systems orchestrate how human-readable source code is translated into executable programs. In a software project, source code changes can induce changes in the build system (aka. build co-changes). It is difficult for developers to identify when build co-changes are necessary due to the complexity of build systems. Prediction of build co-changes works well if there is a sufficient amount of training data to build a model. However, in practice, for new projects, there exists a limited number of changes. Using training data from other projects to predict the build co-changes in a new project can help improve the performance of the build co-change prediction. We refer to this problem as cross-project build co-change prediction. In this paper, we propose CroBuild, a novel cross-project build co-change prediction approach that iteratively learns new classifiers. CroBuild constructs an ensemble of classifiers by iteratively building classifiers and assigning them weights according to its prediction error rate. Given that only a small proportion of code changes are build co-changing, we also propose an imbalance-aware approach that learns a threshold boundary between those code changes that are build co-changing and those that are not in order to construct classifiers in each iteration. To examine the benefits of CroBuild, we perform experiments on 4 large datasets including Mozilla, Eclipse-core, Lucene, and Jazz, comprising a total of 50,884 changes. On average, across the 4 datasets, CroBuild achieves a F1-score of up to 0.408. We also compare CroBuild with other approaches such as a basic model, AdaBoost proposed by Freund et al., and TrAdaBoost proposed by Dai et al.. On average, across the 4 datasets, the CroBuild approach yields an improvement in F1-scores of 41.54%, 36.63%, and 36.97% over the basic model, AdaBoost, and TrAdaBoost, respectively.

关键词： Predictive models Training Data models Measurement Error analysis Buildings Training data

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Virtual Machine Image Content Aware I/O Optimization for Mobile Virtualization

Virtual Machine Image Content Aware I/O Optimization for Mob...

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IEEE International Symposium on Cyberspace Safety and Security

作者： Renhai Chen Yi Wang Jingtong Hu Duo Liu Zili Shao Yong Guan Embedded Systems and CPS Laboratory Department of Computing The Hong Kong Polytechnic University College of Computer Science and Software Engineering Shenzhen University School of Electrical and Computer Engineering Oklahoma State University College of Computer Science Chongqing University College of Computer and Information Management Capital Normal University

ISBN: (纸本)9781479989386

Mobile virtualization introduces extra layers in software stacks, which leads to performance degradation. Especially, each I/O operation has to pass through several software layers to reach the NAND-flash-based storage systems. This paper targets at optimizing I/O for mobile virtualization, since I/O becomes one of major performance bottlenecks that seriously affects the performance of mobile devices. Among all the I/O operations, a large percentage is updating metadata. Frequent updating metadata not only degrades overall I/O performance but also severely reduces flash memory lifetime. In this paper, we propose a novel I/O optimization technique to identify the metadata of a guest file system which is stored in a VM (Virtual Machine) image file and frequently updated. Then, these metadata are stored in a small additional NVM (Non-Volatile Memory) which is faster and more endurable to greatly improve flash memory's performance and lifetime. To the best of our knowledge, this is the first work to identify the file system metadata from regular data in a guest OS VM image file under mobile virtualization. The proposed scheme is evaluated on a real hardware embedded platform. The experimental results show that the proposed techniques can improve write performance to 45.21% in mobile devices with virtualization.

关键词： IO Virtualization Metadata Mobile devices virtual machines Cache Memory System degradation of performance Mobile Conference documents

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Wireshark window authentication based packet captureing scheme to pervent DDoS related security issues in cloud network nodes

Wireshark window authentication based packet captureing sche...

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IEEE International Conference on software engineering and Service sciences (ICSESS)

作者： Waqar Ali Jun Sang Hamad Naeem Rashid Naeem Ali Raza School of Software Engineering Chongqing University Chongqing China Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing China Department of computer science International Islamic University Kuala lumpur Malaysia

DoS (Denial of Service) attack forces a cloud network node to handle few unauthorized access that employ unwanted computing cycle. As a result, the cloud node response is slow as usual and resource on cloud network becomes unavailable. Some Dos attacks are Ping of Death, Teardrop, Snork, Locking authentication, SYN flooding, Operating System Attacks etc. The most vulnerable incident happen when the adversary is committed DDoS (Distributed Denial of Service) attack with comprised cloud network. In this paper, the prevention techniques for DDoS (Distributed Denial of Service) attack in cloud nodes were discussed, a dynamic window scheme in cloud nodes to determine a message verification to resolve unnecessary packet processing was proposed.

关键词： Computer crime Service computing Computer science software engineering software Computers

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Cover Image, Volume 84, Issue 7

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Proteins: Structure, Function, and Bioinformatics 2016年第7期84卷

作者： Wei Wang Juan Liu Lin Sun Department of Computer Science and Technology College of Computer and Information Engineering Henan Normal University Xinxiang 453007 China Laboratory of Computation Intelligence and Information Processing Engineering Technology Research Center for Computing Intelligence and Data Mining Henan Province China Institute of Computer Software School of Computer Wuhan University Wuhan 430072 China

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Emotion recognition from thermal infrared images using deep Boltzmann machine

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Frontiers of Computer science 2014年第4期8卷 609-618页

作者： Shangfei WANG Menghua HE Zhen GAO Shan HE Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA

Facial expression and emotion recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there are no image features specially designed for thermal infrared images. In this paper, we propose using the deep Boltzmann machine to learn thermal features for emotion recognition from thermal infrared facial images. First, the face is located and normalized from the thermal infrared im- ages. Then, a deep Boltzmann machine model composed of two layers is trained. The parameters of the deep Boltzmann machine model are further fine-tuned for emotion recognition after pre-tralning of feature learning. Comparative experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, eye, and mouth are more effective for discriminating valence dimension of emotion than other facial areas. In addition, our study shows that adding unlabeled data from other database during training can also improve feature learning performance.

关键词： emotion recognition thermal infrared images deep Boltzmann machine

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RFID cardinality estimation with blocker tags

RFID cardinality estimation with blocker tags

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Xiulong Liu Bin Xiao Keqiu Li Jie Wu Alex X. Liu Heng Qi Xin Xie Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science and Technology Dalian University of Technology China Department of Computer and Information Sciences Temple University USA National Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Engineering Michigan State University USA

The widely used RFID tags impose serious privacy concerns as a tag responds to queries from readers no matter they are authorized or not. The common solution is to use a commercially available blocker tag which behaves as if a set of tags with known blocking IDs are present. The use of blocker tags makes RFID estimation much more challenging as some genuine tag IDs are covered by the blocker tag and some are not. In this paper, we propose REB, the first RFID estimation scheme with the presence of blocker tags. REB uses the framed slotted Aloha protocol specified in the C1G2 standard. For each round of the Aloha protocol, REB first executes the protocol on the genuine tags and the blocker tag, and then virtually executes the protocol on the known blocking IDs using the same Aloha protocol parameters. The basic idea of REB is to conduct statistically inference from the two sets of responses and estimate the number of genuine tags. We conduct extensive simulations to evaluate the performance of REB, in terms of time-efficiency and estimation reliability. The experimental results reveal that our REB scheme runs tens of times faster than the fastest identification protocol with the same accuracy requirement.

关键词： Estimation Radiofrequency identification Protocols Accuracy Computers Privacy Conferences

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Cluster analysis based on opinion mining

Cluster analysis based on opinion mining

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IEEE International Conference on Ubi-Media computing

作者： Xiaoye Wang Xiaorui Chai Ching-Hsien Hsu Yingyuan Xiao Yukun Li Ministry of Education Tianjin University of Technology Tianjin China Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

ISBN: (纸本)9781467382717

Mining based on opinions can extract useful information from users' comments. After doing cluster and analysis on the information, users can get a detailed understanding of the commodity, then determine to buy the commodity or not. In this paper, firstly, we extract evaluation objects and evaluation words, then cluster the evaluation objects. Next based on SO-PMI algorithm, judge the polarity of evaluation words and determine their polarity intensity values, then use K-means clustering algorithm to cluster the evaluation words. Last, for every kind of target evaluation object, make a count on the proportion of each kind evaluation word, and show the result to users in an intuitive way. This paper uses noun phrase pattern to match comments to extract evaluation objects and put forward the thematic words extraction algorithm. On judging the evaluation words' polarity, this paper establishes an emotional seed dictionary for each target object. The method of establishing dictionary for every attribute can eliminate the influence that less-correlation evaluation words have on the polarity judgment.

关键词： Dictionaries Clustering algorithms Computers Correlation Semantics Algorithm design and analysis Data mining

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