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Titlebook: Security, Privacy and Anonymity in Computation, Communication and Storage; SpaCCS 2016 Internat Guojun Wang,Indrakshi Ray,Sabu M. Thampi Co

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A Software Detection Mechanism Based on SMM in Network Computinglement it on OS kernel or hypervisor level. However, if the system is attacked by the ring 0 or ring 1 level risks, the OS kernel or hypervisor is unable to provide the trusted base, which may cause an incorrect result. To solve the shortcomings, we choose the System Management Mode (SMM) to build a
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ChainMR Crawler: A Distributed Vertical Crawler Based on MapReduceo manage URLs and choose the distributed database Hbase to store the key content of web pages. Experimental results demonstrate that the efficiency of ChainMR Crawler is 6 % higher than Nutch in the field of vertical crawler, which achieves the expected effect.
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Conference proceedings 2016tation, Communication and Storage, SpaCCS 2016, held in Zhangjiajie, China, in November 2016: the 7th International Workshop on Trust, Security and Privacy for Big Data, TrustData 2016; the 6th International Symposium on Trust, Security and Privacy for Emerging Applications, TSP 2016; the 4th Intern
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Detection of Malicious Executables Using Static and Dynamic Features of Portable Executable (PE) Filrated feature vector is then analyzed and classified using classification algorithms. In this work, we also present a comparison of the performance of four classifiers i.e. SVM, Naïve Bayes, J48 and Random Forest. Based on the classification results, we deduce that Random Forest performs best with an accuracy of 97.2 %.
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A Caching-Based Privacy-Preserving Scheme for Continuous Location-Based ServicesS server. At the same time, we propose the cloaking region mechanism based on the move direction of the user to improve the cache hit ratio. Security analysis shows that our proposal can effectively protect the user’s location privacy.
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AppWalker: Efficient and Accurate Dynamic Analysis of Apps via Concolic Walking Along the Event-Depeing along the event-dependency graph. We implement AppWalker based on it. Evaluation over a real-life app set shows that better efficiency and accuracy than state-of-the-art concolic analysis tools are achieved.
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