Titlebook: Security and Privacy in Mobile Information and Communication Systems; 4th International Co Andreas U. Schmidt,Giovanni Russello,Shiguo Lian

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Program Structure-Based Feature Selection for Android Malware Analysisations, and that many of them utilized common advertisement libraries. Such benign code reuse in malware can be expected to cause automated classification and clustering approaches to fail if they base their decisions on features relating to the reused code. To improve detection, classification, and

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Presenting the Brazilian Project TSAM – Security Technologies for Mobile Environmentssses, about 40 million of them for data accesses. During the last quarter of 2011, project TSAM has started with a planned duration of 36 months and the main goal of providing security technologies for mobile environments, concerning secure communication, secure assessments and malware analysis.

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Scalable Trust Assessment and Remediation of Wireless Devices devices, trust issues have new qualities. Concurrently, end-user devices are technically open platforms, and also pose security threats on a large scale to users and networks. Thus, fault detection and remediation methods become costly. It is a key challenge to balance the requirements of scalabili

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Context-Aware, Data-Driven Policy Enforcement for Smart Mobile Devices in Business Environmentsging the IT landscape and its security requirements. This poses challenges in terms of data security, the adherence to privacy laws, and the protection of business assets. To tackle the problem, we developed a data-driven usage control infrastructure that enables integration of smart mobile devices

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Securing Mobile Device-Based Machine Interactions with User Location Historiesuctivity or usability, but risk unauthorized access or unwanted unattended operation. Systems for location based access control have been developed to restrict the user to be in specific locations in order to proceed in a workflow. However, these approaches do not consider the movement pattern of a

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Using Extracted Behavioral Features to Improve Privacy for Shared Route Trackss may seriously violate users’ privacy. Existing privacy methods suffer from the fact that they degrade service quality when adding privacy. In this paper, we present the concept of . that addresses the problem without degrading service quality by substituting location tracks with less privacy invas

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Securing Data Privacy on Mobile Devices in Emergency Health Situations is protected by privacy rules and laws in most jurisdictions. It is therefore a challenge to be able to provide the response team with the relevant data while protecting the privacy of that data. In this paper, we present a system designed to enhance privacy protection of sensitive data downloaded