Trust, Privacy, and Security in Digital Business: 11th by Claudia Eckert, Sokratis K. Katsikas, Günther Pernul
By Claudia Eckert, Sokratis K. Katsikas, Günther Pernul
This e-book constitutes the refereed court cases of the eleventh foreign convention on belief and privateness in electronic company, TrustBus 2014, held in Munich, Germany, in September 2014 together with DEXA 2014. The sixteen revised complete papers provided have been conscientiously reviewed and chosen from various submissions. The papers are equipped within the following topical sections: belief administration; belief metrics and assessment types; privateness and belief in cloud computing; safeguard administration; and safeguard, belief, and privateness in cellular and pervasive environments.
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Additional resources for Trust, Privacy, and Security in Digital Business: 11th International Conference, TrustBus 2014, Munich, Germany, September 2-3, 2014. Proceedings
In: Seventh Asia Joint Conference on Information Security (Asia JCIS 2012), Tokyo, Japan (August 2012) Android Malware Detection Based on Software Complexity Metrics 35 11. : MAMA: Manifest Analysis for Malware detection in Android. Cybernetics and Systems 44(6-7), 469–488 (2013) 12. : MADS: Malicious Android Applications Detection through String Analysis. , Sandhu, R. ) NSS 2013. LNCS, vol. 7873, pp. 178–191. Springer, Heidelberg (2013) 13. : DREBIN: Eﬀective and Explainable Detection of Android Malware in Your Pocket.
2 Background and Related Work The classiﬁcation of malware based on machine learning has a long history on Windows. , sequences of n bytes of binary code. Since the number of distinct n-grams can be quite large, they applied an information gain attribute ranking to select most relevant n-grams. 98 and a false 26 M. Protsenko and T. 05. In 2013, Kong and Yan  proposed an automated classiﬁcation of Windows malware based on function call graphs, extended with additional features such as API calls and I/O operations.
The users need to trust that the issuers design the credentials in an appropriate manner, so that the credential content does not introduce any privacy risk itself. Similar to any other electronic certiﬁcation system, dishonest issuers have the possibility to block a user from accessing a service without any legitimate reason by revoking her credentials. Therefore the users have to trust that the issuer has no interest in disrupting users activities and will not take any action in this regard as long as the terms of agreement are respected.