Information Systems Security and Privacy: First by Olivier Camp, Edgar Weippl, Christophe Bidan, Esma Aïmeur

By Olivier Camp, Edgar Weippl, Christophe Bidan, Esma Aïmeur

This ebook constitutes revised chosen papers from the 1st foreign convention on info structures safeguard and privateness, ICISSP 2015, held in Angers, France, in February 2015.

The 12 papers provided during this quantity have been conscientiously reviewed and choice from a complete of fifty six submissions. They have been prepared in topical sections named: facts and software program protection; privateness and confidentiality; cellular platforms defense; and biometric authentication. The publication additionally comprises invited papers.

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Extra resources for Information Systems Security and Privacy: First International Conference, ICISSP 2015, Angers, France, February 9-11, 2015, Revised Selected Papers

Example text

MalCore: Toward a Practical Malware Identification System 37 valid SCFSs because each character of SCFSs should be checked. On the other hand, the searching time complexity of I-Filtering is O(log s) where s is the number of SCFSs. For S2S matching for each SCFS, each matching is processed through hash value matching whose time complexity is O(1 ) without characterto-character comparison. In addition, the number of comparisons is O(log s) because we stored the hash values in B-tree. Therefore, we can induce the time complexity for finding one SCFS is O(log s) from O(1)O(log s) = O(log s).

Taxonomy for social network data types from the viewpoint of privacy and user control. In: Proceedings of the 8th International Conference on Availability, Reliability and Security (ARES 2013). IEEE (2013, accepted) 19. : Taxonomy of social network data types. EURASIP J. Inf. Sec. 2014(11), 1–17 (2014) 20. : Provider-Independent Social Identity Management for Personal and Professional Applications. D. thesis, University of Regensburg (2013) 21. : An analysis of implemented and desirable settings for identity management on social networking sites.

When we determine whether SCFSs are identical, it is necessary to know whether they are identical to each other but unnecessary to measure how much similar they are because the similarity between matched identical SCFSs is 100 %. This approach can be frequently applied to C2C matching because malware variants in the same family share many identical SCFSs. – Brute-force Malware Comparison: In the similarity measurement procedure, we need to match SCFSs of an input binary with all pre-analyzed malware samples in databases.

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