Sensitive Data Leak Detection Based on Boundary Detection

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Abstract:

Sensitive data has a great influence on our daily lives. Once the leakage of sensitive data occurred, the timely detection and response is of great importance. This article puts forward the concept of boundary detection based on the black box testing. And with the idea of boundary detection, a cross-platform sensitive data leakage detection system is built.

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Advanced Materials Research (Volumes 1049-1050)

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1154-1158

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Dj.M. Maric, P.F. Meier and S.K. Estreicher: Mater. Sci. Forum Vol. 83-87 (1992), p.119.

Google Scholar

[2] M.A. Green: High Efficiency Silicon Solar Cells (Trans Tech Publications, Switzerland 1987).

Google Scholar

[3] Y. Mishing, in: Diffusion Processes in Advanced Technological Materials, edtied by D. Gupta Noyes Publications/William Andrew Publising, Norwich, NY (2004), in press.

Google Scholar

[4] G. Henkelman, G. Johannesson and H. Jónsson, in: Theoretical Methods in Condencsed Phase Chemistry, edited by S.D. Schwartz, volume 5 of Progress in Theoretical Chemistry and Physics, chapter, 10, Kluwer Academic Publishers (2000).

Google Scholar

[5] R.J. Ong, J.T. Dawley and P.G. Clem: submitted to Journal of Materials Research (2003).

Google Scholar

[6] P.G. Clem, M. Rodriguez, J.A. Voigt and C.S. Ashley, U.S. Patent 6, 231, 666. (2001).

Google Scholar

[7] Information on http: /www. weld. labs. gov. cn.

Google Scholar

[1] L. Jia, Y. Meng and J. Zhou: Program and Implementation of Privacy Leak Detection of Cell Phone Based on Network Side. Video Engineering. Vol. 37, No. 5 (2013), pp.99-102.

Google Scholar

[2] D. Wei, Z. Tao: Dynamic Privacy Protection Model Based on Android Permissions. Application Research of Computers. Vol. 29, No. 9 (2012), pp.3478-3482.

Google Scholar

[3] C. Y. Cho, S. Y. Lee and C. P. Tan: Network Forensics on Packet Fingerprints.in: 21st IFIP Information Security Conference (SEC 2006), Karlstad, Sweden (2006).

DOI: 10.1007/0-387-33406-8_34

Google Scholar

[4] B. Beizer: Black-box testing: techniques for functional testing of software and systems. John Wiley & Sons, Inc. (1995).

DOI: 10.1109/ms.1996.536464

Google Scholar

[5] B. Qu, C. Nie, B. Xu, et al: Test case prioritization for black box testing. in: Computer Software and Applications Conference (2007), pp.465-474.

DOI: 10.1109/compsac.2007.209

Google Scholar

[6] B. Beizer, J. Wiley: Black box testing: Techniques for functional testing of software and systems. Software, IEEE. Vol. 13, No. 5 (1996), pp.98-109.

DOI: 10.1109/ms.1996.536464

Google Scholar

[7] U. M. Fayyad, G. Piatetsky-Shapiro G, P. Smyth P, et al: Advances in knowledge discovery and data mining. in: 7th Pacific-Asia Conference, Seoul, Korea (2003), pp.99-106.

Google Scholar

[8] J. Han, M. Kamber: Data mining: Concepts and techniques. China Machine Press (2001), pp.3-6.

Google Scholar

[9] C. Clifton, M. Kantarcioglu, J. Vaidya J, et al: Tools for privacy preserving distributed data mining. ACM SIGKDD Explorations Newsletter, Vol. 4, No. 2 (2002), pp.28-34.

DOI: 10.1145/772862.772867

Google Scholar

[10] D. M. Sunday: A very fast substring search algorithm. Communications of the ACM. Vol. 33, No. 8 (1990), pp.132-142.

DOI: 10.1145/79173.79184

Google Scholar

[11] R. Y. Pinter: Efficient string matching with don't-care patterns. Combinatorial ALgorithms on Words, NATO ASI Series. Vol. 12 (1985), pp.11-29.

DOI: 10.1007/978-3-642-82456-2_2

Google Scholar

[12] R. A. Baeza-Yates: String searching algorithms revisited. Algorithms and Data Structures. Springer Berlin Heidelberg (1989), pp.75-96.

DOI: 10.1007/3-540-51542-9_9

Google Scholar

[13] Z. R. Feng, T. Takaoka: On improving the average case of the Boyer-Moore string matching algorithm. Journal of Information Processing. Vol. 10, No. 3 (1988), pp.173-177.

Google Scholar

[14] L. J. Guibas, A. M. Odlyzko: A new proof of the linearity of the Boyer-Moore string searching algorithm. SIAM Journal on Computing. Vol. 9, No. 4 (1980), pp.672-682.

DOI: 10.1137/0209051

Google Scholar

[15] P. Papadimitriou, H. Garcia-Molina: Data leakage detection. IEEE Transactions on Knowledge and Data Engineering. Vol. 23, No. 1 (2011), pp.51-63.

DOI: 10.1109/tkde.2010.100

Google Scholar

[16] P. Papadimitriou, H. Garcia-Molina: A model for data leakage detection. in: Data Engineering, 2009. ICDE'09. IEEE 25th International Conference on (2009). pp.1307-1310.

DOI: 10.1109/icde.2009.227

Google Scholar