Detection of Sensitive Data Leakage for Privacy Preserving
DOI:
https://doi.org/10.26438/ijcse/v6i9.765769Keywords:
Data leakage, Downsampling, Backpropagation algorithmAbstract
According to Risk Base Security, during last few years leakage of sensitive data record has increased. Human mistake is one of the important reason for data exposure. There is an approach in which data is monitored during transmission to detect the inadvertent data leak cause by human mistakes. However it makes the detection process difficult. There is a need of method that support accurate detection without revealing sensitive data. In particular system, Human identity i,e fingerprint is applied to data file for authentication. It is the process in which original fingerprint matrix is compressed using novel down sampling technique. In the technique, original matrix is compressed by calculating arithmetic mean of the sum of the pixel values on each input row matrix to generate a unit input vector for artificial neural network. The fingerprint samples are matched using back propagation technique. The evaluation result shows improved accuracy and detection time.
References
Xiaokui Shu, Danfeng Yao and Elisa Bertino, fellow," Privacy-Preserving Detection of Sensitive Data Exposure" IEEE Trans. on Information Forensics and Security, Vol. 10, No. 5,pp.1092-1103, May 2015.
Liu F., Shu X., Yao D., and A. R. Butt, "Privacy-preserving scanning of big content for sensitive data exposure with MapReduce," in Proc. ACM Conference on Data Application Security and Privacy, pp.195-206, 2015.
Jagtap V. and Mishra S.," Fast efficient artificial neural network for handwritten digit recognition," International Journal of Computer Science and Information Technologies, vol. 5, pp. 2302-2306., 2014.
Hahn-Ming Lee, Chih-Ming Cheb, Tzong-Ching Huang "Learning improvement of back propagation algorithm by error saturation prevention method," Neurocomputing, November 2001, pp. 125-143.
Lei Yu, Mohamed Laaraiedh, Stephane Avrillon, "Fingerprint localisation based on neural networks and ultra-wide band signals," IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao, pp. 184-189, 14-17 December 2011.
Shu X. and Yao D., "Data leak detection as a service," in Proc. 8th Int. Conf. Secur.Privacy Commun. Netw"., pp. 222-240, 2012.
K. Borders, E. V. Weele, B. Lau, and A. Prakash, "Protecting con_dential data on personal computers with storage capsules," in Proc. 18th USENIX Secur. Symp. , pp. 367-382 ,2009.
A. Nadkarni and W. Enck, "Preventing accidental data disclosure in modern operating systems," in Proc. 20th ACM Conf. Comput. Commun. Secur., pp. 1029-1042, 2013.
Risk Based Security. (Feb. 2017). Data Breach Quick- View: An Executive's Guide to 2013 Data Breach Trends. [Online]. Available: https://www.riskbasedsecurity.com/reports /2016 DataBreachQuickView.pdf, accessed on Oct. 2017.
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