The week's pick
Reseach Article
Detection of Data Leakage using Misuseability Weight Measure
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 70 - Number 21 |
| Year of Publication: 2013 |
| Authors: Mohanapaiya C, Thanapal P |
10.5120/12189-8233
|
Mohanapaiya C, Thanapal P . Detection of Data Leakage using Misuseability Weight Measure. International Journal of Computer Applications. 70, 21 ( May 2013), 7-12. DOI=10.5120/12189-8233
Abstract
Data leakage is a leakage which the information's were leaked out unknowingly. Especially company has partnership with other companies that need to share the information's together. A distributor has a set of given sensitive data to hypothetical trusted third party agents. While sharing the transactions data leakage may occur at any place. Preventing the data leakage is a serious challenge for organizations. In order to overcome these problems an M-score measurability weight measure is introduced. The goal of weight measure is to detect the data leakage when the sensitive data has been leaked, and if possible to identify the agent that leaked the data. This regards applications where the data cannot be perturbed. Perturbation is a useful technique where the data is modified and made less sensitive before being hand over to agents.
References
- Amir Harel, Asaf Shabtai, Lior Rokach and Yuval Elovici, 2009, M-score: A Misuseability weight measure, IEEE Transactions on Dependable and Secure Computing.
- William Eberle and Lawrence Holder,2009, Mining for insider threats in business transaction and process, IEEE Transaction .
- Zhang Xiaosong, Liu Fei , Chen Ting, Li Hua,2009, Research and application of the transparent data encryption in intranet data leakage prevention, International conference on computational intelligence and security.
- Jiangjiang Wu, Jie Zhou, Jun Ma, Songzhu Mei, Jiangchun Ren, 2011, An active data leakage prevention model for insider threat, International symposium on intelligence information
- Bernhard Riedl, Veronika Grascher, Stefan Fenz, Thomas Neubauer, 2008, Pseudonymization for improving the privacy in e-Health applications, Proceedings of the 41st Hawaii international conference on system sciences.
- Majid Raissi-Dehkordi and David Carr,20ll A multi-perspective approach to insider threat detection, The military communications conference-track 3-cyber security and network operations.
- Panagiotis Papadimitriou, Hector Garcia-Molina, 2005, A model for data leakage detection, IEEE international conference on data engineering.
- Khanh viet, Brajendra panda, Yi Hu, 2012 Detecting collaborative insider attacks in information systems, IEEE international conference on systems, man, and cybernetics.
- C. Nithiyandam, D. Tamilselvan, S. Balaji, V. Sivaguru, 2002, Advanced framework of defense system for prevention of insider's malicious behaviors.
Index Terms
Keywords