A Review on Distribution Model for Mobile Agent-Based Information Leakage Prevention
- 1 Computer Science Department, Federal University of Technolog, Akure, Nigeria
- 2 Computer Science Department, Federal University of Technolog, Akure, Nigeria
- 3 Computer Science Department, Federal Polytechnic, Ede, Osun State, Nigeria
Abstract
With the continuous use of cloud and distributed computing, the threats associated with data and information technology (IT) in such an environment have also increased. Thus, data security and data leakage prevention have become important in a distributed environment. In this aspect, mobile agent-based systems are one of the latest mechanisms to identify and prevent the intrusion and leakage of the data across the network. Thus, to tackle one or more of the several challenges on Mobile Agent-Based Information Leakage Prevention, this paper aim at providing a comprehensive, detailed, and systematic study of the Distribution Model for Mobile Agent-Based Information Leakage Prevention. This paper involves the review of papers selected from the journals which are published in 2009 and 2019. The critical review is presented for the distributed mobile agent-based intrusion detection systems in terms of their design analysis, techniques, and shortcomings. Initially, eighty-five papers were identified, but a paper selection process reduced the number of papers to thirteen important reviews.
- British Broadcasting Corporation (BBC) (2014) Target Data Theft Affected 70 Million Customers.
- Verizon (2015) Data Breach Investigations.
- Alneyadi, S., Sithirasenan, E. and Muthukkumarasamy, V. (2016) A Survey on Data Leakage Prevention Systems. Journal of Network and Computer Applications, 62, 137-152. https://doi.org/10.1016/j.jnca.2016.01.008
- Alneyadi, S., Sithirasenan, E. and Muthukkumarasamy, V. (2015) Detecting Data Semantic: A Data Leakage Prevention Approach. 2015 IEEE Trustcom/BigDataSE/ISPA, Helsinki, 20-22 August 2015, 910-917. https://doi.org/10.1109/Trustcom.2015.464
- Margathavall, R.M.P., Pramila, V., Priya, R. and Abiram, P. (2016) Preserving Sensitive Data By Data Leakage Prevention Using Attribute-Based Encryption Algorithm. International Journal of Emerging Technology in Computer Science & Electronics, 21, 3.
- Greenwald, G., MacAskill, E. and Poitras, L. (2013) Edward Snowden: The Whistleblower behind the NSA Surveillance Revelations. The Guardian, 9, 2.
- Mortensen, M. (2014) Who Is Surveilling Whom? Negotiations of Surveillance and Sousveillance in Relation to Wikileaks’ Release of the Gun Camera Tape Collateral Murder. Photographies, 7, 23-37. https://doi.org/10.1080/17540763.2014.896144
- Costante, E., Fauri, D., Etalle, S., Den Hartog, J. and Zannone, N. (2016) A Hybrid Framework for Data Loss Prevention and Detection. 2016 IEEE Security and Privacy Workshops, San Jose, 22-26 May 2016, 324-333. https://doi.org/10.1109/SPW.2016.24
- Ren, L. (2013) DLP Systems: Models, Architecture and Algorithms. 19-21.
- Shabtai, A., Elovici, Y. and Rokach, L. (2012) A Survey of Data Leakage Detection and Prevention Solutions. Springer Science & Business Media, Boston. https://doi.org/10.1007/978-1-4614-2053-8
- Raman, P., Kayacık, H.G. and Somayaji, A. (2011) Understanding Data Leak Prevention. 6th Annual Symposium on Information Assurance, Albany, 7-8 June 2011, 27.
- Yin, F., Yu, R., Wang, L. and Ma, X. (2013) A Distribution Model for Data Leakage Prevention. Proceedings of 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, Shenyang, 20-22 December 2013, 2617-2620. https://doi.org/10.1109/MEC.2013.6885474
- Lee, Y.-C., Bishop, S., Okhravi, H. and Rahimi, S. (2009) Information Leakage Detection in Distributed Systems Using Software Agents. 2009 IEEE Symposium on Intelligent Agents, Nashville, 30 March-2 April 2009, 128-135. https://doi.org/10.1109/IA.2009.4927510