ABSTRACT
Information security is of utmost importance to any organization. With the increasing number of attacks on private data, understanding the risk involved with handling and maintaining it is relevant. Although there are various methods to determine the risk associated with a certain organization's data, there is also a need to speed up the process of computation of this risk. This paper discusses the usage of Artificial Neural Networks that bodes well for the non linear nature of the threat vectors that affect risk involved in setting up a distributed MOOC based software system. An optimization to the existing methods is proposed that makes use of the bio inspired, Cuckoo Search Algorithm. With the concept of Levy Flights and Random Walks, this algorithm produces a much faster rate of convergence in calculation of the importance to be given to each threat vector in assessing the security of the software system.
- Bin Luo, Yi Liu, The Risk Evaluation Model of Network information security Based on Improved BP Neural Network IMSNA, 2012.Google Scholar
- Sudarshan Nandy, Partha Pratim Sarkar and Achintya Das, Training a Feed Forward Neural Network With a Practical Bee Colony Based Back Propogation Method IJCSIT, 2012.Google Scholar
- Nazri Mohd. Nawi, Abdullah Khan, M. Z. Rehman, A New Back-Propagation Neural Network Optimized with Cuckoo Search Algorithm Springer-Verlag Berlin Heidelberg, 2013.Google Scholar
- Yao Youli, Liu Jie, Jia Quan, Risk Assessment Model for E-commerce Security based on FCE International Symposium on Web Information Systems and Applications, 1991.Google Scholar
- Dong-Mei Zhao, Jin-Xing Liu, Ze-Hong Zhang, Method of Risk Evualtion Using Information Security Using Neural Networks Eighth International Conference on Machine Learning and Cybernetics, 2009.Google Scholar
- Bilge Karabacaka, Ibrahim Sogukpinar, ISRAM: information security risk analysis method Elsevier, 2005.Google Scholar
- Bob Blakley, Ellen McDermott, Dan Geer, Information security is information risk management Proceedings of the 2001 workshop on New security paradigms, 2001. Google ScholarDigital Library
- Dong-Mei Zhao, Jin-Xing Liu, Ze-Hong Zhang, Information security: The moving target Journal of Computers and Security, 2009. Google ScholarDigital Library
Index Terms
- Information Risk Analysis in a Distributed MOOC Based Software System Using an Optimized Artificial Neural Network
Recommendations
Taxonomy of information security risk assessment (ISRA)
Information is a perennially significant business asset in all organizations. Therefore, it must be protected as any other valuable asset. This is the objective of information security, and an information security program provides this kind of ...
Risk Assessment of Supply Chain Based on BP Neural Network
KAM '09: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling - Volume 02This paper discusses risk assessment of supply chain based on BP neural network. The risk assessment procedure is discussed and after the risk factors of supply chain identification and analysis, the risk assessment model is built with BP neural ...
Information Security Risk Assessment Method Based on CORAS Frame
CSSE '08: Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 03This paper first carry out the summary to the information security risk assessment's present situation and the correlation criterion, then introduced in detail to the risk which possibly exists carry out the quantification based on the CORAS frame's ...
Comments