Analyzing and Managing the Impact of Risks using Multi Fuzzy Inference System
Malaya K Nayak1, Arka K. Das Mohapatra3
1Dr. Malaya Kumar Nayak, Director, IT Buzz Ltd and U-Com Software Private Ltd, Satya Nagar, Bhubaneswar, India.
2Prof. Dr. A. K. Das Mohapatra, Professor, Department of Business Administration, Sambalpur University, Odisha, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1567-1571 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7452038620/2020©BEIESP | DOI: 10.35940/ijrte.F7452.038620
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Information technology security risk evaluations are necessary in determining measures being taken for risk analysis. Risk analysis is also significant as it predicts the loopholes in the software which can get manipulated during suspicious activities. The article has attempted to analyze the risk issue and further suggests a multi-fuzzy risk evaluation approach for the identification of security threats. This approach analyses hacker risks based on the potential ability for an assailant, their overall probability for an attacks as well as the implications of such attacks. It typically consists of 3 sub fuzzy inference structures. The 1st fuzzy inference structure assesses an assailant’s total capacities. The 2nd fuzzy inference structure assesses the general probability of ambush success, whereas the 3rd fuzzy inference structure measures risk thresholds.
Keywords: IT Risks, Project Risk Management, Fuzzy Interference System, Risk Evaluation, Project Management.
Scope of the Article: Simulation Optimization and Risk Management.