University Events

Description: Topic: Probabilistic Reliability and Security Risk Assessment

Location: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A

Abstract:
With advances and globalization of information technology such as big data and cloud computing, topics about potential risks with security vulnerabilities have been brought to the forefront. Considerable efforts have been made to estimate security risk with an unlimited cycle of disclosed vulnerabilities in the form of threats or attacks and managements to migrate these risks. On the other hand, reliability is often considered as one of the most vital factors that affect functioning of critical computing systems. Existing works on risk analysis have mostly focused on either security or reliability, but not both. In addition, the existing approaches for quantifying risks are mostly based on simple multiplications of frequencies and quantitative consequences of hazard occurrence without considering dependencies among the hazards. In this dissertation research, an integrated framework is explored for simultaneously and systematically modeling and quantifying both reliability and security risk of modern technological systems. Under the framework, causes and effects of different risks are investigated. Analytical methods integrating Markov chains and decision diagrams are developed and demonstrated through a case study on the reliability and security risk occurrence probability analysis of a cloud RAID storage system under attacks. In addition, sequential attacks involving multiple sequence-dependent hazardous actions for a successful attack are modeled and demonstrated through a case study on banking applications subject to Trojan attacks. In the future, methods including (but not limited to) semi-Markov processes and multiple integrals will be investigated for considering arbitrary types of distributions in the risk analysis. More dependent and dynamic reliability and security behaviors will be modeled for probabilistic risk assessment of modern complex systems.

NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.

Advisor: Dr. Liudong Xing
Committee Members: Dr. Hong Liu and Dr. Honggang Wang, Department of Electrical & Computer Engineering, University of Massachusetts Dartmouth; Dr. Yan Sun, Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island.

*For further information, please contact Dr. Liudong Xing at 508.999.8883, or via email at lxing@umassd.edu.