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[EECS Colloquium] 11/30(Thu.) 16:00, Cyber Resilience and Metrics, Dr. Jin-Hee Cho (USARL)
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작성일17-11-23 11:57 조회수33
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EECS Colloquium

 

Host: Hyuk Lim / Language: English

Thursday, November 30, 2017, 16:00~

Haerim Hall, EECS-B Bldg. 1st Floor


Cyber Resilience and Metrics

 

Dr. Jin-Hee Cho

U.S. Army Research Laboratory (USARL), Adelphi, Maryland

 

 

Abstract

This talk discusses two research topics: cyber resilience and cyber metrics. For the topic of cyber resilience, this talk will discuss percolation-based network resilience. In percolation theory, network resilience is mainly addressed in terms of identifying a node occupation probability, called percolation threshold, that can tolerate random or targeted attacks where network connectivity is mainly measured by the size of a largest (or giant component). In addition to fault tolerance, this talk introduces the concept of adaptability and recoverability by taking a holistic approach to enhance network resilience. As the case studies considering the three dimensions of network resilience (i.e., fault-tolerance, adaptability, and recoverability) in percolation-based approaches, this talk will discuss the analysis of the effect of adaptation and recoverability strategies on various performance metrics in addition to the size of a largest component under various network conditions and centrality metrics used to select an initial attack nodes.

Another topic is on cyber metrics. Many different kinds of security and/or dependability metrics have been employed to measure the quality of a computer-based system in the state-of-the-art approaches. However, little metrics have been developed to measure multidimensional aspects of system quality as objective indicators to measure the trustworthiness of a system. As an example framework, this talk will address an ontology-based metric framework, called Security, Trust, Resilience, and Agility Metric, namely STRAM. As case studies, this talk will discuss two studies. First, this talk addresses how the trustworthiness of malware detectors can be measured in the absence of ground truth in which we often face the absence of ground truth detection results while measuring the quality of detectors in real world situations. Second, this talk will demonstrate a suite of agility (or adaptation) metrics that measures the timeliness of attack/defense actions as well as the effectiveness of them. Accordingly, this talk will discuss the experimental results of the measured adaptation metrics using real datasets, and share the challenges, insights, and limitations obtained from the experiments.


Bio

Dr. Jin-Hee Cho received the MS and PhD degrees in computer science from the Virginia Tech in 2004 and 2008, respectively. She is currently a computer scientist at the U.S. Army Research Laboratory (USARL), Adelphi, Maryland. Dr. Cho has published over 85 peer-reviewed journal and conference papers in the areas of trust management, cybersecurity, metrics and measurements, network performance analysis, resource allocation, agent-based modeling, uncertainty reasoning and analysis, information fusion / credibility, and social network analysis. She has been actively involved with ARL’s collaborative research programs and collaborated with US academia, industry, and government researchers. In addition, Dr. Cho is actively collaborating with international research partners in academia and government through various international research programs under the US Department of Defense, including UK, Canada, Australia, New Zealand, Singapore, Norway, and South Korea. She received the best paper awards in IEEE TrustCom’2009, BRIMS’2013, GLOBECOM’2017, and 2017 ARL’s publication award. She is a winner of the 2015 IEEE Communications Society William R. Bennett Prize in the Field of Communications Networking. Dr. Cho was selected for the 2013 Presidential Early Career Award for Scientists and Engineers (PECASE), which is the highest honor bestowed by the US government on outstanding scientists and engineers in the early stages of their independent research careers. She is a senior member of the IEEE and a member of the ACM.



다음글  [IEEE/GIST EECS Seminar] 12/1(Fri.), 4:00 PM, Considerations for commercializing machine learning applications, Dr. Taesu Kim (Neosapience, Inc.)
이전글  [EECS Colloquium] 11/16(Thu.) 16:00, Imperceptible Robotics for Human, Prof. Kyung-In Jang (DGIST)

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