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Faculty Candidate: Xiaojing Liao

Georgia Tech
Tuesday, January 31, 2017, 4:00 pm

Xiaojing Liao
480 Dreese Labs
2015 Neil Avenue
Columbus, Ohio 43210
 

Evaluating Security Risks and Cyber Intelligence through Semantic-aware Inspection Techniques

The cyber threat landscape is quickly changing and it is of vital importance to stay updated and proactively work to improve security. At the same time, piecing together a complete landscape of attacks by identifying the strategies and capabilities of the adversaries requires establishing semantic links among individual observations. Also, defending these attacks require automatically generated semantics-aware policies to complement manual analysis. While semantic-aware inspection of security problem is a promising way to evaluate security risks and provide cyber intelligence, complicating the situation is the gap between security ontology and generic NLP primitives, which tend to be domain-sensitive, language-specific, and computationally intensive.

In this talk, I will explore how to develop a cyber-threat gathering system that takes advantage of semantic-aware inspection to extract cyber intelligence of newly-appearing online crime from online blogs. I'll then discuss how to model emerging and previously imperceptible online crimes from the extracted cyber intelligence via large-scale data analytics. Finally, I will present an efficient and accurate security system based on large-scale semantic processing of text content to defend against these online crimes.

Bio: Xiaojing Liao is a Ph.D. candidate in the School of Electrical and Computer Engineering at Georgia Tech and is a member of the Communications Assurance and Performance (CAP) group. She is advised by Raheem Beyah. Her research interests include web security, data analytics, as well as cyber-physical systems security and privacy. Her current research focuses on discover and understand critical security issues in a large system through data-oriented security analysis. 

Host: Alan Ritter