[PAST EVENT] Toward Automatically Evaluating Security Risks and Providing Cyber Intelligence
The cyber threat landscape is quickly changing and it is of vital importance to stay abreast of emerging threats and to 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 against these attacks requires automatically generated semantics-aware policies to complement manual analysis. While using semantic-aware techniques to address security problems is a promising approach to evaluate security risks and to provide cyber intelligence, there exists a gap between the security ontology and generic NLP primitives needed for such an approach. This gap tends to be domain-sensitive, language-specific, and computationally intensive which further complicates the use of such an approach.
In this talk, I will discuss a cyber-threat gathering framework 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.
Xiaojing Liao is a Ph.D. candidate in the School of Electrical and Computer Engineering at Georgia Institute of Technology. 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. She received the best applied security research paper (the 3rd place) by CSAW. Her work has been published in top-tier security conferences as well as other top-tier computer science conferences.
Xu Liu 757-221-7739