Dr. Bhavani Thuraisingham
Professor of Computer Science
Executive Director of Cyber Security Research and Education Institute
University of Texas at Dallas
Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. Distinguished Professor in the Erik Jonsson School of Engineering and Computer Science at the University of Texas, Dallas (UTD) and the Executive Director of UTD’s Cyber Security Research and Education Institute. She is also a visiting Senior Re-search Fellow at Kings College, University of London and a 2017-2018 Cyber Security Policy Fellow at the New America Foundation. Her research is on integrating Data Science and Cyber Security. Prior to joining UTD she worked at the MITRE Corporation for 16 years including a three-year stint as a Program Director at the NSF where she managed the Information Management and Analytics area and was part of the Cyber Trust theme. She was also a Department Head in Information and Data Management at MITRE. Prior to MITRE, she worked for the commercial industry for six years including at Honeywell. She is the recipient of numerous awards including the IEEE CS 1997 Technical Achievement Award, the ACM SIGSAC 2010 Outstanding Contributions Award, 2013 IBM Faculty Award, 2017 ACM CODASPY Research Award, and 2017 IEEE CS Services Computing Technical Committee Research Innovation Award. She is a 2003 Fellow of the IEEE and the AAAS and a 2005 Fellow of the British Computer Society. She has published over 120 journal articles, 250 conference papers, and 15 books, has delivered over 130 keynote addresses, and is the inventor of five patents in data analytics and secure data management. She co-chaired the Women in Cyber Security conference (WiCyS) in 2016 as well as the 2017 IEEE ICDE Workshop on Women in Data Science and Engineering. She is serving as the Co-Program Chair of the 2018 IEEE Conference on Data Mining.
"Integrating Data Science and Cyber Security"
The collection, storage, manipulation, analysis and retention of massive amounts of data have resulted in serious security and privacy considerations. Various regulations are being proposed to handle big data so that the privacy of the individuals is not violated. For example, even if personally identifiable information is removed from the data, when data is combined with other data, an individual can be identified. While collecting massive amounts of data causes security and privacy concerns, big data analytics applications in cyber security is exploding. For example, an organization can outsource activities such as identity management, intrusion detection and malware analysis to the cloud. The question is, how can the developments in data science techniques be used to solve security problems? Furthermore, how can we ensure that such techniques are secure and adapt to adversarial attacks? This presentation will first describe our research in data science including in stream data analytics and novel class detection and discuss its applications to insider threat detection. Second, it will discuss the emerging research area of adversarial machine learning. Finally, it will discuss why women should pursue careers in data science.