Big Data, Security and Privacy

Prof. Bhavani Thuraisingham, University of Texas at Dallas
11:00-12:00 Wednesday, 16 May 2018, ITE 459, UMBC

The collection, storage, manipulation 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. This is essentially the inference and aggregation problem that data security researchers have been exploring for the past four decades. This problem is exacerbated with the management of big data as different sources of data now exist that are related to various individuals.

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, email filtering and intrusion detection to the cloud. This is because massive amounts of data are being collected for such applications and this data has to be analyzed. The question is, how can the developments in big data management and analytics techniques be used to solve security problems? These problems include malware detection, insider threat detection, and intrusion detection.

To address the challenges of big data security and privacy as well as big data analytics for cyber security applications, we organized a workshop sponsored by the National Science Foundation in September 2014 and presented the results in 2015 at an inter-agency workshop in Washington DC. Since then several developments have been reported on big data security and privacy as well as on big data analytics of cyber security. This presenting will summarize the findings of the workshop and discuss the developments and directions.

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 at Dallas (UTD) and the Executive Director of UTD’s Cyber Security Research and Education Institute since October 2004. She is also a Senior Research Fellow at Kings College, University of London (2015-2018) and a New America Cyber Security Policy Fellow (2017-2018). Her current research is on integrating cyber security and data science. 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. She initiated the Data and Applications Security program at NSF and was a member of the Cyber Trust theme. While at MITRE she was a department head and was also a technical advisor to the DoD, the NSA, the CIA, and the IRS. Prior to that, she worked for the commercial industry for six years including at Honeywell, Inc. She is the recipient of numerous awards including the IEEE CS 1997 Technical Achievement Award, the IEEE ISI 2010 Research Leadership Award, ACM SIGSAC 2010 Outstanding Contributions Award, SDPS 2012 Transformative Achievement Gold Medal, 2013 IBM Faculty Award, ACM CODASPY 2017 Innovative and Lasting Research Contributions Award, IEEE CS Services Computing 2017 Research Innovation Award, and Dallas Business Journal 2017 Women in Technology 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, 15 books, has delivered over 130 keynote and featured addresses, and is the inventor of six US patents. She has chaired/co-chaired top tier conferences including the Women in Cyber Security (WiCyS) 2016, ACM CCS 2017, and is serving as the Program co-Chair for IEEE ICDM 2018. She also delivered a featured address at the Women in Data Science (WiDS) conference in 2018. She received her PhD at the University of Wales, Swansea, UK, and the earned higher doctorate (D. Eng) from the University of Bristol, England, UK for her published research in secure data management.

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