February 16, 2016, meetup wrap-up

We had a wonderful meetup this past Tuesday. Csilla Farkas came and gave an awesome presentation on data analytics and privacy. One of the things to come out of the presentation was Latanya Sweeney's work:

Abstract

Alice goes to the hospital in the United States. Her doctor and health insurance company know the details ― and often, so does her state government. Thirty-three of the states that know those details do not keep the information to themselves or limit their sharing to researchers [1]. Instead, they give away or sell a version of this information, and often they’re legally required to do so. The states turn to you as a computer scientist, IT specialist, policy expert, consultant, or privacy officer and ask, are the data anonymous? Can anyone be identified? Chances are you have no idea whether real-world risks exist. Here is how I matched patient names to publicly available health data sold by Washington State, and how the state responded. Doing this kind of experiment helps improve data-sharing practices, reduce privacy risks, and encourage the development of better technological solutions.

There's not really much to report. I will have some pictures up in the gallery soon. It was a really fun night with a really good talk.

Recording of the meetup:

February 16, 2016, meetup agenda - privacy and big data analytics

We are very excited to have Csilla Farkas an Associate Professor at the Department of Computer Science and Engineering and Director of the Center for Information Assurance Engineering at the Unviersity of South Carolina with as for our next meetup. She will be presenting on privacy issues in the context of big data analytics. An Abstract and more about Csilla can be found below.

Come out for a great talk, infosec fellowship, food, and adult beverages. We meet every third Tuesday at IT-ology at 6:15 p.m. Check out our directions page for how to get to IT-ology and the meeting room.

Abstract

This talk investigates the privacy issues in the context of big data analytics. The need to support data-driven decision making led to the development of sophisticated technologies to collect and analyze large data sets. However, this useful means of analyzing data comes at a cost: sensitive data may be disclosed and individuals' privacy may be violated.   Enterprises, organizations and government agencies collect and analyze vast amounts of data with and without the individuals' knowledge. Even if the raw data is properly sanitized, the result of the analysis may reveal information about specific individuals. Privacy preserving data mining methods have been developed to provide useful analytics without violating users' privacy.  However, these privacy preserving approaches are still limited with respect to the security problem when data mining results are combined with external knowledge to create security violations.  This talk shows some promising approaches that use semantic web technologies 1) to detect undesired inferences due to combining external knowledge with data mining results and 2) to enable individuals (data suppliers) to specify and evaluate privacy preferences in the context of big data analytics.

Bio

Csilla Farkas is an Associate Professor in the Department of Computer Science and Engineering and Director of the Center for Information Assurance Engineering at the University of South Carolina .  Dr. Farkas’ research interests include information security, data inference problem, financial and legal analysis of cyber crime, and security and privacy on the Semantic Web.  She is a recipient of the National Science Foundation Career award.  The topic of her award is “Semantic Web: Interoperation vs. Security – A New Paradigm of Confidentiality Threats.”  Dr. Farkas actively participates in international scientific communities as program committee member and reviewer.

Csilla Farkas received her PhD from George Mason University, Fairfax.  In her dissertation she studied the inference and aggregation problems in multilevel secure relational databases.  She received a MS in computer science from George Mason University and BS degrees in computer science and geology from SZAMALK, Hungary and Eotvos Lorand University, Hungary, respectively.