Kargupta and Co-authors win IEEE 10-Year Highest-Impact Paper Award
Columbia, MD, December 19, 2012
We are pleased to announce that Agnik's President, Dr. Hillol Kargupta received the 10-year Highest-Impact Paper Award from the 2012 IEEE International Data Mining Conference (ICDM) in Brussels, Belgium. Dr. Kargupta is also a Professor of Computer Science and Electrical Engineering, University of Maryland, Baltimore County. Privacy is an important issue in many mobile and distributed applications and algorithms for protecting privacy while being able to compute analytic from that data has strong impacts on many applications in the telematics, insurance, and consumer market, among others.
The
winning paper—“On the Privacy Preserving Properties
of Random Data Perturbation Techniques”—discusses
privacy-preserving data mining and it also received the 2003
ICDM Best Paper
Award. It is co-authored by former UMBC PhD student Souptik
Datta (CS '08)
and Dr. Kargupta’s colleagues at Washington State University—Qi
Wang and
Professor Krishnamoorthy Sivakumar.
Privacy Preserving Data Mining (PPDM) is important in many domains where the data is privacy sensitive and exposing the data to a third party for mining is not an option. Researchers have come up with many PPDM algorithms that attempt to protect data privacy while allowing analysis of the data for detecting patterns. Many of these algorithms make use of randomized techniques. This paper offers a perspective on the structure of random noise using theories of random matrices and their spectral properties in order to analyze their role in preserving data privacy while still keeping data patterns intact for analysis. It points out that spectral properties of random matrices can be exploited to create attacks on many commonly used privacy-preserving data mining algorithms.
Kargupta and his associates point out that you must be very careful when using random noise to protect data, since it can be easily filtered out. “Random noise is really not that unpredictable,” explains Kargupta, since it has a pattern of its own.Out of all of the papers on data mining published within the last ten years, this year Dr. Kargupta’s paper was chosen by IEEE as the most impactful paper in its field.
About Agnik
Agnik is a data analytics company for distributed, mobile, and embedded environments. Agnik's core product offerings are in the area of vehicle performance data analytics. It offers MineFleet for commercial fleets, MineDrive for the usage-based insurance market, and Vyncs for the consumer market and MineCar for the car-repair market. Agnik's core analytic offerings span a wide spectrum including vehicle health, maintenance, driver behavior, emissions, location services among others. Agnik is a recipient of the 2010 Frost & Sullivan Enabling Technology of the Year Award and 2010 IEEE Top-10 Data Mining Case Studies Award. Agnik's technology is based on years of research by its co-founders in this area. Agniks president is an IEEE Fellow, winner of IBM Innovation Award, winner of National Science Foundation CAREER Award among others. For more information about Agnik, visit www.agnik.com.For Additional Information Contact:
Agnik, LLC
410-290-0864
info@agnik.com