Title of Thesis: On Random Additive Perturbation for Privacy Preserving Data Mining Author: Souptik Datta, Master of Science, 2004 Thesis directed by: Dr. Hillol Kargupta, Associate Professor Department of Computer Science and Electrical Engineering Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving...

My prior research has been mainly in the area of privacy preserving data mining. It included such topics as: using randomization for preserving privacy of individual transactions in association rule mining; secure two-party computation of joins between two relational tables, set intersections, join sizes, and supports of vertically partitioned itemsets; improving space and time efficiency in pr...

The aim of privacy preserving data mining (PPDM) algorithms is to extract relevant knowledge from large amounts of data while protecting at the same time sensitive information. An important aspect in the design of such algorithms is the identification of suitable evaluation criteria and the development of related benchmarks. Recent research in the area has devoted much effort to determine a tra...

Privacy preserving mining of distributed data has numerous applications. Each application poses different constraints: What is meant by privacy, what are the desired results, how is the data distributed, what are the constraints on collaboration and cooperative computing, etc. We suggest that the solution to this is a toolkit of components that can be combined for specific privacy-preserving da...

Privacy is an important issue in Data mining. The privacy field has seen speedy advances in current years because ability to store data has increased. Precisely, current advances in the data mining field have led to increased concerns about privacy. Privacy-preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. . Many met...

Wireless sensor networks have been widely deployed in many social settings to monitor human activities and urban environment. In these contexts, they acquire and collect sensory data, and collaboratively fuse the data. Due to resource constraint, sensor nodes however cannot perform complex data processing. Hence, cloud-integrated sensor networks have been proposed to leverage the cloud computin...

Real world healthcare systems are generally large and overly complex systems. Designing privacy-friendly protocols for such systems is a challenging task. In this paper we present a privacy-preserving protocol for the Belgian healthcare system. The proposed protocol protects the patients’ privacy throughout the prescription handling process, while complying with most aspects of the current Belg...

Security and Privacy are among the most important concerns in Vehicular Ad-hoc Networks (VANET). Widely accepted privacy preserving communication scheme in VANETcommunity -that is using pseudonyms –has left open doors for some security problems such as Sybil attack. In this paper, we have proposed an efficient approach detecting this attack while preserving privacy of vehicles in the network.

Big data has been arising a growing interest in both scien- tific and industrial fields for its potential value. However, before employing big data technology into massive appli- cations, a basic but also principle topic should be investigated: security and privacy. One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. Many or...