H. Kargupta

Publications180
h-index44
Citations7,916
Highly Influential Citations350
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On the privacy preserving properties of random data perturbation techniques
TLDR
We present the theoretical foundation of this filtering method and extensive experimental results to demonstrate that in many cases random data distortion preserve very little data privacy. Expand
  • 710
  • 39
  • PDF
Random projection-based multiplicative data perturbation for privacy preserving distributed data mining
TLDR
This paper explores the possibility of using multiplicative random projection matrices for privacy preserving distributed data mining. Expand
  • 537
  • 32
  • PDF
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
  • 393
  • 17
In-Network Outlier Detection in Wireless Sensor Networks
TLDR
To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an algorithm that (1) is flexible with respect to the outlier definition, (2) works in-network with a communication load proportional to the outcome, and (3) reveals its outcome to all sensors. Expand
  • 237
  • 15
An Attacker's View of Distance Preserving Maps for Privacy Preserving Data Mining
TLDR
We examine the effectiveness of distance preserving transformations in privacy preserving data mining in the presence of two types of prior information regarding the original data. Expand
  • 150
  • 15
  • PDF
VEDAS: A Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring
  • 209
  • 14
Approximate Distributed K-Means Clustering over a Peer-to-Peer Network
TLDR
Data intensive peer-to-peer (P2P) networks are finding increasing number of applications. Expand
  • 134
  • 12
The Gene Expression Messy Genetic Algorithm
  • H. Kargupta
  • Mathematics, Computer Science
  • Proceedings of IEEE International Conference on…
  • 20 May 1996
TLDR
Introduces the Gene Expression Messy Genetic Algorithm (GEMGA)-a new generation of messy genetic algorithms that directly search for relations among the members of the search space. Expand
  • 185
  • 11
  • PDF
Distributed Data Mining in Peer-to-Peer Networks
TLDR
This paper presents an exposure to P2P distributed data mining technology and its applications in various domains such as file sharing, e-commerce, and social networking. Expand
  • 253
  • 10
  • PDF
Clustering distributed data streams in peer-to-peer environments
TLDR
This paper describes a technique for clustering homogeneously distributed data in a peer-to-peer environment like sensor networks. Expand
  • 183
  • 9
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