Sushil Jajodia
George Mason University
670 Papers
9.5K Citations
Sushil Jajodia is an academic researcher from George Mason University. The author has contributed to research in topics: Computer science & Access control. The author has an hindex of 101, co-authored 664 publications. Previous affiliations of Sushil Jajodia include National Institute of Standards and Technology & United States Naval Research Laboratory.
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Papers
•Proceedings Article
Checking for k -anonymity violation by views
Chao Yao,X. Sean Wang,Sushil Jajodia +2 more
- 30 Aug 2005
TL;DR: This paper uses a formally-defined notion of k-anonymity to measure disclosure by views, where k >1 is a positive integer, and provides an efficient conservative algorithm that checks for necessary conditions for k-Anonymity violation.
Distributed algorithms for dynamic replication of data
Ouri Wolfson,Sushil Jajodia +1 more
- 01 Jul 1992
TL;DR: Two distributed algorithms for dynamic replication of a data-item in communication networks are presented, each of which continuously moves the replication scheme towards an optimal one, where optimality is defined with respect to different objective functions.
115
Fragmentation and encryption to enforce privacy in data storage
Valentina Ciriani,Sabrina De Capitani di Vimercati,Sara Foresti,Sushil Jajodia,Stefano Paraboschi,Pierangela Samarati +5 more
- 24 Sep 2007
TL;DR: The idea behind the approach is to use encryption as an underlying (conveniently available) measure for making data unintelligible, while exploiting fragmentation as a way to break sensitive associations between information.
Key management for multi-user encrypted databases
Ernesto Damiani,S. De Capitani di Vimercati,Sara Foresti,Sushil Jajodia,Stefano Paraboschi,Pierangela Samarati +5 more
- 11 Nov 2005
TL;DR: This paper presents the approach for the implementation of access control through selective encryption, and the presentation of the experimental results, which demonstrate the applicability of the proposal.
Localized Multicast: Efficient and Distributed Replica Detection in Large-Scale Sensor Networks
TL;DR: This paper presents a novel distributed approach called Localized Multicast for detecting node replication attacks and shows that it is more efficient in terms of communication and memory costs in large-scale sensor networks, and at the same time achieves a higher probability of detecting node replicas.
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