NDLI: Session-wise private data exchange in eHealth peer-to-peer database management systems

Content Provider	IEEE Xplore Digital Library
Author	Rahman, S.M.M. Masud, M.M. Adams, C. Mouftah, H.T. Inomata, A.
Copyright Year	2011
Description	Author affiliation: Graduate School of Information Science, Nara Institute of Science and Technology, 630-0192 Japan (Inomata, A.) \|\| School of Information Technology and Engineering, University of Ottawa, ON, K1N 6N5 Canada (Rahman, S.M.M.; Adams, C.; Mouftah, H.T.) \|\| Computer Science Department, Taif University, Kingdom of Saudi Arabia (Masud, M.M.)
Abstract	In a peer-to-peer database management system(P2PDBMS) system, peers exchange data in a pair-wise fashion on-the-fly in response to a query without any centralized control. Generally, peers create a temporary session during data exchange. The data might be trapped and disclosed by the intruders while exchanged over an insecure communication network. As there is no centralized control for data exchange among peers, we cannot assume any central third party security infrastructure (e.g. PKI) to protect confidential data of an eHealth P2PDBMS. So far, there is currently no available/existing security protocol for secured data exchange in eHealth P2PDBMS. In this paper we propose a security protocol for data exchange in eHealth P2PDBMSs based on pairing-based cryptography and data exchange policy. The proposed protocol allows the peers to compute their secret session keys dynamically by computing pairing on elliptic curve based on the policies between them during data exchange. Our proposed protocol is robust against the man-in-the middle attack, the masquerade attack and the replay attack.
Starting Page	204
Ending Page	206
File Size	261964
Page Count	3
File Format	PDF
ISBN	9781457700828
e-ISBN	9781457700859
DOI	10.1109/ISI.2011.5984081
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Educational institutions Security
Content Type	Text
Resource Type	Article

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