Title :
Private and Secure Service Discovery via Progressive and Probabilistic Exposure
Author :
Zhu, Feng ; Zhu, Wei ; Mutka, Matt W. ; Ni, Lionel M.
Author_Institution :
Michigan State Univ., East Lansing
Abstract :
The involvement of only the necessary users and service providers for service discovery in pervasive computing environments is challenging. Without prudence, users´ and service providers´ requests or service information, their identities, and their presence information may be sacrificed. We identify that the problem may be as difficult as a chicken-and-egg problem, in which both users and service providers want the other parties to expose sensitive information first. In this paper, we propose a progressive and probabilistic approach to solve the problem. Users and service providers expose partial information in turn and avoid unnecessary exposure if there is any mismatch. Although 1 or 2 bits of information are exchanged in each message, we prove that the process converges and that the false-positive overhead decreases quickly. Experiments and hypothesis tests show that security properties hold. We implemented the approach and the performance measurements show that the approach runs efficiently on PDAs.
Keywords :
data privacy; message authentication; probability; ubiquitous computing; false-positive overhead; message authentication; pervasive computing environment; privacy; probabilistic approach; progressive approach; secure service discovery; service providers; Access protocols; Digital audio players; Information security; Measurement; Personal digital assistants; Pervasive computing; Privacy; Testing; Authentication; Pervasive Computing; Privacy; Probabilistic; Security;
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on
DOI :
10.1109/TPDS.2007.1075