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Optimal Unconditionally Secure ID-Based Key Distribution Scheme for Large-Scaled Networks
Goichiro HANAOKA Tsuyoshi NISHIOKA Yuliang ZHENG Hideki IMAI
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E84-A
No.1
pp.222-230 Publication Date: 2001/01/01 Online ISSN:
DOI: Print ISSN: 0916-8508 Type of Manuscript: Special Section PAPER (Special Section on Cryptography and Information Security) Category: Keyword: key predistribution system, ID-based cryptosystem, collusion attack,
Full Text: PDF(299.1KB)>>
Summary:
Efficient ID-based key sharing schemes are desired worldwide in order to obtain secure communications on the Internet and other related networks, and Key Pre-distribution System (KPS) is one of the majority of such key sharing schemes. The remarkable property of KPS, is that, user need only input the partner's identifier to the secret KPS-algorithm in order to share a key between them. Although this is just a small part of many advantages KPS has in terms of efficiency, an enormous amount of memory is always required to achieve perfect security. While the conventional KPS methods can establish communication links between any pair of entities in a communication system, in most of the practical communication environment, such as in a broadcast system, not all links will be required. In this article, we achieved a desirable method to remove the unnecessary communication links between any pair of entities in a communication system. In our scheme, required memory size per entity was just proportional to the number of entities of the partner's, while that in conventional KPS, it is proportional to the number of entities of the whole communication system. As an example, if an entity communicates with only 1/r others, the memory requirement is reduced to 1/r of the conventional KPS's. Furthermore, it was proven that the obtained memory size was optimum. Overall, our scheme confirmed greater efficiency to achieve secure communication particularly suited in large-scale networks.
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