Conference paper
Provably Secure Group Authentication in the Asynchronous Communication Model
Wuhan University of Technology1
Cyber Security, Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Guilin University of Electronic Technology3
University of Missouri at Kansas City4
Shaanxi Normal University5
Hubei University of Technology6
State Key Laboratory of Cryptology Science and Technology7
Fujian Normal University8
University of Wollongong9
Department of Applied Mathematics and Computer Science, Technical University of Denmark10
...and 0 moreAuthentication is one of the most fundamental services in information security. Compared with traditional authentication methods, group authentication enables a group of users to be authenticated at once rather than authenticating each user individually. Therefore, it is preferred in the group-oriented environment, such as multicast/conference communications.
While several group authentication schemes have been proposed over the past few years, no formal treatment for this cryptographic problem has ever been suggested. Existing papers only provide heuristic evidences of security and some of these schemes have later been found to be flawed. In this paper, we present a formal security model for this problem.
Our model not only captures the basic requirement in group authentication that an adversary cannot pretend to be a group member without being detected, but also considers some desirable features in real-world applications, such as re-use of the credentials in multiple authentication sessions and allowance for users to exchange messages through asynchronous networks.
We then introduce an efficient group authentication scheme where its security can be reduced to some well-studied complexity theoretic assumptions.
Language: | English |
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Publisher: | Springer |
Year: | 2020 |
Pages: | 324-340 |
Proceedings: | 21st International Conference on Information and Communications Security |
Series: | Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
ISBN: | 3030415783 , 3030415791 , 9783030415785 and 9783030415792 |
ISSN: | 03029743 |
Types: | Conference paper |
DOI: | 10.1007/978-3-030-41579-2_19 |
ORCIDs: | Meng, Weizhi |