Abstract
As knowledge based systems become more sophisticated, communications between systems or among their subsystems often conducted over public channels such as the Internet, wireless medium, etc. To secure communications over public channels, the most often used method is Diffie and Hellman’s public key infrastructure approach. This method requires a trusted third party to verify identifies, which does not play well with independent knowledge based systems, especially in the case of autonomous agents. In this paper, we proposes an asymptotic secrecy model to secure communications between and within knowledge based systems over public channels. The new model assumes that adversaries are storage space bounded, but not computationally bounded. At the initial phase of the secret communication, both parties exchange a large amount of random bits so that adversaries are not able to save all of them due to the storage space limitation. Each party only saves received data. At the second phase, each party regenerates the random bits, combines them with received data, and generates an encryption key iteratively with a one-way hash function. The key is then used to encrypt the future transmissions from one party to the other. After each transmission, the key is also updated iteratively based on data received. Finally, the proposed model is applied to solve some problems in wireless sensor networks as examples to show how the model can be applied for knowledge based systems in general.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Date
6-2007
Document Type
Article
Department, Program, or Center
Computer Science (GCCIS)
Recommended Citation
B. Yuan, Secure Communications with An Asymptotic Secrecy Model, Knowledge-Bsed systems (2007), doi: 10.1016/j.knosys.2007.01.006
Campus
RIT – Main Campus
Comments
This is the post-print of an article published by Elsevier. Copyright 2007 Elsevier B.V. The final, published version is located at: https://doi.org/10.1016/j.knosys.2007.01.006