Artificial Neural Network based Byzantine Agreement Protocol

K.W. Lee and H.T. Ewe (Malaysia)


Artificial Neural Networks, ByzantineGenerals Problem, Fault Tolerance, Cryptography,Network Security.


Reliability of distributed computer systems and computer networks involves the fault-tolerant capability of handling malfunctioning components that give contradictory information to other units in the systems. A malicious environment consists of both loyal and faulty units. The problem of finding an algorithm to achieve consensus among all the loyal units in the network is called Byzantine Generals Problem (BGP), and the algorithm of solving BGP is known as Byzantine Agreement Protocol (BAP). A new approach to BGP using artificial neural networks (ANN) is recommended in [1,2]. In this paper, we propose an improved ANN based BAP. It shows better performance when the size of the network n ≥ 10. This ANN based BAP has several advantages over traditional BAP. The good points include (i) great reduction of memory space requirement; (ii) parallel processing ability of each node unit; (iii) repeatability of neural network learning capability to the dynamic Byzantine environment.

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