Dynamics of learning algorithms for the On-Demand Secure Byzantine Routing protocol

Abstract

We investigate the performance of of several protocol enhancements to the On-Demand Secure Byzantine Routing (ODSBR) [3] protocol in the presence of various Byzantine Attack models. These enhancements include a) modifications to the packet flow rates, b) a network layer retransmission capability and c) Nodal Weighting (in addition to Link Weighting) in the reputation database. These enhancements are meant to improve the learning rate of the protocol. The attack models investigated include previously investigated models [4] and a new and effective attack model, termed the MAC-Level Attack. We investigate the protocol enhancements through analytic models and simulation studies. We find that the protocol enhancements improve the learning times of the ODSBR protocol. The Nodal Weighting enhancement specifically helps in the presence of the various colluding Byzantine Attack models investigated. © 2006 Springer-Verlag Berlin Heidelberg.