Deep learning based game-theoretical approach to evade jamming attacks

Abstract

Software-defined radios (SDRs) with substantial cognitive (computing) and networking capabilities provide an opportunity for malicious individuals to jam the communications of other legitimate users. Channel hopping is a well known anti-jamming tactic used in order to evade jamming attacks. We model the interaction between a transmitter, who uses chaotic pseudo-random patterns for channel hopping, and a sophisticated jammer, who uses advanced machine learning algorithms to predict the transmitter’s frequency hopping patterns as a non-cooperative security game. We investigate the effectiveness of adversarial distortions in such a scenario to support the anti-jamming efforts by deceiving the j..