Oct 4, 2021 · In this work, we provide a machine-learning-based anti-jamming technique for CR networks to avoid a hostile jammer, where both the jamming and ...

Oct 14, 2021 · However, our major concern is to combat jamming attacks in cognitive radio networks. The model of a jammer in a CRN is shown in Fig. 1, where ...

In particular, Jamming is considered as one of the most challenging security threat in CR networks. In jamming, an attacker jams the communication by ...

The jammer could be an intelligent entity that is capable of exploiting the dynamics of the environment. In this work, we provide a machine-learning-based anti- ...

This work provides a machine-learning-based anti- jamming technique for CR networks to avoid a hostile jammer, where both the jamming and anti-jamming ...

Sep 17, 2024 · The proposed study introduces a novel anti-jamming approach for cognitive radio networks (CRNs) by integrating the Stackelberg game model with direct sequence ...

At each stage of the game, secondary users observe the spectrum availability, the channel quality, and the attackers' strategy from the status of jammed ...

Oct 22, 2024 · The antijamming methods in power domain are traditional techniques, and the anti-jamming mechanisms in spectrum domain are promising schemes. ..

This paper addresses the emerging threat issues posed by high-dynamic intelligent jamming and proposes an intelligent anti-jamming communication algorithm ...

This article designs Double Deep Q Network (Double DQN) to model the confrontation between the cognitive radio network and the jammer and proposes an ...