Efficient attack strategy for legitimate energy-powered eavesdropping in tactical cognitive radio networks

The cognitive radio network (CRN) is not only considered a useful medium for users, but it is also an environment vulnerable to proactive attackers. This paper studies an attack strategy for a legitimate energy-constrained eavesdropper (e.g., a government agency) to efficiently capture the suspicious wireless communications (i.e., an adversary communications link) in the physical layer of a CRN in tactical wireless networks. Since it is powered by an energy harvesting device, a full-duplex active eavesdropper constrained by a limited energy budget can simultaneously capture data and interfere with the suspicious cognitive transmissions to maximize the achievable wiretap rate while minimizing the suspicious transmission rate over a Rayleigh fading channel. The cognitive user operation is modeled in a time-slotted fashion. In this paper, we formulate the problem of maximizing a legitimate attack performance by adopting the framework of a partially observable Markov decision process. The decision is determined based on the remaining energy and a belief regarding the licensed channel activity in each time slot. Particularly, in each time slot, the eavesdropper can perform an optimal action based on two functional modes: (1) passive eavesdropping (overhearing data without jamming) or (2) active eavesdropping (overhearing data with the optimal amount of jamming energy) to maximize the long-term benefit. We illustrate the optimal policy and compare the performance of the proposed scheme with that of conventional schemes where the decision for the current time slot is only considered to maximize its immediate reward.