Proactive Eavesdropping via Opportunistic Energy Transfer and Jamming for Wireless-Powered Suspicious Communication

This paper investigates the information surveillance with a half-duplex legitimate monitor (E) for wireless-powered suspicious communication in Internet of Things networks, which consists of one suspicious power-beacon (PB),
${N}$
battery-free suspicious transmitters (STs) operating in orthogonal frequency bands (FBs) and one suspicious destination (SD). The suspicious communication includes two phases: in phase 1, the PB chooses one best ST and exhausts its power over the corresponding FB for the energy transfer; in phase 2, by exploiting the harvested energy, such ST uploads its suspicious message to the SD. Under this setup, a novel proactive eavesdropping scheme is proposed to maximize the eavesdropping success probability at E. Specifically, in phase 1, E assists energy transfer in random
${K}$
FBs, to deliberately increase the harvested energy of the corresponding
${K}$
STs; in phase 2, E overhears in the same
${K}$
FBs and jams in the remaining
${N}\,\,-\,\,{K}$
FBs concurrently, to intentionally improve the interference levels of the SD in those
${N}\,\,-\,\,{K}$
FBs. We prove that, given
${K}$
, as E’s energy transfer power in phase 1 or jamming power in phase 2 increases: 1) the suspicious system will choose one of those unjammed
${K}$
STs for information uploading with a higher probability, thus increasing the conditional probability of E’s eavesdropping and 2) the ratio of the selected ST’s transmit power and communication rate will improve, thus enhancing the decoding success probability of E concurrently. In addition, given E’s transmit power in phases 1 and 2, as
${K}$
increases, the conclusion of i) still holds, but the conclusion of ii) reverses. Hence, to maximize the objective, which is the product of the conditional probability of eavesdropping and the decoding success probability, interestingly there exists a fundamental trade-off in deciding both
${K}$
and the power allocations in phases 1 and 2, and a simple search can be exploited to find the optimal solution. Numerical results show the effectiveness of our proposed scheme compared to competitive benchmarks.