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IEEE Transactions on Green Communications and Networking

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

Guojie Hu, Jiangbo Si, Yunlong Cai, Naofal Al‐Dhahir

Published Dec 27, 2021• 4 citations
Publisher

Abstract

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.

DOI
10.1109/tgcn.2021.3138559

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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{N}Nbattery-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 randomK{K}KFBs, to deliberately increase the harvested energy of the correspondingK{K}KSTs; in phase 2, E overhears in the sameK{K}KFBs and jams in the remainingN  −  K{N}\,\,-\,\,{K}N−KFBs concurrently, to intentionally improve the interference levels of the SD in thoseN  −  K{N}\,\,-\,\,{K}N−KFBs. We prove that, givenK{K}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 unjammedK{K}KSTs 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, asK{K}Kincreases, 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 bothK{K}Kand 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.
This letter studies the proactive eavesdropping with one half-duplex legitimate monitor (E) over the wireless-powered multichannel suspicious system, where the suspicious transmitter (ST) proceeds energy harvesting from the power beacon and then communicates with the suspicious destination (SD) via N parallel channels. Under this setup, one jamming-assisted eavesdropping scheme is proposed to maximize the ergodic eavesdropping rate at E. Specifically, we first fix the number of jamming channels K at E, and then reveal that E should jam with maximum power over these K channels to force the ST to allocate more power over the other N - K channels, so as to maximally increase the perceived power at E over the corresponding N - K channels. Armed with this, to maximize the ergodic rate, the following work is only to find the optimal K with simple search. Moreover, one closed-form sub-optimal K is derived for practical implementation. Results present the great gain achieved by the proposed scheme compared to conventional passive eavesdropping and the effectiveness of the sub-optimal K.
This paper studies the proactive eavesdropping for the potential energy-constrained suspicious communication system with one full-duplex-enabled legitimate monitor. Specifically, for such a system, we consider the proactive eavesdropping over finite time blocks under the off-line framework. In each time block, the monitor first acts as the masked power beacon deliberately to proceed wireless energy transfer to the suspicious transmitter for its uplink data transmission, then adaptively executes jamming, passive eavesdropping or assisting strategy based on our provided exact channel condition with strict proofs. According to these adaptive strategies and considering the optimization of transmit power at the monitor, we aim to solve the problem of sum eavesdropping rates maximization over N (N ≥ 1 ) time blocks subject to limited power at the monitor, which is explained as a difficult mixed-inter nonlinear programming (MINLP) problem. Fortunately, it is shown that this MINLP problem can be divided into one jamming subproblem and one passive eavesdropping/assisting subproblem. To observe the achieve performance bound, we firstly exploit the exhaustive search based algorithm and block coordinate descent (BCD) based algorithm to solve these two subproblems, respectively. In addition, in order to decrease the time complexities, we further propose one jamming power efficiency sorting based heuristic algorithm and one signal-to-noise ratio (SNR) approximation based fast algorithm. Numerical results present the considerable gains brought from our proposed adaptive proactive eavesdropping strategy.
This letter studies the legitimate surveillance with one half-duplex legitimate monitor (E) over the suspicious multichannel relaying system, where the suspicious transmitter (ST) and relay (SR) implement the optimal power allocation over all orthogonal channels under a joint sum-power constraint to maximize the communication rate of the suspicious system. Under this setup and considering that SR operates in amplify-and-forward (AF) or decode-and-forward (DF) mode, E aims to i) determine the optimal set of sub-channels for jamming and ii) optimize its jamming power over these sub-channels in order to deliberately force ST and SR reallocating power to the unjammed sub-channels to the most, so as to increase the perceived power of E over the unjammed sub-channels and then maximize the eavesdropping rate. In particular, for the AF case, the formulated problem is non-convex, for which the slack variables are introduced and successive convex approximation is exploited. For the DF case, some insights are provided for the optimization process. Results present the considerable gain of the proposed strategy compared to intuitive schemes.
This letter studies proactive eavesdropping with one legitimate monitor (E) in the classical single-hop suspicious communication. Specifically, unlike all previous works that ignored the suspicious channel training phase and just considered the jamming power optimization of E in the suspicious data transmission phase to facilitate eavesdropping, this letter advances the research by comprehensively investigating the jamming power allocation of E in both phases, with the purpose of maximizing its eavesdropping success probability. Under this setup, we first derive an exact expression of the objective and reveal the existence of a fundamental trade-off in deciding the jamming power allocation, for which a simple one-dimensional search is employed to find the optimal solution. To simplify the analysis, we further derive a tight approximation of the objective and then develop a very fast alternating optimization algorithm to find the sub-optimal jamming power allocation. Moreover, we extend our analysis to the case where the channel state information is available at the suspicious transmitter via channel feedback. Simulation results demonstrate the effectiveness of our proposed scheme compared to competitive benchmarks.
We investigate proactive eavesdropping with one half-duplex legitimate monitor (E) in unmanned aerial vehicle (UAV)-enabled suspicious relaying systems, which consist of a suspicious transmitter (ST), a suspicious UAV-based relay (SU) and a suspicious destination (SD). Under this setup, we propose two jamming-assisted eavesdropping strategies, namely, “Eavesdrop-Then-Jam” (ETJ) and “Jam-Then-Eavesdrop” (JTE), to maximize the eavesdropping throughput of E. Specifically, for ETJ, E first eavesdrops the suspicious signal of the ST in the ST-SU phase and then jams the SD in the SU-SD phase; for JTE, E first jams the SU in the ST-SU phase and then eavesdrops the suspicious signal of the SU in the SU-SD phase.However, in both strategies, as the jamming power of E (independent variable) changes, the SU can also adaptively adjust its deployment (dependent variable) to maximize the benefit of the suspicious system. Facing this challenge, we can only employ the undesirable exhaustive search over both the independent and dependent variables to achieve the optimal solution. To decrease the complexity, we further derive a tight approximation of the Lambert function and then develop easy-to-implement algorithms to find the sub-optimal solutions. Numerical results demonstrate the effectiveness of our proposed strategies compared to conventional passive eavesdropping.
Short packet communications play key roles in the Internet-of-Things. Conventional Shannon’s coding theorem is not applicable for short packet communications, and the achievable rate in the finite blocklength regime is related to the blocklength and the decoding error probability. Contrary to conventional physical layer security, wireless information surveillance assumes that the communication users are suspicious users and the eavesdroppers are legitimate monitors, and proactive eavesdropping via jamming has been proposed to improve the eavesdropping performance. Existing works on proactive eavesdropping ignored the scenario when the suspicious users adopt the short packet communications. Thus, this paper tries to develop effective proactive eavesdropping schemes suitable for the short packet suspicious communications. Under the truncated channel inversion power allocation and the modified constant power allocation policies at the suspicious source, the problems of jamming power allocation for maximizing the monitoring success probability subject to the average transmit power constraint at the monitor are investigated. Based on the Dinkelbach-type algorithm, the Lagrange duality method and a novel tractable approximate expression for the decoding error probability, we derive suboptimal solutions to the problems. Simulation results demonstrate the effectiveness of the proposed solutions compared to various benchmark algorithms in existing literature.