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Asilomar Conference on Signals, Systems and Computers (ACSSC)

A full-duplex active eavesdropper in mimo wiretap channels: Construction and countermeasures

Amitav Mukherjee, Arnold Lee Swindlehurst

Published Nov 1, 2011• 73 citations
Publisher

Abstract

We examine the design of a full-duplex active eaves-dropper in the 3-user MIMOME wiretap channel, where all nodes are equipped with multiple antennas. The adversary intends to optimize its transmit and receive sub-arrays and jamming signal parameters so as to minimize the MIMO secrecy rate of the main channel. The full-duplex operating mode of the adversary induces self-interference at its receive sub-array, which is factored into the adversary's optimization. We characterize the worst-case jamming covariance for arbitrary and Gaussian input signaling, and develop a numerical algorithm to compute the same. We then examine sub-optimal active eavesdropping schemes that comprise essentially an antenna subset selection problem for the adversary, followed by a brief discussion of a potential countermeasure where the transmitter allocates some of its spatial dimensions for jamming the eavesdropper. Numerical results are presented to verify the efficacy of the proposed adversarial optimization algorithms.

DOI
10.1109/acssc.2011.6189999

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We examine the design of a full-duplex active eaves-dropper in the 3-user MIMOME wiretap channel, where all nodes are equipped with multiple antennas. The adversary intends to optimize its transmit and receive sub-arrays and jamming signal parameters so as to minimize the MIMO secrecy rate of the main channel. The full-duplex operating mode of the adversary induces self-interference at its receive sub-array, which is factored into the adversary's optimization. We characterize the worst-case jamming covariance for arbitrary and Gaussian input signaling, and develop a numerical algorithm to compute the same. We then examine sub-optimal active eavesdropping schemes that comprise essentially an antenna subset selection problem for the adversary, followed by a brief discussion of a potential countermeasure where the transmitter allocates some of its spatial dimensions for jamming the eavesdropper. Numerical results are presented to verify the efficacy of the proposed adversarial optimization algorithms.
This paper investigates reliable and covert transmission strategies in a multiple-input multiple-output (MIMO) wiretap channel with a transmitter, receiver and an adversarial wiretapper, each equipped with multiple antennas. In a departure from existing work, the wiretapper possesses a novel capability to act either as a passive eavesdropper or as an active jammer, under a half-duplex constraint. The transmitter therefore faces a choice between allocating all of its power for data, or broadcasting artificial interference along with the information signal in an attempt to jam the eavesdropper (assuming its instantaneous channel state is unknown). To examine the resulting trade-offs for the legitimate transmitter and the adversary, we model their interactions as a two-person zero-sum game with the ergodic MIMO secrecy rate as the payoff function. We first examine conditions for the existence of pure-strategy Nash equilibria (NE) and the structure of mixed-strategy NE for the strategic form of the game. We then derive equilibrium strategies for the extensive form of the game where players move sequentially under scenarios of perfect and imperfect information. Finally, numerical simulations are presented to examine the equilibrium outcomes of the various scenarios considered.
This paper investigates transmission strategies in a MIMO wiretap channel with a transmitter, receiver and wiretapper, each equipped with multiple antennas. In a departure from existing work, the wiretapper is able to act either as a passive eavesdropper or as an active jammer per channel use, under a half-duplex constraint. The transmitter therefore faces a choice between dynamically allocating all of its power for data; or broadcasting artificial noise along with the information signal in order to selectively degrade the eavesdropper's channel. We model the network as a zero-sum game in strategic form with the MIMO secrecy rate as the payoff function. We first carry out a detailed analysis of the various rate outcomes that result from the possible actions of the agents. We then discuss the conditions for equilibrium outcomes in the strategic form of the game. Finally, numerical simulations are presented to corroborate the analytical results.
In this paper, secure communication over a multi-input multi-output multi-eavesdropper (MIMÓME) wiretap channel is considered. We propose an enhanced MIMÓME artificial noise (AN) model in which the receiver (Bob) adopts the latest Full-Duplex MIMO Radio technique to emit AN jointly with the transmitter (Alice). An achievable secrecy rate is obtained for this model over an unfavorable noiseless eavesdropping channel. Optimization problem is formulated to solve the beamforming and power allocation for Alice and Bob's transmitting signals and to determine the dimension allocation between the information and AN signals. Simulations are carried out to illustrate the optimization process, and the results show that the enhanced MIMÓME model outperforms existing AN models for low self-interference regime.
Full-duplex (FD) jamming transceivers recently have been shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this paper, we investigate whether FD jamming can also improve the system's secrecy energy efficiency (SEE) in terms of securely communicated bits per Joule when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high signal-to-noise ratio (SNR), or for a bidirectional FD communication setup.
Owing to the openness of wireless channels, ensuring the security of communication for massive multiple-input multiple-output (MIMO) systems faces severe challenges. For the massive MIMO system in the presence of a full-duplex (FD) multi-antenna eavesdropper, a dual artificial-noise (AN) injection scheme is proposed to enhance communication security in this paper. Specifically, AN is superimposed onto the transmitted pilot signals to interfere with the eavesdropper from estimating the legitimate user channel in pilot training phases. In the phase of data transmission, the AN generated in the null space of the legitimate user is introduced to prevent the eavesdropper from receiving the confidential messages. Meanwhile, an iterative optimization algorithm is presented to obtain the optimal power allocation between the information-bearing signals and the AN for the potential countermeasures taken by the eavesdropper. Numerical results are presented to validate the superior performance of the proposed scheme in security ensurance compared to the conventional ones with AN injection schemes.
This paper considers a scenario in which an Alice-Bob pair wishes to communicate in secret in the presence of an active Eve, who is capable of jamming as well as eavesdropping and operates in full-duplex (FD) mode. As countermeasure, Bob operates in FD mode, using a subset of its antennas to receive, and the remaining antennas to transmit jamming noise. Alice and Bob employ linear precoding, and all nodes use Gaussian code books. In that context, our goal is to maximize the achievable secrecy degrees of freedom (S.D.o.F.) of the system. We provide the optimal receive/transmit antennas allocation at Bob, based on which we determine in closed form the maximum achievable S.D.o.F. We also provide a method for constructing the precoding matrices of Alice and Bob, based on which the maximum S.D.o.F. can be achieved. We further investigate the adverse scenario in which Eve knows Bob's transmission strategy and optimizes its transmit/receive antennas allocation in order to minimize the achievable S.D.o.F. For that case, we find the worst case achievable S.D.o.F. Numerical results validate the theoretical findings and demonstrate the performance of the proposed method.