Abstract:In this paper, we present a signaling design for secure integrated sensing and communication (ISAC) systems comprising a dual-functional multi-input multi-output (MIMO) base station (BS) that simultaneously communicates with multiple users while detecting targets present in their vicinity, which are regarded as potential eavesdroppers. In particular, assuming that the distribution of each parameter to be estimated is known \textit{a priori}, we focus on optimizing the targets' sensing performance. To this end, we derive and minimize the Bayesian Cram\'er-Rao bound (BCRB), while ensuring certain communication quality of service (QoS) by exploiting constructive interference (CI). The latter scheme enforces that the received signals at the eavesdropping targets fall into the destructive region of the signal constellation, to deteriorate their decoding probability, thus enhancing the ISAC's system physical-layer security (PLS) capability. To tackle the nonconvexity of the formulated problem, a tailored successive convex approximation method is proposed for its efficient solution. Our extensive numerical results verify the effectiveness of the proposed secure ISAC design showing that the proposed algorithm outperforms block-level precoding techniques.
Abstract:In this paper, we investigate the sensing-aided physical layer security (PLS) towards Integrated Sensing and Communication (ISAC) systems. A well-known limitation of PLS is the need to have information about potential eavesdroppers (Eves). The sensing functionality of ISAC offers an enabling role here, by estimating the directions of potential Eves to inform PLS. In our approach, the ISAC base station (BS) firstly emits an omni-directional waveform to search for potential Eves' directions by employing the combined Capon and approximate maximum likelihood (CAML) technique. Using the resulting information about potential Eves, we formulate secrecy rate expressions, that are a function of the Eves' estimation accuracy. We then formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the CRB with the aid of the artificial noise (AN), and minimize the CRB of targets'/Eves' estimation. By taking the possible estimation errors into account, we enforce a beampattern constraint with a wide main beam covering all possible directions of Eves. This implicates that security needs to be enforced in all these directions. By improving estimation accuracy, the sensing and security functionalities provide mutual benefits, resulting in improvement of the mutual performances with every iteration of the optimization, until convergence. Our results avail of these mutual benefits and reveal the usefulness of sensing as an enabler for practical PLS.
Abstract:Integrated sensing and communication (ISAC) has recently emerged as a candidate 6G technology, aiming to unify the two key operations of the future network in spectrum/energy/cost efficient way. ISAC involves communicating information to receivers and simultaneously sensing targets, while both operations use the same waveforms, the same transmitter and ultimately the same network infrastructure. Nevertheless, the inclusion of information signalling into the probing waveform for target sensing raises unique and difficult challenges from the perspective of information security. At the same time, the sensing capability incorporated in the ISAC transmission offers unique opportunities to design secure ISAC techniques. This overview paper discusses these unique challenges and opportunities for the next generation of ISAC networks. We first briefly discuss the fundamentals of waveform design for sensing and communication. Then, we detail the challenges and contradictory objectives involved in securing ISAC transmission, along with state-of-the-art approaches to address them. We then identify the new opportunity of using the sensing capability to obtain knowledge of the targets, as an enabling approach against known weaknesses of PHY security. Finally, we illustrate a low-cost secure ISAC architecture, followed by a series of open research topics. This family of sensing-aided secure ISAC techniques brings a new insight on providing information security, with an eye on robust and hardware-constrained designs tailored for low-cost ISAC devices.
Abstract:We study security solutions for dual-functional radar communication (DFRC) systems, which detect the radar target and communicate with downlink cellular users in millimeter-wave (mmWave) wireless networks simultaneously. Uniquely for such scenarios, the radar target is regarded as a potential eavesdropper which might surveil the information sent from the base station (BS) to communication users (CUs), that is carried by the radar probing signal. Transmit waveform and receive beamforming are jointly designed to maximize the signal-to-interference-plus-noise ratio (SINR) of the radar under the security and power budget constraints. We apply a Directional Modulation (DM) approach to exploit constructive interference (CI), where the known multiuser interference (MUI) can be exploited as a source of useful signal. Moreover, to further deteriorate the eavesdropping signal at the radar target, we utilize destructive interference (DI) by pushing the received symbols at the target towards the destructive region of the signal constellation. Our numerical results verify the effectiveness of the proposed design showing a secure transmission with enhanced performance against benchmark DFRC techniques.
Abstract:This paper addresses the problem that designing the transmit waveform and receive beamformer aims to maximize the receive radar SINR for secure dual-functional radar-communication (DFRC) systems, where the undesired multi-user interference (MUI) is transformed to useful power. In this system, the DFRC base station (BS) serves communication users (CUs) and detects the target simultaneously, where the radar target is regarded to be malicious since it might eavesdrop the transmitted information from BS to CUs. Inspired by the constructive interference (CI) approach, the phases of received signals at CUs are rotated into the relaxed decision region, and the undesired MUI is designed to contribute in useful power. Then, the convex approximation method (SCA) is adopted to tackle the optimization problem. Finally, numerical results are given to validate the effectiveness of the proposed method, which shows that it is viable to ensure the communication data secure adopting the techniques that we propose.