Interference alignment (IA) networks seem secure, due to the fact that signals from the legitimate network may act as interference to disrupt the external eavesdropping. However, when some users inside the network are cooperating to eavesdrop one certain user, it will not be secure any longer. Thus, we concentrate on the eavesdropping attacks in this paper, and propose a novel collusive eavesdropping scheme (CES) in a K- user IA network, where one of the users is eavesdropped by an eavesdropper with the aid of the other (K - 2) cooperators. To perform the passive eavesdropping without being noticed by the targeted user, the precoding and decoding matrices of the eavesdropper and cooperators are re-designed, and some of the cooperators should sacrifice their own quality of transmission to help the eavesdropper meet the feasibility condition. Extensive simulation results are provided to show the eavesdropping effectiveness of the proposed CES in IA networks.
Interference alignment (IA) networks seem secure, due to the fact that signals from the legitimate network may act as interference to disrupt the external eavesdropping. However, when some users inside the network are cooperating to eavesdrop one certain user, it will not be secure any longer. Thus, we concentrate on the eavesdropping attacks in this paper, and propose a novel collusive eavesdropping scheme (CES) in a K- user IA network, where one of the users is eavesdropped by an eavesdropper with the aid of the other (K - 2) cooperators. To perform the passive eavesdropping without being noticed by the targeted user, the precoding and decoding matrices of the eavesdropper and cooperators are re-designed, and some of the cooperators should sacrifice their own quality of transmission to help the eavesdropper meet the feasibility condition. Extensive simulation results are provided to show the eavesdropping effectiveness of the proposed CES in IA networks.
Interference alignment (IA) can be secure due to the fact that the received signal of a targeted user at the eavesdropper may be embedded by interference from other concurrent users. However, when some malicious users inside the network cooperate to eavesdrop one specific user, the network will not be secure any more. Thus, we focus on eavesdropping attacks, and propose a novel collusive eavesdropping scheme (CES) in a K-user IA-based network. In this scheme, one user is eavesdropped on by an eavesdropper with the aid of the other (K - 2) users. To perform passive eavesdropping without being noticed by the targeted user, the precoding and decoding matrices of the eavesdropper and its cooperators are redesigned, and some of the cooperators sacrifice their own quality of transmission to help the eavesdropper meet the feasibility condition. Therefore, the feasibility condition of CES is derived, based on which the minimal number of low-quality cooperators and the maximal number of receiving antennas at each user are obtained. The received power of eavesdropping is analyzed with different numbers of antennas at each receiver, which also affects the eavesdropping performance. Extensive simulation results are provided to show the effectiveness of CES.
In interference alignment (IA)-based networks, interferences are constrained into certain subspaces at the unintended receivers, and the desired signal can be recovered free of interference. Due to the superposition of signals from legitimate users at the eavesdropper, the IA-based network seems to be more secure than conventional wireless networks. Nevertheless, when adequate antennas are equipped, the legitimate information can still be eavesdropped. In this paper, we analyze the performance of the external eavesdropper, and propose two anti-eavesdropping schemes for IA-based networks. When the channel state information (CSI) of eavesdropper is available, zero-forcing scheme can be utilized, in which the transmitted signals are zero-forced at the eavesdropper through the precoding of transmitters in IA-based networks. Furthermore, a more generalized artificial noise (AN) scheme is proposed for IA-based networks without the knowledge of eavesdropper's CSI. In this scheme, a single-stream AN is generated by each user, which will disrupt the eavesdropping without introducing any additional interference to the legitimate transmission of IA-based networks. In addition, the feasibility conditions, transmission rate, and eavesdropping rate are analyzed in detail, and an iterative algorithm to achieve the scheme is also designed. Extensive simulation results are provided to verify our analysis results and show the effectiveness of the proposed anti-eavesdropping schemes for IA-based networks.
In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of the average secrecy sum rate.
We investigate the physical layer security (PLS) in multi-user interference networks. In particular, we consider secure transmission from a legitimate source (Alice) to a legitimate destination (Bob), coexisting with multiple passive eavesdroppers (Eves), as well as multiple legitimate transceivers. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we propose an artificial noise (AN) assisted interference alignment (IA) for security enhancement. Unlike traditional IA based security approaches which may result in secret signal cancellation, we design a modified alternating minimization (AM) scheme to overcome this threat, by incorporating the max-eigenmode beamforming (MEB) for secure transmission. Moreover, by partitioning the IA equation into three independent subsets and their combinations, a much tighter necessary condition for IA feasibility is established. We also provide guiding insights into the practical system designs, including useful guidelines for the selection of the dimension of AN. Furthermore, the power allocation ratio between the secret signal and the AN signal is optimized to minimize the secrecy outage probability (SOP), subject to a minimum secrecy rate constraint. Numerical results demonstrate that our design can enhance both quality and security of the secret signal, and thus is suitable and reliable for PLS in interference networks.
This work addresses the security of a two-user broadcast channel. The challenge of protecting a broadcast channel is associated with the necessity of securing the system, not only against eavesdropping attacks originating from external nodes, but also to ensure that the inside users do not eavesdrop on each other’s information. To address this issue, the present work proposes a cooperative jamming scheme that provides protection against eavesdropping attacks carried out simultaneously by inside users and external eavesdroppers. To achieve this goal, the developed scheme combines real interference alignment with a blind cooperative jamming technique defined in the literature. An information theoretical analysis shows that positive secure degrees of freedom are achievable using the proposed solution.
This paper investigates physical layer security (PLS) in wireless interference networks. Specifically, we consider confidential transmission from a legitimate transmitter (Alice) to a legitimate receiver (Bob), in the presence of non-colluding passive eavesdroppers (Eves), as well as multiple legitimate transceivers. To mitigate interference at legitimate receivers and enhance PLS, artificial noise (AN) aided interference alignment (IA) is explored. However, the conventional leakage minimization (LM) based IA may exhibit confidential signal cancellation phenomenon. We theoretically analyze the cause and then establish a condition under which this phenomenon will occur almost surely. Moreover, we propose a means of avoiding this phenomenon by integrating the max-eigenmode beamforming (MEB) into the traditional LM based IA. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we derive a closed form expression for the secrecy outage probability (SOP), and establish a condition under which positive secrecy rate is achievable. To enhance security performance, an SOP constrained secrecy rate maximization (SRM) problem is formulated and an efficient numerical method is developed for the optimal solution. Numerical results demonstrate the effectiveness and the usefulness of the proposed approach.