In this letter, we investigate the cooperative jamming decision problem among multiple jammers for physical layer security. We introduce the social tie concept to model the cooperative jammer's willingness to cooperate. We first formulate the problem as a social tie based cooperative jamming game. We establish the existence of a pure Nash equilibrium (NE) and then devise an algorithm to compute the desired NE which can achieve the minimum secrecy outage probability among all the NEs. Moreover, we derive an upper bound on the gap between the secrecy outage probability achieved at the best NE and the minimum secrecy outage probability achieved with all jammers participating. Numerical results validate our theoretical analysis.
In this letter, we investigate the cooperative jamming decision problem among multiple jammers for physical layer security. We introduce the social tie concept to model the cooperative jammer's willingness to cooperate. We first formulate the problem as a social tie based cooperative jamming game. We establish the existence of a pure Nash equilibrium (NE) and then devise an algorithm to compute the desired NE which can achieve the minimum secrecy outage probability among all the NEs. Moreover, we derive an upper bound on the gap between the secrecy outage probability achieved at the best NE and the minimum secrecy outage probability achieved with all jammers participating. Numerical results validate our theoretical analysis.
Cooperative jamming is a popular technique for physical layer security, which is helpful to increase the secrecy of communication networks. To enhance the performance of cooperative jamming, this paper proposed a two-layer network consisting of a social network and a physical communication network. Each user is in the social network and their willingness of providing jamming is modeled by a susceptible-infective-recovery(SIR) spreading model, while devices of each user and their connection are presented in the physical communication network as the lower layer. The concept of social tie is introduced to the description of connections between two layers, and game theory is used to model processes of cooperative jamming. It is discovered that stronger social tie and SIR model is helpful to decrease secrecy outage probability of communication networks. Furthermore, our proposed two-layer network can raise the efficiency of designing strategies for cooperative jamming. Simulation results also demonstrate the proposed model and algorithms successfully enhance the secrecy performance for communication networks.
This paper studies the secrecy rate maximization problem of a secure wireless communication system in the presence of multiple eavesdroppers. The security of the communication link is enhanced through cooperative jamming with the help of multiple jammers. First, a feasibility condition is derived to achieve a positive secrecy rate at the destination. Then, we solve the original secrecy rate maximization problem, which is not convex in terms of power allocation at the jammers. To circumvent this nonconvexity, the achievable secrecy rate is approximated for a given power allocation at the jammers, and the approximated problem is formulated into a geometric programming one. Based on this approximation, an iterative algorithm has been developed to obtain the optimal power allocation at the jammers. Next, we provide a bisection approach, based on 1-D search, to validate the optimality of the proposed algorithm. In addition, by assuming Rayleigh fading, the secrecy outage probability (SOP) of the proposed cooperative jamming scheme is analyzed. More specifically, a single-integral form expression for the SOP is derived for the most general case, as well as a closed-form expression for the special case of two cooperative jammers and one eavesdropper. Simulation results have been provided to validate the convergence and the optimality of the proposed algorithm, as well as the theoretical derivations of the presented SOP analysis.
Internet of Things (IoT) is becoming an emerging paradigm to achieve ubiquitous connectivity, via massive deployment of physical objects, such as sensors, controllers, and actuators. However, concerns on the IoT security are raised due to the wireless broadcasting nature and the energy constraint of the physical objects. In this paper, we study secure downlink transmission from a controller to an actuator, with the help of a cooperative jammer to fight against multiple passive and noncolluding eavesdroppers. In addition to artificial noise aided secrecy beamforming for secure transmission, cooperative jamming (CJ) is explored to further enhance physical layer security. In particular, we provide a secrecy enhancing transmit design to minimize the secrecy outage probability (SOP), subject to a minimum requirement on the secrecy rate. Based on a strict mathematical analysis, we further characterize the impacts of the main channel quality and the minimum secrecy rate on transmit designs. Numerical results confirm that our design can enhance both security (in terms of SOP) and power efficiency as compared with the approach without CJ.
A wireless communication aided with Cooperative Jamming in order to enhance Physical Layer security is modeled with Game Theory, using Secrecy Capacity as payment function. To completely take in account the inherent randomness of the wireless channel, a Second Order Cone Programming deterministic equivalent is derived from the game resulting probabilistic optimization problem. Results show how upper and lower bounds of the secrecy capacity, associated to the game values, can be used to characterize the system. Suggested mixed strategies are implemented and compared with pure strategies, and it's shown that performance of mixed strategies, in terms of outage probability, lays exactly between the performances of pure strategies.
The broadcast nature of wireless communication makes it vulnerable to Eavesdropping. To enhance the communication security, cooperative jamming (CJ) is applied and studied in many previous works. However, jamming signal may also decrease the signal-to noise ratio (SNR) of legal receivers, and degrade the overall performance of networks. Therefore, the jammer power must be reasonably controlled. In this paper, the jamming power control over two-user Gaussian interference wiretap channel is investigated. We aim to establish the optimal scheme for each communication pair with game theory. To maximize secrecy rate with minimal jamming power, we first derive the pure and mixed strategies Nash Equilibrium (NE) in non-cooperative game frame. Then given the overall utility and fairness, we establish a cooperative game. In cooperative game frame, time-sharing mechanism is used. In both frames, we derive best equilibrium strategy for each transmitter. Numerical results demonstrate that the system utility is really improved with jamming power control based on game theory.
We have proposed and analyzed secrecy performance of a network architecture which contains a source, two destinations, a friendly jammer (FJ) and an eavesdropper (Eve). To jam the Eve in order to secure the confidential information of both users, the FJ sends a jamming signal while the source sends the combined information signal using non-orthogonal multiple access (NOMA) technique to both the users. A known jamming is considered which is known by both the users. Both the users subtract the known jamming from the received signal and then decode the information signal as per the NOMA technique. We analyzed the physical layer security of the network in terms of the secrecy outage probability (SOP) where the two users have different target secrecy rates. A closed form expression of the SOP is developed. We have analyzed the SOP under the impact of several numerical parameters such as: source transmit signal to noise ratio (SNR), FJ transmit SNR, fraction of source transmit power, and different target secrecy rates. For a fixed transmit SNR of the FJ, we obtain an optimal value of the source transmit SNR at which SOP is minimized. These analyzed results are also supported by the MATLAB based simulation results.