In this paper, we investigate unmanned aerial vehicle (UAV) assisted physical layer security in multi-beam satellite enabled vehicle communications. Particularly, the UAV is exploited as a relay to improve the secure satellite-to-vehicle link, and simultaneously serves as a jammer by deliberately generating artificial noise (AN) to confuse Eve. The satellite beamforming (BF) and UAV power allocation (PA) are jointly optimized to maximize the secrecy rate of the legitimate user within a target beam while guaranteeing the quality of service (QoS) of users within other beams. Since the problem is nonconvex, we first convert it into an equivalent two-stage problem. Then, the outer-stage problem is solved by using one-dimensional search, and the inner-stage problem is transformed to a bi-convex problem by using the semi-definite relaxation (SDR) and Charnes Cooper transformation. To solve the inner-stage bi-convex problem, we propose an iterative alternating optimization algorithm, where the optimal BF is obtained by semi-definite programming (SDP), and the optimal UAV PA is subsequently obtained by solving the reformulated fractional programming problem with an iterative Dinkelbach method. The tightness of SDR and the complexity of our proposed approach are analyzed, and extensive simulations are carried out to evaluate the effectiveness of our proposed approach.

In this paper, physical layer security in multi-antenna small-cell networks is investigated, where the multi-antenna base stations (BSs), cellular users, and eavesdroppers are all randomly distributed according to three independent Poisson point processes. To improve the secrecy performance, artificial noise (AN) aided transmission is adopted at each BS. Based on the stochastic geometry, we first derive the closed-form expressions of the connection and secrecy outage probabilities, and then comprehensively analyze the impact of different parameters through asymptotic analysis. It shows that in a low cell-load case, deploying more BSs will improve the connection and secrecy outage performance, and deploying more transmit antennas at each BS will only improve the connection outage performance. For a fixed-rate transmission, the condition under which AN becomes unnecessary is derived. We also derive a semi closed-form expression of the lower bound of the achievable average secrecy rate, which is numerically efficient to evaluate. Finally, we extend the study to a high cell-load case and adopt the zero-forcing beamforming scheme to support multi-user transmission. The connection and secrecy outage probabilities are also analyzed. Moreover, the optimal number of users maximizing the secrecy area spectral efficiency is discussed, and it is shown to be a fixed portion of the number of transmit antennas. Simulation results are presented to validate the theoretical analysis.

In the hierarchical control paradigm of a smart grid cyber-physical system, decentralized local agents (LAs) can potentially be compromised by opportunistic attackers to manipulate electricity prices for illicit financial gains. In this paper, to address such opportunistic attacks, we propose a Dirichlet-based detection scheme, where a Dirichlet-based probabilistic model is built to assess the reputation levels of LAs. Initial reputation levels of the LAs are first trained using the proposed model, based on their historical operating observations. An adaptive detection algorithm with reputation incentive mechanism is then employed to detect opportunistic attackers. We demonstrate the utility of our proposed scheme using data collected from the IEEE 39-bus power system with the PowerWorld simulator.