To overcome signal blockage and extend coverage to both indoor and outdoor users, simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) are employed. In addition, Non-Orthogonal Multiple Access (NOMA) is integrated to improve spectral efficiency and support multiple-user access. Given this setup, it is essential to investigate the Physical Layer Security (PLS) performance of STAR-RIS-assisted NOMA systems, particularly with multiple eavesdroppers. To evaluate the signals’ interception risks, we derive closed-form expressions for the Secrecy Outage Probability (SOP) and the Intercept Probability (IP) for both system setups at the near users and colluding/non-colluding eavesdroppers.1

Unmanned aerial systems (UAS) and unmanned aerial vehicles (UAVs) have been utilized in numerous civilian and military applications. However, with the increasing deployment of UAS, several cybersecurity challenges have emerged, particularly vulnerabilities in GPS transmissions. GPS jamming attacks pose a significant threat to UAS, resulting in performance degradation and capability loss. To address this challenge, we propose a novel approach for detecting jamming attacks on GPS transmissions in UAS. The proposed approach combines Naive Bayes and Multi-Layer Perceptron algorithms to offer efficient and precise detection of GPS jamming attacks. We evaluated the proposed approach’s performance against various machine learning (ML) models using a synthetic dataset. The experimental results demonstrate the effectiveness of the proposed approach in detecting jamming attacks in GPS transmissions, achieving better accuracy than other ML models under several jammers. Index Terms---AI, ML, UAS/UAV, GPS Jamming Attacks.

Implantable medical devices (IMDs) necessitate secure and energy-efficient communication systems to safeguard patient data and maintain device functionality. In this paper, our primary focus is on examining the impact of varying channel models on the success of Physical Layer Key Generation (PLKG) for Implantable Medical Devices (IMDs), whilst also introducing an energy-aware approach. We utilize the unique properties of double$\kappa-\mu$Shadowed fading channels, a generalized model allowing us to cover a range of special cases, including Nakagami-m, Rician, and Rayleigh fading. We apply a moving average filter to improve the stability of received signal strength (RSS) measurements and employ an adaptive threshold for quantization. To reconcile the generated keys, we adapt the Cascade protocol, ensuring its lightweight operations. Energy awareness is a paramount feature in our PLKG system, achieved by limiting reconciliation attempts to prevent rapid battery depletion. Through rigorous simulations, we present a comprehensive analysis of the performance of our energy-aware PLKG system under various fading conditions

Non-orthogonal-multiple-access (NOMA) technique has been considered to fulfill the exponential increase in wireless devices, data traffic, and access demand. Still, NOMA-aided systems are subject to wireless attacks such as eavesdropping. As a solution to encounter such menace, physical layer security (PLS) has been widely adopted to protect the networks from an information theoretic perspective. In this paper, we analyze the PLS of a downlink NOMA-aided network while employing a decode-and-forward (DF) relaying system. We assume the generalized Fisher-Snedecor composite fading$\mathcal{F}$, wherein Nakagami-m, Rayleigh, and one-sided Gaussian are special cases. Under those assumptions, we derive the closed-form expressions of the outage probability (OP), ergodic capacity, average secrecy capacity (ASC), and upper bound approximations. Our results are validated with Monte Carlo simulations, where they indicated that the power allocation ratio in NOMA and the fading parameters have a major impact on the system's robustness against the eavesdropping attack.

In this paper, we aim at tackling the security performances of dual-hop mixed free-space optical (FSO)/radio frequency (RF) cooperative with the non-orthogonal multiple access (NOMA) technique. Particularly, we consider a downlink communication scenario, where a base station (BS) is commu-nicating with remote users in the existence of an eavesdropping attack. The hop from the BS to the relaying system is considered an FSO link, where the atmospheric turbulences are described by Málaga-$\mathcal{M}$. Besides, the RF links between the relay and users/attacker are assumed to follow the Double$\kappa-\mu$Shadowed fading since it unifies a wide set of special-case fading models. Moreover, we derive the closed-form expressions of the outage probability at the 1stlegitimate user and at the attacker, as well as the secrecy outage probability (SOP) in terms of the multivariate Fox-H function. Finally, we investigate the impact of the RF fading parameters, path-loss, power ratio, and pointing error on the secrecy performance.

Mixed radio frequency-free space optical (RF-FSO) systems are widely investigated and employed in network architectures due to their high data rate capabilities and large coverage areas. Although, the FSO beam is very sensitive to blockages such as building which leads to severe penetration loss. Thereby, in such case scenarios, it is more convenient to avoid the blockage by adding a third FSO hop to reach the destination and the signal pathway becomes a triple-hop RF-FSO-FSO system. Moreover, we need to have a more generalized RF fading model to obtain performance metrics that cover multiple signal propagation mediums. Inspired by that, we consider an uplink triple-hop RF-FSO-FSO communication scenario, where the RF link is modeled with the Double Shadowed$\kappa-\mu$fading while the FSO links are subject to Málaga-$\mathcal{M}$with pointing errors. Furthermore, we derive the closed-from expressions of the outage probability (OP) and the ergodic capacity in terms of the multivariate Fox-H function.

Wireless vehicular network (WVN) is exponentially gaining attention from industries and researchers since it is the keystone of intelligent transportation systems (ITS). Despite the sophisticated features and services that it can offer, it is susceptible to networking attacks such as eavesdropping threats where the confidential transmitted signal could be overheard by a malicious entity. In this paper, we intend to study the physical layer security (PLS) where we consider the eavesdropping attack for vehicle-to-infrastructure (V2I) communications. We analyze the average secrecy capacity, under different scenarios by comparing the performances of employing the decode-and-forward (DF) relay, the amplify-and-forward fixed gain (AFFG) relay, and the intelligent reflecting surface (IRS). Actually, this comparison investigates the efficiency of IRS comparing to the traditional relaying systems, since it was introduced as a novel paradigm in wireless technology with highly promising potential, especially in 5G and 6G.

The concept of intelligent transportation systems (ITS) is considered to be a highly promising area of research due to its diversity of unique features. It is based mainly on the wireless vehicular network (WVN), where vehicles can perform sophisticated services such as sharing real-time safety information. To ensure high-quality service, WVN needs to solve the security challenges like eavesdropping, where malicious entities try to intercept the confidential transmitted signal. In this paper, we are going to provide a security scheme under the Double kappa-mu Shadowed fading. Our solution is based on the use of a friendly jammer that will transmit an artificial noise (AN) to jam the attacker’s link and decrease its eavesdropping performances. To evaluate the efficiency of our solution, we investigated the outage probability for two special cases: Nakagami-m and Rician shadowed while taking into consideration the density of the blockage and the shadowing effects. We also studied the average secrecy capacity via deriving closed-form expressions of the ergodic capacity at the legitimate receiver and the attacker for the special case: Nakagami-m fading distribution.