Multiple Eavesdroppers Research Articles

NOMA-Based Cognitive Satellite Terrestrial Relay Network: Secrecy Performance Under Channel Estimation Errors and Hardware Impairments

Nonorthogonal multiple access (NOMA) and cognitive integrated satellite terrestrial relay networks are the promising and key part for the next-generation wireless networks. This article researches the joint effects of channel estimation errors (CEEs) and hardware impairments on the secrecy performance of cognitive integrated satellite terrestrial relay networks. The noncolluding eavesdropping scheme is applied in the multiple eavesdroppers, where the eavesdropper with the highest eavesdropping capacity is selected to overhear the legitimate transmission signal. Moreover, the detailed analysis for the secrecy outage probability (SOP) is obtained based on the utilized partial terrestrial relay selection strategy. To obtain the insightful conclusions, the asymptotic analysis along with the secrecy coding gain and secrecy diversity order for the SOP are further derived, which gives the effective methods to valuate the impacts of CEEs and hardware impairments on the considered system with the NOMA scheme in high signal-to-noise ratio regime. Moreover, simulations are derived for the secrecy energy efficiency. Finally, Monte Carlo simulations are given to prove the correctness of the theoretical SOP analysis.

DeepAntiJam: Stackelberg Game-Oriented Secure Transmission via Deep Reinforcement Learning

In this letter, we present a novel deep reinforcement learning-assisted anti-jamming transmission scheme (DeepAntiJam) to guarantee reliable and creditable transmission in the presence of one smart jammer and multiple eavesdroppers. Specifically, we formulate secure transmission as a Stackelberg game in which the jammer, as the leader, adaptively adjusts its jamming power while the transmitter, as the follower, selects its transmit power and secrecy rate accordingly. Furthermore, the existence and uniqueness of Stackelberg equilibrium are proved. To achieve the Stackelberg equilibrium when the prior knowledge of jammer is unknown, DeepAntiJam is proposed to improve the secrecy throughput, where a solver neural network is utilized to determine the optimal transmission parameter according to the transmission strategy obtained by deep reinforcement learning. Moreover, transfer learning is introduced into the initialization of DeepAntiJam to avoid unnecessary initial random exploration. Simulation results validate that DeepAntiJam can enhance secrecy throughput significantly under the coexistence of smart jammer.

Security Outage Probability Analysis of Cognitive Networks With Multiple Eavesdroppers for Industrial Internet of Things

The Industrial Internet of Things (IIoT) has been recognised as having the potential to benefit a range of industrial sectors substantially. However, widespread development and deployment of IIoT systems are limited for some reasons, the most significant of which are a shortage of spectrum resources and network security issues. Given the heterogeneity of IIoT devices, typical cryptographic security techniques are insufficient since they can suffer from challenges including computation, storage, latency, and interoperability. This paper presents a physical layer security analysis of the underlying cognitive radio networks for IIoT. Through consideration of the spectrum, IIoT devices can opportunistically utilise the primary spectrum, thereby improving spectrum efficiency and allowing access by an increased number of devices. Specifically, we propose two cognitive relay transmission (CRT) schemes, optimal single CRT (O-SCRT) and multiple CRT (MCRT), to improve transmission reliability further. Since it is challenging to obtain channel state information in the wiretap link, we provide a sub-optimal single CRT scheme and derive closed-form expressions of security outage probability by invoking both selection combination and maximal ratio combination techniques at the eavesdropper. To provide a benchmark, the round-robin single CRT scheme is also analyzed. Simulation results are provided to verify our analysis and show that O-SCRT provides the best system security outage performance.

Trajectory design for UAV-enabled maritime secure communications: A reinforcement learning approach

This paper investigates an unmanned aerial vehicle (UAV)-enabled maritime secure communication network, where the UAV aims to provide the communication service to a legitimate mobile vessel in the presence of multiple eavesdroppers. In this maritime communication networks (MCNs), it is challenging for the UAV to determine its trajectory on the ocean, since it cannot land or replenish energy on the sea surface, the trajectory should be pre-designed before the UAV takes off. Furthermore, the take-off location of the UAV and the sea lane of the vessel may be random, which leads to a highly dynamic environment. To address these issues, we propose two reinforcement learning schemes, Q-learning and deep deterministic policy gradient (DDPG) algorithms, to solve the discrete and continuous UAV trajectory design problem, respectively. Simulation results are provided to validate the effectiveness and superior performance of the proposed reinforcement learning schemes versus the existing schemes in the literature. Additionally, the proposed DDPG algorithm converges faster and achieves higher utilities for the UAV, compared to the Q-learning algorithm.

Secure transmission of simultaneous wireless information and power transfer system for Internet of things

Abstract Due to the excellent broadcasting characteristics of radio signals, simultaneous wireless information and power transfer (SWIPT) can transmit both information and energy, and provide users with stable power supply. Wireless channel has the characteristics of openness, which will lead to the leakage of information in the SWIPT system. It is one of the research hotspots in the industry to ensure the secure transmission of information in SWIPT system where there are differences in the transmission of energy and information. This paper proposes an ‘information-energy’ dynamic switching opportunistic secure transmission scheme. First, a model considering three factors of multi-cell, multi-user and multiple eavesdropper is established which assumes that the user adopts a time-domain switching receiver that collects energy in a nonlinear model. Then, combined with the time-varying wireless channel, a dynamic information energy switching transmission scheme based on signal-to-interference noise ratio threshold is proposed. Finally, the energy and information transmission performance of the scheme are comprehensively analysed.

Secure Transmission of Terahertz Signals with Multiple Eavesdroppers.

The terahertz (THz) band is expected to become a key technology to meet the ever-increasing traffic demand for future 6G wireless communications, and a lot of efforts have been paid to develop its capacity. However, few studies have been concerned with the transmission security of such ultra-high-speed THz wireless links. In this paper, we comprehensively investigate the physical layer security (PLS) of a THz communication system in the presence of multiple eavesdroppers and beam scattering. The method of moments (MoM) was adopted so that the eavesdroppers’ channel influenced by the PEC can be characterized. To establish a secure link, the traditional beamforming and artificial noise (AN) beamforming were considered as transmission schemes for comparison. For both schemes, we analyzed their secrecy transmission probability (STP) and ergodic secrecy capacity (ESC) in non-colluding and colluding cases, respectively. Numerical results show that eavesdroppers can indeed degrade the secrecy performance by changing the size or the location of the PEC, while the AN beamforming technique can be an effective candidate to counterbalance this adverse effect.

QoE-Aware Video Delivery in Multimedia IoT Network with Multiple Eavesdroppers

How to deal with the increasing video traffic and diverse service demands while ensuring the security of transmission is an open issue in the multimedia Internet of Things (IoT). This paper addresses this issue and studies a secure delivery scheme under a multicast scenario in the presence of multiple eavesdroppers where small base stations (SBSs) can send videos to users cooperatively. Aiming at potential eavesdroppers, a channel model including artificial noise is introduced to reduce the harm of illegal data acquisition. A network quality of experience (QoE) optimization problem is first formulated to account for video quality and delivery delay. In order to solve the nonconvex problem, the successive convex approximation (SCA) technique is applied to optimize multicast group beamforming, reduce the possibility of multicast video eavesdropping, and select video quality where a heuristic scheme is proposed to maximize the network QoE. The effectiveness of the proposed scheme is finally validated by extensive simulations in terms of algorithm convergence performance and network QoE-enhanced performance.

The Effect of Channel Estimation Error on Secrecy Outage Capacity of Dual Selection in the Presence of Multiple Eavesdroppers

The Effect of Channel Estimation Error on Secrecy Outage Capacity of Dual Selection in the Presence of Multiple Eavesdroppers

Secrecy performance analysis of amplify-and-forward relay cooperative networks with simultaneous wireless information and power transfer

Simultaneous wireless information and power transfer (SWIPT) is a promising technology to enhance the power constraint issue in the wireless networks. In this paper, we investigate the secrecy performance of a selective cooperative relaying network with an energy harvesting (EH) technique, in which a source terminal communicates with a legitimate user at the destination terminal through N amplify-and-forward (AF) relays in the presence of multiple eavesdroppers. The relays deploy SWIPT with power splitting-based relaying (PSR) and time switching-based relaying (TSR) protocols to harvest energy. We present closed-form expressions for the secrecy performance metrics, consisting of the probability of non-zero secrecy capacity, the secrecy outage probability, and the average secrecy capacity to evaluate the physical layer security (PLS) of the system. Using the mathematical expressions, we obtain numerical results under the parameters of the system. These results demonstrate that using relay selection can significantly improve the secrecy performance of the system. Moreover, we compare the cooperative relay system without SWIPT and the system with SWIPT. It is observed that depending on the distance of eavesdroppers from the relays and the destination, the system based on SWIPT may achieve a better PLS than the system without SWIPT. Finally, we provide Monte-Carlo simulation results to confirm the validity of our analysis.

Analysis of secrecy outage performance for full duplex NOMA relay systems with appearance of multiple eavesdroppers

Analysis of secrecy outage performance for full duplex NOMA relay systems with appearance of multiple eavesdroppers

Secure and Robust MIMO Transceiver for Multicast Mission Critical Communications

Mission-critical communications (MCC) involve all communications between people in charge of the safety of the civil society. MCC have unique requirements that include improved reliability, security and group communication support. In this paper, we propose secure and robust Multiple-Input-Multiple-Output (MIMO) transceivers, designed for multiple Base Stations (BS) supporting multicast MCC in presence of multiple eavesdroppers. We formulate minimization problems with the Sum-Mean-Square-Error (SMSE) at legitimate users as an objective function, and a lower bound for the MSE at eavesdroppers as a constraint. Security is achieved thanks to physical layer security mechanisms, namely MIMO beamforming and Artificial Noise (AN). Reliability is achieved by designing a system which is robust to two types of channel state information errors: stochastic and norm-bounded. We propose a coordinate descent-based algorithm and a worst-case iterative algorithm to solve these problems. Numerical results at physical layer and system level reveal the crucial role of robust designs for reliable MCC. We show the interest of both robust design and AN to improve the security gap. We also show that full BS cooperation in preferred for highly secured and reliable MCC but dynamic clustering allows to trade-off security and reliability against capacity.

Satisfaction-Maximized Secure Computation Offloading in Multi-Eavesdropper MEC Networks

In this paper, we consider a mobile edge computing (MEC)-based secure computation offloading system, and design a practical multi-eavesdropper model including two specific scenarios of non-colluding and colluding eavesdropping. Furthermore, we design a requirement satisfaction model by exploring practical variations in user request patterns for security provisioning, delay reduction and energy saving. Based on these, we propose a satisfaction-maximized secure computation offloading (SMax-SCO) scheme, and then formulate an optimization problem aiming at maximizing users’ requirement satisfactions subject to secrecy offloading rate, tolerable delay, task workload and maximum power constraints. Since the optimization problem is nonconvex, we present an efficient successive convex approximation (SCA)-based algorithm to obtain suboptimal solutions. We demonstrate that the proposed SMax-SCO scheme achieves a significant improvement in security performance and requirement satisfaction compared with existing schemes. Moreover, we conclude that SMax-SCO can resist eavesdropping attacks of multiple eavesdroppers and even colluding eavesdroppers.

Physical-Layer Security for Cache-Enabled C-RANs via Rate Splitting

This letter proposes a rate splitting (RS)-based secure transmit approach against multiple eavesdroppers in cache-enabled cloud radio access networks (C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -RANs). Unlike existing secure schemes, our approach uses the common stream for dual purposes, serving as the desired message for legitimate users (LUs) and artificial noise (AN) for eavesdroppers. We jointly optimize message splitting, remote radio head (RRH) clustering, and beamforming to maximize the minimum secrecy rate among all LUs and to meet the fronthaul capacity and transmit power per RRH constraints. We transform the formulated problem into two-tier alternating optimization by constructing accurate surrogates for the non-convex objective functions and constraints. We solve the outer-tier and inner-tier problems with the semi-closed-form expressions and the convex framework, respectively. The proposed transmit approach achieves significant gains over existing schemes.

A channel perceiving attack and the countermeasure on long-range IoT physical layer key generation

Physical layer key generation is a lightweight technique to generate secret keys from wireless channels for resource-constrained Internet of things (IoT) applications. The security of the key generation relies on spatial decorrelation, which assumes that eavesdroppers observe uncorrelated channel measurements when they are located over a half-wavelength away from legitimate users. Unfortunately, no experimental validation exists for communications environments with both large-scale and small-scale fading effects. Furthermore, while the current key generation work mainly focuses on short-range communications techniques such as WiFi and ZigBee, the exploration with long-range communications, e.g., LoRa, is somewhat limited. This paper presents a long-range key generation testbed and reveals a new attack scenario that perceives and utilizes large-scale fading effects in key generation channels, by using multiple eavesdroppers circularly around a legitimate user. We formalized such an attack and validated it through extensive experiments conducted in indoor and outdoor environments. It is corroborated that the attack reduces secret key capacity when large-scale fading is predominant. We further investigated potential defenses by proposing a conditional entropy and high-pass filter-based countermeasure to estimate and eliminate large-scale fading components. The experimental results demonstrated that the countermeasure significantly improved the key generation’s security when both large-scale and small-scale fading existed. The keys generated by legitimate users have a desirable low key disagreement rate (KDR) and are validated by the NIST randomness tests. In contrast, eavesdroppers’ average KDR is increased from 0.25 to 0.49.

On Secure NOMA-Based Terrestrial and Aerial IoT Systems

In this paper, we study the secure communication performance of non-orthogonal multiple access (NOMA) communication systems with aerial eavesdroppers. Firstly, the ground-to-ground NOMA communications systems are considered wherein the near user is uniformly distributed in an inner disc and the far user is uniformly distributed in an outer ring within cell coverage of a base station at the center. A single eavesdropper is uniformly distributed outside the protected zone or multiple eavesdroppers are randomly dispersed and modeled as a three-dimensional (3D) homogeneous Poisson point process. Subsequently, the secrecy performance of the ground-to-air NOMA communications systems are investigated wherein the near user is uniformly distributed in an internal 3D spherical cap and the far user is uniformly distributed in an external 3D spherical cap. To enhance secrecy performance, a protected zone is introduced around the ground base station. Novel exact expressions for the secrecy outage probability (SOP) for both scenarios are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of system parameters on SOP of the considered system.

Joint optimization for secure ambient backscatter communication in NOMA-enabled IoT networks

Non-Orthogonal Multiple Access (NOMA) has emerged as a novel air interface technology for massive connectivity in Sixth-Generation (6G) era. The recent integration of NOMA in Backscatter Communication (BC) has triggered significant research interest due to its applications in low-powered Internet of Things (IoT) networks. However, the link security aspect of these networks has not been well investigated. This article provides a new optimization framework for improving the physical layer security of the NOMA ambient BC system. Our system model takes into account the simultaneous operation of NOMA IoT users and the Backscatter Node (BN) in the presence of multiple EavesDroppers (EDs). The EDs in the surrounding area can overhear the communication of Base Station (BS) and BN due to the wireless broadcast transmission. Thus, the chief aim is to enhance link security by optimizing the BN reflection coefficient and BS transmit power. To gauge the performance of the proposed scheme, we also present the suboptimal NOMA and conventional orthogonal multiple access as benchmark schemes. Monte Carlo simulation results demonstrate the superiority of the NOMA BC scheme over the pure NOMA scheme without the BC and conventional orthogonal multiple access schemes in terms of system secrecy rate.

Intelligent Reflecting Surface-Assisted Wireless Secret Key Generation against Multiple Eavesdroppers.

In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user’s SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex–concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.

The impact of channel imperfection and multiple eavesdroppers on security of dual-signal selection in AF-relay systems

The impact of channel imperfection and multiple eavesdroppers on security of dual-signal selection in AF-relay systems

Artificial Noise Sheltered FH Broadcasting With Frequency Mismatch: Secrecy Analysis and Power Allocation

To protect military broadcasting against both hostile interference and eavesdropping, an artificial noise (AN) sheltered frequency hopping (FH) broadcasting (ANS-FHB) architecture is proposed in this paper, and the secrecy capacity is employed to measure its secrecy performance. Besides, considering the inevitable frequency mismatch after synchronization will degrade system secrecy in practical applications, the optimal transmitting power allocation (PA) for the confidential information (CI) and AN is provided to maximize secrecy capacity in presence of frequency mismatch. Moreover, to be adapted to various application scenarios, the proposed optimal PA scheme is further simplified according to the frequency synchronization ability and relative channel quality. The analysis and simulations show that the proposed ANS-FHB system can achieve a non-negative secrecy rate even when existing multiple eavesdroppers. In addition, the optimal power ratio of AN to CI shows a downward trend from one to zero as frequency mismatch increases to mitigate the secrecy loss.

Improving Physical Layer Security in IRS-Aided WPCN Multicast Systems via Stackelberg Game

This paper investigates an intelligent reflecting surface (IRS) aided secure wireless powered communication network (WPCN), where a transmitter first harvests energy from a power station (PS), and then uses the collected energy to transmit information to multiple internet of things (IoT) devices in the form of multicast in the presence of multiple eavesdroppers. An IRS is deployed to enhance the efficiency of wireless energy transfer (WET) and secure wireless information transfer (WIT). Considering that the PS and transmitter belong to different service providers, we model this energy interaction through a Stackelberg game and propose an IRS-aided energy trading and secure communication (IRS-ETSC) scheme, in which the transmitter needs to pay an energy price as an incentive for the PS energy service. Specifically, the transmitter as the leader can control the energy price, WET time, two-stage phase shifts, and beamforming vector, while the PS as the follower can adjust the transmit power. To solve the non-convex leader game problem, we propose a two-step approach to decompose the original problem into two subproblems. The first subproblem can be solved independently by an efficient alternating optimization (AO) based algorithm, in which the closed-form optimal beamforming vector and energy phase shifts are alternately optimized. Then, the second subproblem is relaxed by semidefinite relaxation (SDR) and solved by an iterative algorithm based on block coordinate descent (BCD), where the optimal energy price, optimal WET time, and suboptimal information phase shifts can be obtained by golden section method and successive convex approximation (SCA) respectively. Both subproblems can converge to a stationary point. Numerical results show that compared with the traditional non-IRS scheme, the proposed IRS-ETSC scheme achieves utility improvement for both the PS and transmitter.