92 research outputs found
Securing MIMO Wiretap Channel with Learning-Based Friendly Jamming under Imperfect CSI
Wireless communications are particularly vulnerable to eavesdropping attacks
due to their broadcast nature. To effectively deal with eavesdroppers, existing
security techniques usually require accurate channel state information (CSI),
e.g., for friendly jamming (FJ), and/or additional computing resources at
transceivers, e.g., cryptography-based solutions, which unfortunately may not
be feasible in practice. This challenge is even more acute in low-end IoT
devices. We thus introduce a novel deep learning-based FJ framework that can
effectively defeat eavesdropping attacks with imperfect CSI and even without
CSI of legitimate channels. In particular, we first develop an
autoencoder-based communication architecture with FJ, namely AEFJ, to jointly
maximize the secrecy rate and minimize the block error rate at the receiver
without requiring perfect CSI of the legitimate channels. In addition, to deal
with the case without CSI, we leverage the mutual information neural estimation
(MINE) concept and design a MINE-based FJ scheme that can achieve comparable
security performance to the conventional FJ methods that require perfect CSI.
Extensive simulations in a multiple-input multiple-output (MIMO) system
demonstrate that our proposed solution can effectively deal with eavesdropping
attacks in various settings. Moreover, the proposed framework can seamlessly
integrate MIMO security and detection tasks into a unified end-to-end learning
process. This integrated approach can significantly maximize the throughput and
minimize the block error rate, offering a good solution for enhancing
communication security in wireless communication systems.Comment: 12 pages, 15 figure
Joint Optimization for Secure and Reliable Communications in Finite Blocklength Regime
To realize ultra-reliable low latency communications with high spectral
efficiency and security, we investigate a joint optimization problem for
downlink communications with multiple users and eavesdroppers in the finite
blocklength (FBL) regime. We formulate a multi-objective optimization problem
to maximize a sum secrecy rate by developing a secure precoder and to minimize
a maximum error probability and information leakage rate. The main challenges
arise from the complicated multi-objective problem, non-tractable back-off
factors from the FBL assumption, non-convexity and non-smoothness of the
secrecy rate, and the intertwined optimization variables. To address these
challenges, we adopt an alternating optimization approach by decomposing the
problem into two phases: secure precoding design, and maximum error probability
and information leakage rate minimization. In the first phase, we obtain a
lower bound of the secrecy rate and derive a first-order Karush-Kuhn-Tucker
(KKT) condition to identify local optimal solutions with respect to the
precoders. Interpreting the condition as a generalized eigenvalue problem, we
solve the problem by using a power iteration-based method. In the second phase,
we adopt a weighted-sum approach and derive KKT conditions in terms of the
error probabilities and leakage rates for given precoders. Simulations validate
the proposed algorithm.Comment: 30 pages, 8 figure
Physical Layer Security for Visible Light Communication Systems:A Survey
Due to the dramatic increase in high data rate services and in order to meet
the demands of the fifth-generation (5G) networks, researchers from both
academia and industry are exploring advanced transmission techniques, new
network architectures and new frequency spectrum such as the visible light
spectra. Visible light communication (VLC) particularly is an emerging
technology that has been introduced as a promising solution for 5G and beyond.
Although VLC systems are more immune against interference and less susceptible
to security vulnerabilities since light does not penetrate through walls,
security issues arise naturally in VLC channels due to their open and
broadcasting nature, compared to fiber-optic systems. In addition, since VLC is
considered to be an enabling technology for 5G, and security is one of the 5G
fundamental requirements, security issues should be carefully addressed and
resolved in the VLC context. On the other hand, due to the success of physical
layer security (PLS) in improving the security of radio-frequency (RF) wireless
networks, extending such PLS techniques to VLC systems has been of great
interest. Only two survey papers on security in VLC have been published in the
literature. However, a comparative and unified survey on PLS for VLC from
information theoretic and signal processing point of views is still missing.
This paper covers almost all aspects of PLS for VLC, including different
channel models, input distributions, network configurations,
precoding/signaling strategies, and secrecy capacity and information rates.
Furthermore, we propose a number of timely and open research directions for
PLS-VLC systems, including the application of measurement-based indoor and
outdoor channel models, incorporating user mobility and device orientation into
the channel model, and combining VLC and RF systems to realize the potential of
such technologies
Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance
We investigate the performance of multi-user multiple-antenna downlink
systems in which a BS serves multiple users via a shared wireless medium. In
order to fully exploit the spatial diversity while minimizing the passive
energy consumed by radio frequency (RF) components, the BS is equipped with M
RF chains and N antennas, where M < N. Upon receiving pilot sequences to obtain
the channel state information, the BS determines the best subset of M antennas
for serving the users. We propose a joint antenna selection and precoding
design (JASPD) algorithm to maximize the system sum rate subject to a transmit
power constraint and QoS requirements. The JASPD overcomes the non-convexity of
the formulated problem via a doubly iterative algorithm, in which an inner loop
successively optimizes the precoding vectors, followed by an outer loop that
tries all valid antenna subsets. Although approaching the (near) global
optimality, the JASPD suffers from a combinatorial complexity, which may limit
its application in real-time network operations. To overcome this limitation,
we propose a learning-based antenna selection and precoding design algorithm
(L-ASPA), which employs a DNN to establish underlaying relations between the
key system parameters and the selected antennas. The proposed L-ASPD is robust
against the number of users and their locations, BS's transmit power, as well
as the small-scale channel fading. With a well-trained learning model, it is
shown that the L-ASPD significantly outperforms baseline schemes based on the
block diagonalization and a learning-assisted solution for broadcasting systems
and achieves higher effective sum rate than that of the JASPA under limited
processing time. In addition, we observed that the proposed L-ASPD can reduce
the computation complexity by 95% while retaining more than 95% of the optimal
performance.Comment: accepted to the IEEE Transactions on Wireless Communication
Physical Layer Security in Integrated Sensing and Communication Systems
The development of integrated sensing and communication (ISAC) systems has been spurred by the growing congestion of the wireless spectrum. The ISAC system detects targets and communicates with downlink cellular users simultaneously. Uniquely for such scenarios, radar targets are regarded as potential eavesdroppers which might surveil the information sent from the base station (BS) to communication users (CUs) via the radar probing signal. To address this issue, we propose security solutions for ISAC systems to prevent confidential information from being intercepted by radar targets.
In this thesis, we firstly present a beamformer design algorithm assisted by artificial noise (AN), which aims to minimize the signal-to-noise ratio (SNR) at the target while ensuring the quality of service (QoS) of legitimate receivers. Furthermore, to reduce the power consumed by AN, we apply the directional modulation (DM) approach to exploit constructive interference (CI). In this case, the optimization problem is designed to maximize the SINR of the target reflected echoes with CI constraints for each CU, while constraining the received symbols at the target in the destructive region.
Apart from the separate functionalities of radar and communication systems above, we investigate sensing-aided physical layer security (PLS), where the ISAC BS first emits an omnidirectional waveform to search for and estimate target directions. Then, we formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the Cram\'er-Rao bound (CRB) with the aid of the AN, designing a beampattern with a wide main beam covering all possible angles of targets. The main beam width of the next iteration depends on the optimal CRB. In this way, the sensing and security functionalities provide mutual benefits, resulting in the improvement of mutual performances with every iteration of the optimization, until convergence.
Overall, numerical results show the effectiveness of the ISAC security designs through the deployment of AN-aided secrecy rate maximization and CI techniques. The sensing-assisted PLS scheme offers a new approach for obtaining channel information of eavesdroppers, which is treated as a limitation of conventional PLS studies. This design gains mutual benefits in both single and multi-target scenarios
An Overview of Physical Layer Security with Finite Alphabet Signaling
Providing secure communications over the physical layer with the objective of achieving secrecy without requiring a secret key has been receiving growing attention within the past decade. The vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are Gaussian distributed. However, in practice, the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation. Hence, understanding the impact of the finite-alphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security. With this motivation, this article reviews recent developments on physical layer security with finite-alphabet inputs. We explore transmit signal design algorithms for single-antenna as well as multi-antenna wiretap channels under different assumptions on the channel state information at the transmitter. Moreover, we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multi-carrier transmission systems, broadcast channels with confidential messages, cognitive multiple access and relay networks. Throughout the article, we stress the important behavioral differences of discrete versus Gaussian inputs in the context of the physical layer security. We also present an overview of practical code construction over Gaussian and fading wiretap channels, and discuss some open problems and directions for future research
Secure Precoding for Future Wireless Communication Systems
Department of Electrical EngineeringPhysical layer security has emerged a flourishing strategy to protect confidential information from eavesdroppers with lower computational complexity compared to cryptography. Secure precoding is a promising transmission method of physical layer security to improve security by exploiting an intrinsic attribute of wireless communications. The main goal of the secure precoding is to maximize secrecy rate in multi-input and multi-output (MIMO) systems with the presence of eavesdroppers. Unfortunately, there exists no optimal solution, and also solving the secrecy rate maximization problem becomes more challenging as networks involve a multi-user (MU) and multi-eavesdropper (ME) scenario because of its non-smoothness and non-convexity. In this thesis, I proposed a novel secure precoding algorithm for downlink MU-MIMO systems under ME threat to enhance the secrecy rate, and provide subsequent analyses for realizing ultra-reliable low latency communications (URLLC). By incorporating strong security, communication reliability, and latency, a multi-objective optimization problem is investigated in the finite blocklength (FBL) regime. The derived optimization problem aims to maximize the secrecy rate by designing a secure precoder, while simultaneously minimizing both the maximum error probability and the rate of information leakage. The proposed FBL-based optimization algorithm provides the significantly improved tradeoff among the security, the error probability, and information leakage rate. Therefore, the proposed algorithms can offer significantly improved security for future wireless communication systems.clos
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