331 research outputs found
Artificial-Noise-Aided Physical Layer Phase Challenge-Response Authentication for Practical OFDM Transmission
Recently, we have developed a PHYsical layer Phase Challenge-Response
Authentication Scheme (PHY-PCRAS) for independent multicarrier transmission. In
this paper, we make a further step by proposing a novel artificial-noise-aided
PHY-PCRAS (ANA-PHY-PCRAS) for practical orthogonal frequency division
multiplexing (OFDM) transmission, where the Tikhonov-distributed artificial
noise is introduced to interfere with the phase-modulated key for resisting
potential key-recovery attacks whenever a static channel between two legitimate
users is unfortunately encountered. Then, we address various practical issues
for ANA-PHY-PCRAS with OFDM transmission, including correlation among
subchannels, imperfect carrier and timing recoveries. Among them, we show that
the effect of sampling offset is very significant and a search procedure in the
frequency domain should be incorporated for verification. With practical OFDM
transmission, the number of uncorrelated subchannels is often not sufficient.
Hence, we employ a time-separated approach for allocating enough subchannels
and a modified ANA-PHY-PCRAS is proposed to alleviate the discontinuity of
channel phase at far-separated time slots. Finally, the key equivocation is
derived for the worst case scenario. We conclude that the enhanced security of
ANA-PHY-PCRAS comes from the uncertainty of both the wireless channel and
introduced artificial noise, compared to the traditional challenge-response
authentication scheme implemented at the upper layer.Comment: 33 pages, 13 figures, submitted for possible publicatio
A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends
This paper examines the security vulnerabilities and threats imposed by the
inherent open nature of wireless communications and to devise efficient defense
mechanisms for improving the wireless network security. We first summarize the
security requirements of wireless networks, including their authenticity,
confidentiality, integrity and availability issues. Next, a comprehensive
overview of security attacks encountered in wireless networks is presented in
view of the network protocol architecture, where the potential security threats
are discussed at each protocol layer. We also provide a survey of the existing
security protocols and algorithms that are adopted in the existing wireless
network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term
evolution (LTE) systems. Then, we discuss the state-of-the-art in
physical-layer security, which is an emerging technique of securing the open
communications environment against eavesdropping attacks at the physical layer.
We also introduce the family of various jamming attacks and their
counter-measures, including the constant jammer, intermittent jammer, reactive
jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the
integration of physical-layer security into existing authentication and
cryptography mechanisms for further securing wireless networks. Finally, some
technical challenges which remain unresolved at the time of writing are
summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201
Wireless communication, sensing, and REM: A security perspective
The diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted
Deep Learning Methods for Device Identification Using Symbols Trace Plot
Devices authentication is one crucial aspect of any communication system.
Recently, the physical layer approach radio frequency (RF) fingerprinting has
gained increased interest as it provides an extra layer of security without
requiring additional components. In this work, we propose an RF fingerprinting
based transmitter authentication approach density trace plot (DTP) to exploit
device-identifiable fingerprints. By considering IQ imbalance solely as the
feature source, DTP can efficiently extract device-identifiable fingerprints
from symbol transition trajectories and density center drifts. In total, three
DTP modalities based on constellation, eye and phase traces are respectively
generated and tested against three deep learning classifiers: the 2D-CNN,
2D-CNN+biLSTM and 3D-CNN. The feasibility of these DTP and classifier pairs is
verified using a practical dataset collected from the ADALM-PLUTO
software-defined radios (SDRs)
An Overview of Physical Layer Security with Finite-Alphabet Signaling
Providing secure communications over the physical layer with the objective of
achieving perfect 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 we discuss some open problems and
directions for future research.Comment: Submitted to IEEE Communications Surveys & Tutorials (1st Revision
Securing NextG networks with physical-layer key generation: A survey
As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks
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