124 research outputs found
MIMO Techniques for Jamming Threat Suppression in Vehicular Networks
Vehicular ad hoc networks have emerged as a promising field of research and development, since they will be able to accommodate a variety of applications, ranging from infotainment to traffic management and road safety. A specific security-related concern that vehicular ad hoc networks face is how to keep communication alive in the presence of radio frequency jamming, especially during emergency situations. Multiple Input Multiple Output techniques are proven to be able to improve some crucial parameters of vehicular communications such as communication range and throughput. In this article, we investigate how Multiple Input Multiple Output techniques can be used in vehicular ad hoc networks as active defense mechanisms in order to avoid jamming threats. For this reason, a variation of spatial multiplexing is proposed, namely, vSP4, which achieves not only high throughput but also a stable diversity gain upon the interference of a malicious jammer
Intrusion Detection System for Platooning Connected Autonomous Vehicles
The deployment of Connected Autonomous Vehicles (CAVs) in Vehicular Ad Hoc Networks (VANETs) requires secure wireless communication in order to ensure reliable connectivity and safety. However, this wireless communication is vulnerable to a variety of cyber atacks such as spoofing or jamming attacks. In this paper, we describe an Intrusion Detection System (IDS) based on Machine Learning (ML) techniques designed to detect both spoofing and jamming attacks in a CAV environment. The IDS would reduce the risk of traffic disruption and accident caused as a result of cyber-attacks. The detection engine of the presented IDS is based on the ML algorithms Random Forest (RF), k-Nearest Neighbour (k-NN) and One-Class Support Vector Machine (OCSVM), as well as data fusion techniques in a cross-layer approach. To the best of the authors’ knowledge, the proposed IDS is the first in literature that uses a cross-layer approach to detect both spoofing and jamming attacks against the communication of connected vehicles platooning. The evaluation results of the implemented IDS present a high accuracy of over 90% using training datasets containing both known and unknown attacks
Bypassing a Reactive Jammer via NOMA-Based Transmissions in Critical Missions
Wireless networks can be vulnerable to radio jamming attacks. The quality of
service under a jamming attack is not guaranteed and the service requirements
such as reliability, latency, and effective rate, specifically in
mission-critical military applications, can be deeply affected by the jammer's
actions. This paper analyzes the effect of a reactive jammer. Particularly,
reliability, average transmission delay, and the effective sum rate (ESR) for a
NOMA-based scheme with finite blocklength transmissions are mathematically
derived taking the detection probability of the jammer into account.
Furthermore, the effect of UEs' allocated power and blocklength on the network
metrics is explored. Contrary to the existing literature, results show that gNB
can mitigate the impact of reactive jamming by decreasing transmit power,
making the transmissions covert at the jammer side. Finally, an optimization
problem is formulated to maximize the ESR under reliability, delay, and
transmit power constraints. It is shown that by adjusting the allocated
transmit power to UEs by gNB, the gNB can bypass the jammer effect to fulfill
the 0.99999 reliability and the latency of 5ms without the need for packet
re-transmission.Comment: 6 pages, 7 figures, IEEE International Conference on Communications
(ICC) 202
Enhanced Physical Layer Security for Full-duplex Symbiotic Radio with AN Generation and Forward Noise Suppression
Due to the constraints on power supply and limited encryption capability,
data security based on physical layer security (PLS) techniques in backscatter
communications has attracted a lot of attention. In this work, we propose to
enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive
eavesdropper, which may overhear the information and interfere legitimate
communications simultaneously by emitting attack signals. To deal with the
eavesdroppers, we propose a security strategy based on pseudo-decoding and
artificial noise (AN) injection to ensure the performance of legitimate
communications through forward noise suppression. A novel AN signal generation
scheme is proposed using a pseudo-decoding method, where AN signal is
superimposed on data signal to safeguard the legitimate channel. The phase
control in the forward noise suppression scheme and the power allocation
between AN and data signals are optimized to maximize security throughput. The
formulated problem can be solved via problem decomposition and alternate
optimization algorithms. Simulation results demonstrate the superiority of the
proposed scheme in terms of security throughput and attack mitigation
performance
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