ArticleSensors (Basel, Switzerland)2023
RIS-Enabled Secret Key Generation for Secured Vehicular Communication in the Presence of Denial-of-Service Attacks.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 8 citations in OpenAlex.
- Adaptive Dual Reinforcement Learning for Hybrid Spatial-Temporal Networks in RIS-Assisted Indoor Localization (ADRL-HSTNet).Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security solutions should be computationally inexpensive, ultra-reliable, and capable of operating in any wireless propagation environment. Physical layer secret key generation has emerged as a promising technique, which leverages the inherent randomness of wireless-channel responses in amplitude and phase to generate high-entropy symmetric shared keys. The sensitivity of the channel-phase responses to the distance between network terminals makes this technique a viable solution for secure vehicular communication, given the dynamic behavior of these terminals. However, the practical implementation of this technique in vehicular communication is hindered by fluctuations in the communication link between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. This study introduces a key-generation approach that uses a reconfigurable intelligent surface (RIS) to secure message exchange in vehicular communication. The RIS improves the performance of key extraction in scenarios with low signal-to-noise ratios (SNRs) and NLoS conditions. Additionally, it enhances the network's security against denial-of-service (DoS) attacks. In this context, we propose an efficient RIS configuration optimization technique that reinforces the signals received from legitimate users and weakens the signals from potential adversaries. The effectiveness of the proposed scheme is evaluated through practical implementation using a 1-bit RIS with 64×64 elements and software-defined radios operating within the 5G frequency band. The results demonstrate improved key-extraction performance and increased resistance to DoS attacks. The hardware implementation of the proposed approach further validated its effectiveness in enhancing key-extraction performance in terms of the key generation and mismatch rates, while reducing the effect of the DoS attacks on the network.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.