Reinforcement Learning Based PHY Authentication for VANETs

Lu, Xiaozhen; Xiao, Liang; Xu, Tangwei; Zhao, Yifeng; Tang, Yuliang; Zhuang, Weihua

doi:10.1109/tvt.2020.2967026

Cited by 78 publications

(31 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, some solutions based on trust, certificates and physical identity authentication have been proposed to deal with GPS spoofing in the VANETs. They applies deep reinforcement learning (RL) to optimize the authentication policy, 17 which effectively solve the problem of limited computing resources, and is suitable for edge computing in many mobile ad hoc networks. However, due to the continuous expansion of the application area of the UAV, the adjustment of parameters can only target a specific business environment, there is no uniform standard for designing and evaluating an authentication model based on RL.…”

Section: Methods Based On Cryptographymentioning

confidence: 99%

See 1 more Smart Citation

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Chen

Miao

et al. 2020

Concurrency and Computation

View full text Add to dashboard Cite

Most of the existing global positioning system (GPS) spoofing detection schemes are vulnerable to the generative GPS spoofing attack, or require additional auxiliary equipment and extensive signal processing capabilities, leading to defects such as low real-time performance and large communication overhead which are not available for the unmanned aerial vehicle (UAV, also known as drone) system. Therefore, we propose a novel solution which employs information fusion based on the GPS receiver and inertial measurement unit. We use a real-time model of tracking and calculating to derive the current position of the drones which are then contrasted with the position information received by the receiver to verify whether the presence or absence of spoofing attack. Subsequent experimental work shows that, the proposed method can accurately detect the spoof within 8 seconds, with a detection rate (DR) of 98.6%. Compared with the existing schemes, the performance of real-time detecting is improved while the DR is ensured. Even in our worst-case, we detect the spoof within 28 seconds after the UAV system starts its mission.

show abstract

Section: Methods Based On Cryptographymentioning

confidence: 99%

“…In practice, only observed values with measurement errors can be obtained, let d𝜏 om = ΔT oAm − NT rm , and according to the nonlinear measurement equation in Equation ( 5), thus we can obtain the Equation (17).…”

Section: Single Uavmentioning

confidence: 99%

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Chen

Miao

et al. 2020

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…For performance evaluation of suggested system and for comparison with existing systems, we utilized the software simulator tool named NS-2 [51]; in Table 2, the suggested system is evaluated with different significant challenges such as CH duration, Average, Stability convergence, cluster member, control overhand by speed and vehicle, energy consumption and throughput of various parameters. Secure Stable-CA [51][52][53][54][55][56][57] and Moth-Flame-CA [58] were used to perform the comparison of stab Trust. Once the operation on different elements of trust, the value of stab Trust is between 0.0 to 1.0.…”

Section: Experimental and Evaluationmentioning

confidence: 99%

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

et al. 2021

View full text Add to dashboard Cite

Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature.

show abstract

“…It facilitates light weightiness communication authentication and vehicle animosity and resists any attack on the data centre. In [ 25 , 26 ], proposed a mechanism for authentication based on edge computing-based smart grid blockchains. This mechanism provides reasonable assistance and security.…”

Section: Related Workmentioning

confidence: 99%

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Arumugam

Maurya

et al. 2021

Sensors

View full text Add to dashboard Cite

The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new opportunities in the new Industrial Transformation. There have been notable challenges regarding the security of data and challenges related to privacy when collecting real-time and automatic data while observing applications in the industry. This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. In FT-Block (Federated transfer learning blockchain), several blockchains are applied to preserve privacy and security for all types of industrial applications. Additionally, by introducing the authentication mechanism based on transfer learning, blockchains can enhance the preservation and security standards for industrial applications. Specifically, Novel Supportive Twin Delayed DDPG trains the user model to authenticate specific regions. As it is considered one of the most open and scalable interacting platforms of information, it successfully helps in the positive transfer of different kinds of data between devices in more significant and local operations of the industry. It is mainly due to a single authentication factor, and the poor adaptation to regular increases in the number of users and different requirements that make the current authentication mechanism suffer a lot in IIoT. As a result, it has been very clearly observed that the given solutions are very useful.

show abstract

Reinforcement Learning Based PHY Authentication for VANETs

Cited by 78 publications

References 38 publications

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Detection of global positioning system spoofing attack on unmanned aerial vehicle system

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Contact Info

Product

Resources

About