A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks

Gyawali, Sohan; Qian, Yi; Hu, Rose Qingyang

doi:10.1109/tvt.2021.3079385

Cited by 20 publications

(6 citation statements)

References 24 publications

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“…Additionally, it appears that the word dependability is often used with reference to security and safety performance measures in dealing with malicious network attacks under the IoV scenario, as revealed by a brief review of the current state of research in the field [12][13][14]. Moreover, some studies aimed at improving the trustworthiness of the IoV confuse this concept with trust by studying the trust value management of vehicles and examining only the reputations of individual nodes within the IoV.…”

Section: Refsmentioning

confidence: 99%

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An integrated dependability guarantee provisioning for cluster‐based IoV networks with slicing

Wang

Jing

et al. 2023

IET Intelligent Trans Sys

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High‐dependability Internet of Vehicle (IoV) is essential for urban transit, since it contributes to the safe operation of vehicles, and even to the safety of the entire city. This paper introduces the IoV cluster model with network slicing. Based on this model, an integrated vehicles clustering and network slicing scheme for IoV networks is introduced to guarantee the dependability of different traffics in IoV. The network slicing scheme is proposed to divide the wireless frequency resource of the IoV network into separate logical networks. A analysis model, based on age of information, is utilized as an integrated indicator for evaluating the dependability of the IoV system in urban transit. Asynchronous reinforcement learning with advantage actor‐critic is employed to optimize the integrated dependability of IoV. It is demonstrated in simulations that the proposed IoV cluster incorporating the network slicing scheme can guarantee the integrated dependability of the IoV system. Moreover, by the application of reinforcement learning, the system dependability can be further improved.

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Section: Refsmentioning

confidence: 99%

“…In the LTE-V2X based the IoV system, the t HARQ is t HARQ = t Vs−p + t Vr−p + t data (14) where t data indicates transmission time between sending vehicle and receiving vehicle, t Vs−p and t Vr−p are the processing time of sending vehicle and receiving vehicle.…”

Section: Dependability Analysis Considering Packet Drop and Re-transm...mentioning

confidence: 99%

An integrated dependability guarantee provisioning for cluster‐based IoV networks with slicing

Wang

Jing

et al. 2023

IET Intelligent Trans Sys

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“…More recently, Gyawali, et al [50] developed an approach for a privacy-preserving misbehavior detection system in vehicular communication networks. The approach leverages several external components, alongside homomorphic encryption to enforce privacy, while detecting abnormal vehicle behavior.…”

Section: Privacy-preserving Detection Techniquesmentioning

confidence: 99%

Privacy-Preserving Tampering Detection in Automotive Systems

et al. 2021

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Modern auto-vehicles are built upon a vast collection of sensors that provide large amounts of data processed by dozens of Electronic Control Units (ECUs). These, in turn, monitor and control advanced technological systems providing a large palette of features to the vehicle’s end-users (e.g., automated parking, autonomous vehicles). As modern cars become more and more interconnected with external systems (e.g., cloud-based services), enforcing privacy on data originating from vehicle sensors is becoming a challenging research topic. In contrast, deliberate manipulations of vehicle components, known as tampering, require careful (and remote) monitoring of the vehicle via data transmissions and processing. In this context, this paper documents an efficient methodology for data privacy protection, which can be integrated into modern vehicles. The approach leverages the Fast Fourier Transform (FFT) as a core data transformation algorithm, accompanied by filters and additional transformations. The methodology is seconded by a Random Forest-based regression technique enriched with further statistical analysis for tampering detection in the case of anonymized data. Experimental results, conducted on a data set collected from the On-Board Diagnostics (OBD II) port of a 2015 EUR6 Skoda Rapid 1.2 L TSI passenger vehicle, demonstrate that the restored time-domain data preserves the characteristics required by additional processing algorithms (e.g., tampering detection), showing at the same time an adjustable level of privacy. Moreover, tampering detection is shown to be 100% effective in certain scenarios, even in the context of anonymized data.

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“…e question to be considered is how a vehicle decides whether to believe a message sent by a dependable vehicle. In order to prevent the above problems from causing improper behavior of the vehicle, misconduct detection mechanisms [10] and reputation systems [11] have been put forward. Trust vehicles can be distinguished from untrusted vehicles by building trust relationships and detecting malicious behavior in IOV, thereby preventing the vehicle from being misdirected by other malicious vehicles.…”

Section: Introductionmentioning

confidence: 99%

Trust-Based Certificateless Privacy-Preserving Authentication in Internet of Vehicles

2022

Security and Communication Networks

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Owing to the security requirements of Internet of vehicles (IOV), it is necessary to design a secure privacy-preserving scheme for communication. Traditional privacy-preserving schemes have two deficiencies. One is the high cost of computation and communication. Another is the inability to prevent the spread of malicious or modified messages. Motivated by those facts, we proposed a trust-based authentication scheme for certificateless privacy-preserving of IOV, based on the advantages of the short key, fast speed, and high security performance of elliptic curve cryptography (ECC). We proposed a method to replace the revocation list by authenticating trust to prevent broadcasting fake and altered massages. Our scheme can encrypt the message sent by the node while adopting a certificateless authentication method to complete the anonymous authentication function, which protects the privacy of the node information and effectively reduces the system storage load. In addition, aggregate signatures can effectively reduce computational and communication overhead. It is proven theoretically that the proposed scheme can satisfy correctness, anonymity, confidentiality of messages, and unforgeability of signatures. Therefore, this scheme is more suitable for the deployment and application of physical IOV.

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A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks

Cited by 20 publications

References 24 publications

An integrated dependability guarantee provisioning for cluster‐based IoV networks with slicing

An integrated dependability guarantee provisioning for cluster‐based IoV networks with slicing

Privacy-Preserving Tampering Detection in Automotive Systems

Trust-Based Certificateless Privacy-Preserving Authentication in Internet of Vehicles

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