Securing Traffic-Related Messages Exchange Against Inside-and-Outside Collusive Attack in Vehicular Networks

Feng, Jingyu; Liu, Nan; Cao, Jie; Zhang, Yuqing; Lu, Guangyue

doi:10.1109/jiot.2019.2933632

Cited by 14 publications

(6 citation statements)

References 24 publications

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“…In this way, the effectiveness of each technique in the AGTM and the robustness of the overall model can be verified. Finally, we selected the following three comparison models: the equal‐weight trust model (EWTM) [16], the feedback model based on the target information entropy theory (FMOIE) [17], and the trust value fluctuation analysis model (TFAM) [18]. They have been proposed and cited in the existing literature, and all belong to lightweight models.…”

Section: Simulation Analysismentioning

confidence: 99%

“…Yuan et al adopt an information fusion algorithm based on objective information entropy theory, which can overcome the limitations of traditional trust schemes, whereby the trust factors are weighed manually or subjectively [17]. Feng et al established weights based on the volatility of the nodes' trust values and improved the real-time performance to detect malicious attacks [18]. There are also studies on the improvement of trust models based on complex algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…Feng et al. established weights based on the volatility of the nodes' trust values and improved the real‐time performance to detect malicious attacks [18]. There are also studies on the improvement of trust models based on complex algorithms.…”

Section: Introductionmentioning

confidence: 99%

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A lightweight and anti‐collusion trust model combined with nodes dynamic relevance for the power internet of things

Zhao,

Sun

2023

IET Science Measure & Tech

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A large number of monitoring sensors are introduced in the power grid. However, the traditional trust models commonly used for edge‐side security management are weak in detecting large‐scale malicious interactions and collusion attacks. For that, a lightweight and anti‐collusion trust model combined with nodes’ dynamic relevance for the power Internet of Things (IoT) is proposed. Firstly, a global trust management system is constructed according to the working mechanism of sensors in the power grid. After that, trust feedback and contact frequency of the devices are combined to build an adaptive dynamic weight vector based on relevance volatility. Fluctuations in trust values are reduced and the trust difference between normal and malicious nodes is widened. An anti‐collusion algorithm based on contact set awareness is also designed to effectively detect collusion attacks. The checksum local broadcast is established in the trust model to counteract the risk of intelligent terminal failure. The results show that the trust model achieves 100% accuracy of node discrimination when the maximum proportion of malicious nodes is 20% in a 50‐node network scale. In addition, the calculation time of the overall model is 211 ms and the memory consumption is 161 kb, which is suitable for power IoT sensor networks.

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Section: Simulation Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A lightweight and anti‐collusion trust model combined with nodes dynamic relevance for the power internet of things

Zhao,

Sun

2023

IET Science Measure & Tech

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“…However, most spatial cloaking schemes assume that CVs always tell the truth, and fail to consider location cheating behaviors during the construction of the cloaking area. The high mobility and volatility characteristics of VANETs make adjacent vehicles usually unknown to each other [11]. This may offer opportunities for dishonest CVs to provide false location information, which leads that the cloaking area cannot satisfy the privacy protection requirement of RV.…”

Section: Introductionmentioning

confidence: 99%

TCA: A Trusted Collaborative Anonymity Construction Scheme for Location Privacy Protection in VANETs

2022

KSII TIIS

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As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

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“…Meanwhile, as collectors, vehicles can integrate and analyze received information, so as to avoid congested road and prevent accidents. However, due to the wireless network communication environment, it's easy for attackers to intercept, tamper and replay the transmitted messages, which gives a risk to security and reliability of VANETs [3]. According to [4], authentication is considered to be the most reliable mechanism to ensure the legitimacy of entities in VANETs.…”

Section: Introductionmentioning

confidence: 99%

AAAS: An Anonymous Authentication Scheme Based on Group Signature in VANETs

Jiang

Shen

2020

IEEE Access

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As special ad-hoc networks, vehicular ad-hoc networks (VANETs) support vehicles to communicate with each other via opportunistic wireless links. In order to protect privacy of drivers, vehicles registered in VANETs are required to authenticate and communicate with surrounding vehicles or roadside infrastructure anonymously. However, due to high-speed driving and wireless environment, it is vital to propose a privacy protection scheme that is able to balance security and efficiency. Consequently, this paper proposes an anonymous authentication scheme in VANETs (AAAS). Specifically, we add region trust authority to provide more efficient anonymous authentication service for vehicles. Subsequently, group signature mechanism is adopted to achieve anonymity and conditional privacy. Moreover, security and performance analysis show that AAAS has higher security and efficiency.

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Securing Traffic-Related Messages Exchange Against Inside-and-Outside Collusive Attack in Vehicular Networks

Cited by 14 publications

References 24 publications

A lightweight and anti‐collusion trust model combined with nodes dynamic relevance for the power internet of things

A lightweight and anti‐collusion trust model combined with nodes dynamic relevance for the power internet of things

TCA: A Trusted Collaborative Anonymity Construction Scheme for Location Privacy Protection in VANETs

AAAS: An Anonymous Authentication Scheme Based on Group Signature in VANETs

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