Trust Management Schemes for Secure Routing in VANETs — A Survey

Gillani, Maryam; Ullah, Ata; Niaz, Hafiz Adnan

doi:10.1109/macs.2018.8628440

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…In such kinds of techniques, the network can detect and recognize irregularities with a high level of precision. It also forecasts the upcoming word deriving from each vehicle respectively [12].…”

Section: A Network Safetymentioning

confidence: 99%

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Role of Machine Learning in WSN and VANETs

Gillani

Niaz

Tayyab

2021

IJECER

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Dynamic nature of Vehicular Ad-hoc Networks (VANETs) and Wireless Sensor Networks (WSN) makes them hard to deal accordingly. For such dynamicity, Machine learning (ML) approaches are considered favourable. ML can be described as the process or method of self-learning without human intervention that can assist through various tools to deal with heterogeneous data to attain maximum beneﬁts from the network. In this paper, a quick summary of primary ML concepts are discussed along with several algorithms based on ML for WSN and VANETs. Afterwards, ML based WSN and VANETs application, open issues, challenges of rapidly changing networks and various algorithms in relation to ML models and techniques are discussed. We have listed some of the ML techniques to take additional consideration of this emergent ﬁeld. A summary is given for ML techniques application with their complexities to cover on open issues to kick start further research investigation. This paper provides excellent coverage of state-of-the-art ML applications that are being used in WSN and VANETs with their comparative analysis.

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Section: A Network Safetymentioning

confidence: 99%

“…VANETs hold rapidly changing traffic states and conditions [12]. ML work for the real-time traffic data and traffic information stored by numerous vehicular sensors.…”

Section: Traffic Flow Predictionmentioning

confidence: 99%

Role of Machine Learning in WSN and VANETs

Gillani

Niaz

Tayyab

2021

IJECER

Self Cite

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“…The literature provides a considerable amount of publications [3][4][5] dealing with trust management systems in different domains (IoT, WMN (Wireless Mesh Networks), MANET (Mobile Ad-Hoc Networks), VANET (Vehicular Ad-Hoc Networks), P2P (Peer to Peer) Networks). However, traditional approaches suffer from a low decentralization level of their trust systems, missing initial trust score evaluations, insecure trust data storage and uncomplete trust models.…”

Section: A Backgroundmentioning

confidence: 99%

Blockchain and Trust for Secure, End-User-Based and Decentralized IoT Service Provision

et al. 2020

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Building trust relationships between different decentralized entities in the IoT ecosystem is essential. Hereof, the combination of blockchain technology and trust evaluation techniques is recently considered as an efficient measure. However, both technologies within the IoT are still facing some limitations which are addressed in this research. First, this publication reviews various blockchain-based trust approaches and depicts their strengths and limitations regarding their usage in decentralized IoT communities. Then, an optimized trust model with a multi-layer adaptive and trust-based weighting system is proposed. Additionally, different trust metric parameters and their mathematical models used for trust evaluation are presented. Moreover, this publication presents a novel approach for incentivization processes in the IoT marketplace using control loops and smart contracts. Thereby, participants are motivated to continuously improve their behavior. Finally, the proposed trust model is proved to be reliable. The experimental results conducted from different scenarios show that the presented approach provides more resiliency against various attacks than existing ones.

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“…Few surveys related to the trust management for VANETs are reported [14,15,25,26]. Reference [15] discussed the revocation target which covered the entity-oriented, data-oriented, and hybrid trust models.…”

Section: Introductionmentioning

confidence: 99%

“…It covered the specific trust model while did not cover the whole trust management system. Gillani et al [26] launched a survey on trust management techniques for routing protocol. It focused on the trust management schemes which were applicable for the release of useful information for real-time applications.…”

Section: Introductionmentioning

confidence: 99%

Security and Privacy in Vehicular Ad Hoc Network and Vehicle Cloud Computing: A Survey

Sheikh

Liang

Wang

2020

Wireless Communications and Mobile Computing

103

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Vehicular networks are becoming a prominent research field in the intelligent transportation system (ITS) due to the nature and characteristics of providing high-level road safety and optimized traffic management. Vehicles are equipped with the heavy communication equipment which requires a high power supply, on-board computing device, and data storage devices. Many wireless communication technologies are deployed to maintain and enhance the traffic management system. The ITS is capable of providing services to the traffic authorities and precautionary measures to the drivers and passengers. Several methods have been proposed for discussing the security and privacy issues for the vehicular ad hoc networks (VANETs) and vehicular cloud computing (VCC). They receive a great deal of attention from researchers around the world since they are new technologies, and they can improve road safety and enhance traffic flow by utilizing the vehicles resources and communication system. Firstly, the VANETs are presented, including the basic overview, characteristics, threats, and attacks. The location privacy methodologies are elaborated, which can protect the confidential information of the vehicle, such as the location detail and driver information. Secondly, the trust management models in the VANETs are comprehensively discussed, followed by the comparison of the cryptography and trust models in terms of different kinds of attacks. Then, the simulation tools and applications of the VANETs are discussed, and the evolution is presented from the VANETs to VCC in the vehicular network. Thirdly, the VCC is discussed from its architecture and the security and privacy issues. Finally, several research challenges on the VANETs and VCC are presented. In sum, this survey comprehensively covers the location privacy and trust management models of the VANETs and discusses the security and privacy issues in the VCC, which fills the gap of existing surveys. Also, it indicates the research challenges in the VANETs and VCC.

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Trust Management Schemes for Secure Routing in VANETs — A Survey

Cited by 10 publications

References 18 publications

Role of Machine Learning in WSN and VANETs

Role of Machine Learning in WSN and VANETs

Blockchain and Trust for Secure, End-User-Based and Decentralized IoT Service Provision

Security and Privacy in Vehicular Ad Hoc Network and Vehicle Cloud Computing: A Survey

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