A Security Aware Fuzzy Enhanced Reliable Ant Colony Optimization Routing in Vehicular Ad hoc Networks

Zhang, Hang; Bochem, Arne; Sun, Xu Guang; Hogrefe, Dieter

doi:10.1109/ivs.2018.8500485

Cited by 19 publications

(11 citation statements)

References 13 publications

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“…A Swarm Intelligence algorithm for VANET protection against such kind of routing attacks is introduced in [82]. In [83]- [88], the use of Swarm Intelligence algorithms in dynamic VANETs is introduced for better routing. These include Ant-Colony-Based routing, geographic algorithm based on Cat Swarm optimization for VANET, Particle Swarm Optimization algorithms, Bee-Inspired Approach, and Fuzzy Logic.…”

Section: E Security In Vanetmentioning

confidence: 99%

“…Studies in [95]- [99] have utilized Fuzzy logic, ANN, Unsupervised learning and game theory, respectively to devise an Intrusion Detection System (IDS) for VANET. Zhang et al [88] have introduced a security aware routing protocol against black holes, and flooding attacks, using Fuzzy logic and ACO. Tables 5 presents a brief summary of the research works where AI is utilized in different forms to the domain of security in VANETs.…”

Section: E Security In Vanetmentioning

confidence: 99%

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Artificial Intelligence for Vehicle-to-Everything: A Survey

et al. 2019

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Recently, the advancement in communications, intelligent transportation systems, and computational systems has opened up new opportunities for intelligent traffic safety, comfort, and efficiency solutions. Artificial intelligence (AI) has been widely used to optimize traditional data-driven approaches in different areas of the scientific research. Vehicle-to-everything (V2X) system together with AI can acquire the information from diverse sources, can expand the driver's perception, and can predict to avoid potential accidents, thus enhancing the comfort, safety, and efficiency of the driving. This paper presents a comprehensive survey of the research works that have utilized AI to address various research challenges in V2X systems. We have summarized the contribution of these research works and categorized them according to the application domains. Finally, we present open problems and research challenges that need to be addressed for realizing the full potential of AI to advance V2X systems.

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Section: E Security In Vanetmentioning

confidence: 99%

Section: E Security In Vanetmentioning

confidence: 99%

Artificial Intelligence for Vehicle-to-Everything: A Survey

et al. 2019

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“…In 2018, Zhang et al [34] have implemented a security aware fuzzy enhanced reliable ant colony optimisation (SAFERACO) routing protocol to recognise misbehaving nodes and eliminate them from the routing process. In the NS‐3 the SAFERACO was implemented and evaluated it under various scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The main objective of this research work is to select the optimal route, for that a novel metaheuristic algorithm named MC‐JA is selected. This is because heuristic has a capability to find a sufficiently good solution to an optimisation problem, especially with incomplete information [33, 34] Moreover, metaheuristic makes few assumptions to solve the optimisation problems, and so they may be used for a variety of problems [29, 30]. Here, the input solution to this algorithm is the matrix, i.e.…”

Section: Selection Of Optimal Route Using Mc‐jamentioning

confidence: 99%

Optimal routing in VANET using improved meta‐heuristic approach: a variant of Jaya

Gnanasekar¹,

Samiappan

2020

IET Communications

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“…Using a significant inference rule, it can be suitably used for carving security demands as per expectation. The most recent work of Zhang et al [46] have combined fuzzy logic and swarm optimization concept in order to develop a secure routing protocol for vehicular networks. Using a simulation-based study, the study outcome shows effective packet forwarding performance over increasing mobile nodes.…”

Section: I) Fuzzy-logic Based Security Solutionmentioning

confidence: 99%

Insights on Security Improvements and Implications of Artificial Intelligence in MANET

T.M.¹,

Shivakumar²

2019

CAE

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Mobile Adhoc Network (MANET) is claimed to be an integral part of all futuristic network and communication system e.g. cloud, reconfigurable network, Internet-of-Things (IoT), interdomain routing, etc. However, the security problems of MANET is not yet been mitigated irrespective of archives of security approaches and solution. For a MANET system to be integrated with upcoming technologies it is required that their routing system should offer higher level of resistance against all potential threats as well as they should also offer a better flexibility to tailor the security scheme based on demand of the environment, where the mobile nodes are operating. It is also seen that Artificial Intelligence is another big boon which is currently being proliferating at faster speed and there are some segment of research where it is also claimed to contribute towards security system in MANET. Therefore, this paper offers insights to the current state of security system using conventional as well as using Artificial Intelligence to explore about its research gap.

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A Security Aware Fuzzy Enhanced Reliable Ant Colony Optimization Routing in Vehicular Ad hoc Networks

Cited by 19 publications

References 13 publications

Artificial Intelligence for Vehicle-to-Everything: A Survey

Artificial Intelligence for Vehicle-to-Everything: A Survey

Optimal routing in VANET using improved meta‐heuristic approach: a variant of Jaya

Insights on Security Improvements and Implications of Artificial Intelligence in MANET

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