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A survey on Intrusion Detection Systems and Honeypot based proactive security mechanisms in VANETs and VANET Cloud

期刊

VEHICULAR COMMUNICATIONS
卷 12, 期 -, 页码 138-164

出版社

ELSEVIER
DOI: 10.1016/j.vehcom.2018.04.005

关键词

Cybersecurity; Honeypot; Intrusion Detection System (IDS); Security Threats; Vehicular Ad-hoc Networks (VANETs); VANET Cloud

资金

  1. SMVD University

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Vehicular ad-hoc Network (VANET) is an emerging type of Mobile ad-hoc Networks (MANETs) with excellent applications in the intelligent traffic system. Applications in VANETs are life critical since human lives are at stake and therefore, interaction among nodes (vehicles) must be established in the most secure manner. To provide security for VANETs, various security measures are designed, the most popular of which is Intrusion Detection Systems (IDSs). IDS has already proved its worth in detection of malicious nodes in traditional networks but applying the IDS in VANET like networks is somehow different and difficult due to its peculiar characteristics such as resource-constrained nodes, high mobility of nodes, specific protocols stacks, and standards. This paper presents a brief introduction about the various IDSs, in general, to get the readers well acquainted with the concept of IDS after which an in-depth survey of various IDSs that are propounded for VANETs is put forward followed by analyzing and comparing each technique along with merits and demerits. Some basic instructions have also been presented for developing IDSs that have a potential application in VANET and VANET Cloud. Our aim is to identify leading trends, open challenges, and future research directions in the deployment of IDS in VANET. In order to bridge the research gaps in terms of performance, detection rate and overhead, and also to overcome the challenges of existing IDS in literature, a proactive bait based Honeypot optimized IDS system is also proposed with the aim to detect existing and zero-day attacks with minimal overhead. Finally, some open research works being carried out in the field is also proposed. (C) 2018 Elsevier Inc. All rights reserved.

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