Network Intrusion Detection Using Machine Learning in Vanets: A Review
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Vehicular Ad-hoc Network (VANETs) aids the vehicles to form a self-organized network in the absence of centralized infrastructure. It is the constituent of MANET and supports intelligent transport system (ITS). Each node is free to move independently in an ad-hoc network. In absence of centralized architecture, security becomes the crucial aspect of VANET. Cryptographic techniques such as digital signatures and encryption are unable to deal with unknown attacks. In order to deal with this issue, there is need of other technique to “detect and notify” these unknown attacks i.e. intrusion detection. An Intrusion Detection System (IDS) is a set of software that monitors a single or a network of computers for malicious activities (attacks) aiming at stealing or tampering data or corrupting network protocol usual routing behavior. This paper focuses on possible security attacks in VANETs and introduced the concept of intrusion detection system to combat against these attacks. It also discusses machine learning techniques for security in VANETs.
Authors and Affiliations
Priyanka Gulati, Kamal Gupta
Keywords
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