Intelligent Reputation System for Safety Messages in VANET
This addresses security issues in VANET to prevent hazardous situations and loss of life, but appears incremental as it builds on existing reputational systems.
The paper tackles the problem of falsified safety messages in Vehicle Ad-hoc Networks (VANET) by proposing an Intelligent Reputation System (IRS) that identifies attacking vehicles using a multi-parameter Greedy Best First algorithm, resulting in enhanced safety levels and superior performance compared to other reputational systems.
Nowadays, Vehicle Ad - hoc Nets (VANET) applications have become very important in our lives because VANET provides drivers with safety messages, warnings, and instructions to ensure drivers have a safe and enjoyable journey. VANET Security is one of the hottest topics in computer networks research, Falsifying VANET system information violates VANET safety objectives and may lead to hazardous situations and loss of life. In this paper, an Intelligent Reputation System (IRS) aims to identify attacking vehicles will be proposed; the proposed system will rely on opinion generation, trust value collection, traffic analysis, position based, data collection, and intelligent decision making by utilizing the multi-parameter Greedy Best First algorithm. The results of this research will enhance VANET's safety level and will facilitate the identification of misbehaving vehicles and their messages. The results of the proposed system have also proven to be superior to other reputational systems.