Summary
Internet of Vehicles is recorded as an ever growing area for connected vehicles to exchange their information with other vehicles using vehicle‐to‐vehicle communication. Vehicle‐to‐vehicle communication is possible by forming vehicular ad hoc networks, with the help of roadside units using vehicle‐to‐roadside communications in the network. Internet of networks has many advantages such as road safety, traffic management, and sharing information on daily traffic and updating traffic information. For example, the Internet of Vehicles can be used to reduce traffic and deaths occurring due to road accidents, to reduce the fuel needed, and to reduce travel time. Interconnected vehicles rapidly learn about road conditions and traffic and respond to the driver; thus, necessary actions are taken. However, the attacker can modify the information in the connected vehicles and, thus, creates problem on the road. Data fascination is one of the main attacks on connected vehicles where connected vehicles take action based on information from the other vehicle. In this paper, first, a model has been proposed to detect the data fascination attack using the hashing technique to enhance the security in the interconnected vehicles by adjusting the size of the contention window to transfer original information to other interconnected vehicles at the correct time. Second, a model has been suggested to reduce the travel time in case of traffic congestion. The efficiency of the proposed model is checked using numerical methods obtained from the simulation results. From the obtained results, the proposed approach prevents data fascination attacks in interconnected vehicles and provides high throughput with lower delay.
Wireless sensor network is dynamic and follows multi-hop based communication, it is essential to provide an IDS software to avoid malicious behavior and data loss. The existing software like packet sniffer can sniff all or just parts of the traffic from a single node in the network. A few methods were proposed to avoid traffic narrowing using switches to gain access to traffic from other systems on the network but it is taking more time and cost. This paper discussed an Optimized Trust Based Traffic Analyzer (OOTBTA) for wireless sensor networks in order to provide an efficient intrusion detection system where the optimum trusted traffic is obtained by Genetic Algorithm. OOTBTA used as optimal intrusion detection system where it focuses on the packet sniffing and its working only for best trusted nodes in the network. OOTBTA observe the working behavior, packet format, timing and mainly optimally whether the nodes are trusted nodes or not. The simulation of OOTBTA is carried out in Network Simulation software and the results are compared with the existing IDS such as LBIDS and DAD results to evaluate the performance.
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