Autonomous vehicles are cars that drive autonomously and safely to their destination. Autonomous vehicles offer driver convenience but can also be used as an attack tool to cause accidents. The attacker can infiltrate the controller area network exchanging information of the electronic control unit of the autonomous vehicles and take control of the vehicle's movement. As a result, the attacked autonomous vehicles may drive abnormally and cause an accident. In addition, an attacker can try various attacks such as a denial of service attack that sends many unnecessary packets to autonomous vehicles and paralyzes the network, and a replay attack that continuously sends old information that does not match the current road conditions. These attacks can cause vehicles accidents without infiltrative the controller area network controllers of autonomous vehicles. This paper proposes a countermeasure to denial of service attacks on autonomous vehicles, which uses the autonomous vehicles speed information sensed by sensor nodes of wireless sensor networks. In the event of an accident, for example, the autonomous vehicles detect a denial of service attack by comparing the information calculated at the base station with the Autonomous vehicles’ own information. The autonomous vehicles maintain speed based on the information received from the base station. Then the base station communicates with the infrastructure based on the road condition information received from the wireless sensor networks sensor nodes. This allows the infrastructure to control the roads and prevent further accidents. This paper shows that the WSN-based IoT can be modeled and simulated based on discrete event systems to cope with denial of service attacks on autonomous vehicles, enabling them to operate normally and safely.
CITATION STYLE
Chung*, W. J., & Cho*, T. H. (2019). Modeling and Simulation of DoS Attack Response in WSN based IoT. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 9525–9532. https://doi.org/10.35940/ijrte.d9905.118419
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