Abstract
As the increasing popularity and development of the Internet of Vehicles (IoV), it is important to ensure the reliability and safety for IoV. However, communicating in an open-access environment makes road safety, communication security and privacy issues facing great challenges. Also, the high requirement of real-time detection and reponse to the security issues makes edge detection a more and more important research subject. Among all the challenges, Sybil Denial of Service (DoS) Attack is one of the most severe threats to the IoV safety, which can lead to traffic jams and other safety issues. In this paper, we introduce a Real-Time Edge Detection Scheme for Sybil DDoS in IoV. We use the entropy theory to quantify the traffic distribution, and further design an algorithm named Fast Quartile Deviation Check (FQDC) to recognize and locate the attack. Furthermore, because of the calculation limit in IoV scenarios, we also optimize the calculation with some useful techniques, such as the optimized sliding window, the incremental calculation of entropy values and make it suitable for the IoV environment. Finally, we proposed a temporal index. Temporal False Omission Rate (TFOR), to measure the performance of response speed and omission rate. In our evaluation, we successfully detect all the Sybil DDoS attacks provided in the F2MD datasets, and have the average alarm delay of 4.9193 seconds, and the average TFOR of 1.6024%.
Highlights
The security research in the Internet of Vehicles (IoV) environment is becoming a more and more active subject and researching area, aiming at reducing accidents and improving road safety
IoV is a special branch of the Internet of Things (IoT) [1], [2], which helps maintain the traffic by using modern electronic devices and information tenologies, and implements more effective traffic management and accident avoidance
We introduced a real-time edge detection scheme for Sybil DDoS in the IoV based on entropy theory
Summary
The security research in the Internet of Vehicles (IoV) environment is becoming a more and more active subject and researching area, aiming at reducing accidents and improving road safety. DDoS is the most popular and effective method to take over a IoV, which is the same with the situation in traditional network. J. Li et al.: RTED-SD: A Real-Time Edge Detection Scheme for Sybil DDoS in the IoV. We introduced a real-time edge detection scheme for Sybil DDoS in the IoV based on entropy theory. We designed an optimized calculation algorithm in [24] to simplify the entropy calculation in DDoS detection in traditional software designed network, and further revise the algorithm suitable for IoV scenario, and the low response time alse meets the demand of fast edge detection [4], [8], [9]. Our detection scheme can help recognize Sybil DDoS just on the edge of every seperate IoV area, without any central support saving the response time and calculation power.
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