Title
Collaborative security attack detection in software-defined vehicular networks.
Abstract
Vehicular ad hoc networks (VANETs) are taking more attention from both the academia and the automotive industry due to a rapid development of wireless communication technologies. And with this development, vehicles called connected cars are increasingly being equipped with more sensors, processors, storages, and communication devices as they start to provide both infotainment and safety services through V2X communication. Such increase of vehicles is also related to the rise of security attacks and potential security threats. In a vehicular environment, security is one of the most important issues and it must be addressed before VANETs can be widely deployed. Conventional VANETs have some unique characteristics such as high mobility, dynamic topology, and a short connection time. Since an attacker can launch any unexpected attacks, it is difficult to predict these attacks in advance. To handle this problem, we propose collaborative security attack detection mechanism in a software-defined vehicular networks that uses multi-class support vector machine (SVM) to detect various types of attacks dynamically. We compare our security mechanism to existing distributed approach and present simulation results. The results demonstrate that the proposed security mechanism can effectively identify the types of attacks and achieve a good performance regarding high precision, recall, and accuracy.
Year
Venue
Keywords
2017
Asia-Pacific Network Operations and Management Symposium-APNOMS
Software-defined vehicular cloud,security,support vector machine
Field
DocType
ISSN
Wireless,Computer security,Computer science,Support vector machine,Computer network,Security service,Software,Cloud computing security,Wireless ad hoc network,Vehicular ad hoc network,Automotive industry
Conference
2576-8565
Citations 
PageRank 
References 
1
0.35
11
Authors
5
Name
Order
Citations
PageRank
Myeongsu Kim1221.98
Insun Jang2426.44
Sukjin Choo3171.89
Jungwoo Koo421.03
Sangheon Pack5913117.20