|Table of Contents|

Traffic anomaly detection method for vehicular ad-hoc networkflooding attack(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2020年04期
Page:
454-461
Research Field:
Publishing date:

Info

Title:
Traffic anomaly detection method for vehicular ad-hoc networkflooding attack
Author(s):
Li Yuan1Xie Yizhen2Wang Yongjian3Jiang Hong4
1.School of Information Engineering,Southwest University of Science and Technology,Mianyang 620010,China; 2.International College,Beijing University of Posts and Telecommunications,Beijing 100876,China; 3.National Computer Network and Information Securi
Keywords:
vehicular ad-hoc network flood attack traffic detection Hurst self-similarity
PACS:
TP393.1
DOI:
10.14177/j.cnki.32-1397n.2020.44.04.010
Abstract:
In order to effectively detect flooding attacks and mitigate the adverse effects of flooding attacks in VANET,this paper proposes a lightweight traffic anomaly detection method for flooding attacks in vehicular ad-hoc network(VANET). By using the Hurst self-similar parameter estimation method in the roadside unit(RSU)to calculate the self-similar change curve of the data traffic,this method can detect abnormal traffic and upload the packet information during the abnormal period to the Cloud.The cloud counts the packet sent by each node,and identifies the malicious node that initiates the flooding attacks by detecting the abnormal total data. The simulation results of the actual network traffic of VANET show that the traffic anomaly detection method can effectively detect malicious nodes under three types of flooding attacks intensity:low,medium and high.

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Last Update: 2020-08-30