DDoS Malicious Node Detection by Jaccard and Page Rank Algorithm in Cloud Environment
|© 2021 by IJCTT Journal|
|Year of Publication : 2021|
|Authors : Adil Hussain Mohammed|
|DOI : 10.14445/22312803/IJCTT-V69I5P108|
How to Cite?
Adil Hussain Mohammed, "DDoS Malicious Node Detection by Jaccard and Page Rank Algorithm in Cloud Environment," International Journal of Computer Trends and Technology, vol. 69, no. 5, pp. 55-59, 2021. Crossref, https://doi.org/10.14445/22312803/IJCTT-V69I5P108
Cloud infrastructure increases the strength of service and product based companies by serving more users with limited infrastructure. Many of researcher are working to improve the security of vulnerable cloud infrastructure. This paper has proposed a trust based model for detection of DDoS attacked malicious nodes in the network. Based on node resource uses in the network a belief was developed by the cloud bridge. Further paper evaluates jaccard coefficient trust value based on transaction happens between nodes. This jaccard coefficient is social feature calculate as per node behavior with all other nodes. Finally a cumulative trust was estimate by page rank method using jaccard and initial belief model. Experiment was done on DDoS attack network. Result shows that proposed model has increases the malicious node detection.
Cloud computing, Jaccard Coefficient, Page Rank, Classification, Trust Model.
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