A Novel Approach to Measure the Quality of Cluster and Finding Intrusions Using Intrusion Unearthing and Probability Clomp Algorithm
Azhagiri. M
Information Security Education Journal, Vol. 5, No. 1, 2018.
DOI: 10.6025/isej/2018/5/1/11-23
Link: http://www.dline.info/isej/fulltext/v5n1/isejv5n1_2.pdf
Abstract:
Objectives: Network security is used to monitor and prevent unauthorized access, deployment, enhancement, or
contradiction of a network of computers. Network security is a primary issue in processing on the grounds that numerous
assortments of assaults are expanding step by step. Despite the fact that, more number of research works were completed in
the past for system security yet at the same time there are numerous testing issues.
Methods/Statistical Analysis: To address the issues in the existing literature, the probability clomp algorithm has been
proposed to form the cluster and intrusion unearthing algorithm has been implemented among the clustering environment.
Findings: The execution of the proposed Intrusion Detection System (IDS) recognizes the interruption significantly more
successfully than the current frameworks. The quality of the cluster is measured with the help of attributes like precision and
entropy which is compared with the existing approach.
Application/Improvements: The proposed algorithm is able to achieve high observations and detection to overcome the
disadvantages of existing algorithm.