Performance Evaluation of PCA Filter In Clustered Based Intrusion Detection System

Shirbhate, S. V.; Sherekar, S. S.; Thakare, V. M.

doi:10.1109/icesc.2014.100

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Shirbhate et al [2014] : The study, analysis clustering is one of the needs for machine learning algorithms to be useful to large scale data and exploration of recent Development of data mining application such as classification and will lead to obtain the direction of future research.. The aim methods for a set of large data are to investigate the performance of different clustering.…”

Section: Connection Session Recordmentioning

confidence: 99%

“…Cloud infrastructure consumes enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions [11].…”

Section: H Energy Costmentioning

confidence: 99%

“…Intrusion the computers from unauthorized or malicious actions detection system protects the computers from unauthorized or malicious actions. [11]. D. Nadya El MOUSSAID et al [2015]: At that time to discriminate between the genuine packets and the dose packets a filter methodology was used.…”

Section: Connection Session Recordmentioning

confidence: 99%

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Anomaly and Missuses Detection Using IDS Technique

Devi¹

2017

IJRASET

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In the recent years, as the second line of defense after firewall, the intrusion detection technique has got fast development. a mixture of data mining techniques such as clustering, categorization and association rule detection are being used for intrusion detection This research proposed IDS using cloud computing by integrated signature based (Snort) with abnormality based (Naive Bayes) to enhance system security to detect attacks. This research used Knowledge Discovery Data Mining (KDD) CUP 20 dataset and Waikato Environment for Knowledge Analysis (WEKA) program for testing the proposed hybrid IDS. Accuracy, detection rate, time to construct model and false alarm rate were used as parameters to evaluate performance with Naïve Bayes, Snort with J48graft and Snort

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Section: Connection Session Recordmentioning

confidence: 99%

“…Cloud infrastructure consumes enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions [11].…”

Section: H Energy Costmentioning

confidence: 99%