A Comparative Study of Diverse Intrusion Detection Methods using Machine Learning Techniques

V. Kathiresan, S. Karthik, Phani Kumar Katuri P. Divya, D. Palanivel Rajan

20222022 International Conference on Computer Communication and Informatics (ICCCI)21 citationsDOI

Abstract

Establishing robust and efficient intrusion detection systems (IDS) and Intrusion prevention systems (IPS) are inevitable in today's security world. The major role of IDS is detecting the anomaly in network traffic using effective methods. Machine learning techniques take a vital role in intrusion detection based on anomaly detection. This paper deals with the survey on machine learning techniques used in intrusion detection. The classification algorithms of machine learning like logistic regression, naïve Bayes, KNN, Decision Tree, Random Forest, and SVM are suitable for intrusion detection. This paper analyses the behaviour and properties of the machine learning-based classification techniques which is used for intrusion detection application.

Topics & Concepts

Intrusion detection systemComputer scienceMachine learningDecision treeArtificial intelligenceSupport vector machineAnomaly detectionAnomaly-based intrusion detection systemNaive Bayes classifierRandom forestNetwork securityIntrusionData miningComputer securityGeologyGeochemistryNetwork Security and Intrusion DetectionInternet Traffic Analysis and Secure E-votingAdvanced Malware Detection Techniques