Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Brief Review onDifferent Machine Learning-Based Intrusion Detection Systems Subject The topic of the resource Decision tree algorithm; Intrusion detection; kNN algorithm; Random Forest algorithm; Support vector Machine algorithm Description An account of the resource In the contemporary cybersecurity landscape, the proliferation of complex and sophisticated cyber threats necessitates the development of robust Intrusion Detection Systems (IDS) for safeguarding network infrastructures. These threats make it more challenging to maintain the communitys availability, integrity, and confidentiality. To ensure a secure network, community administrators should implement multiple intrusion detection systems (IDS) to monitor and detect unauthorized and malicious activities. An intrusion detection system examines the networks traffic by analyzing data flowing through computers to identify potential security threats or malicious activities. It alerts administrators when suspicious activities are detected. IDS generally performs two types of malicious activity detection: misuse or signature-based detection, which entails collecting and comparing information to a database of known attack signatures, and anomaly detection, which detects any behavior that differs from the standard activity and assumes it to be malicious. The proposed paper offers an overview of how different Machine Learning Algorithms like Random forest, k - Nearest Neighbor, Decision tree, Support Vector Machine, Naive Bayes, and K- means are used for IDS and how these algorithms perform on different well-known datasets, and Their accuracy and performance are evaluated and compared, providing valuable insights for future work. kNN shows an accuracy of 90.925% for Denial of Service Attacks and 98.244% for User To Root attacks. The SVM algorithm shows an accuracy of 93.051% for Probe attacks and 80.385% accuracy for remote-to-local attacks. According to our implementation, these two algorithms work better than the others. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Samanta S.; Sen A.P.; Mukhopadhyay D.; De S.; Bhattacharyya S.; Platos J. Source A related resource from which the described resource is derived Lecture Notes on Data Engineering and Communications Technologies, Vol-220, pp. 98-108. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-71619-5_10" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-71619-5_10</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207871773&amp;doi=10.1007%2F978-3-031-71619-5_10&amp;partnerID=40&amp;md5=dd173c2d39c093bc97bbf56781c64b64" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207871773&amp;doi=10.1007%2f978-3-031-71619-5_10&amp;partnerID=40&amp;md5=dd173c2d39c093bc97bbf56781c64b64</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23674512 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Samanta S., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Sen A.P., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Mukhopadhyay D., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bangalore, India; De S., Department of Computer Science and Engineering, Cooch Behar Government Engineering College, West Bengal, Cooch Behar, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic, Algebra University, Zagreb, Croatia; Platos J., VSB Technical University of Ostrava, Ostrava, Czech Republic