COMPARITIVE ANALYSIS OF MACHINE LEARNING ALGORITHM FOR ANOMALY DETECTION: A LITERATURE SURVEY

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Manohar Vemula; Shaik Balasaidulu

COMPARITIVE ANALYSIS OF MACHINE LEARNING ALGORITHM FOR ANOMALY DETECTION: A LITERATURE SURVEY

Authors: Manohar Vemula, Shaik Balasaidulu

Unique Paper ID: 147169
Volume: 5
Issue: 5
PageNo: 114-117

Keywords: Intrusion detection KDD Cup 99 dataset.

Abstract:
Intrusion detection system used to discover illegal and avoidable activities at accessing or manipulating computer system. To improve system correctness and decrease false positive rate based on DARPA 98 and later the updated version which shoes some arithmetic issues, researcher focuses on various dataset. Manu researchers give their efforts to explore the dataset by different techniques. In this paper machine learning based methods which are one of the types of anomaly detection, techniques are discussed.

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ISSN: 2349-6002
Volume: 5
Issue: 5
PageNo: 114-117

COMPARITIVE ANALYSIS OF MACHINE LEARNING ALGORITHM FOR ANOMALY DETECTION: A LITERATURE SURVEY

Available:https://ijirt.org/article?manuscript=147169

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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