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Journal ArticleDOI

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

TLDR
The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.
Abstract
This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection. Short tutorial descriptions of each ML/DM method are provided. Based on the number of citations or the relevance of an emerging method, papers representing each method were identified, read, and summarized. Because data are so important in ML/DM approaches, some well-known cyber data sets used in ML/DM are described. The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/DM for cyber security is presented, and some recommendations on when to use a given method are provided.

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Proceedings ArticleDOI

Impact of Machine Learning in Various Network Security Applications

TL;DR: This paper represents a converged exposition of machine learning approach on various network security applications specifying the possible future scope and detailed outcome of the researches on the basis of intrusion detection, analysis of malware behavior, internet traffic classification, and other security aspects.
Journal ArticleDOI

A Comparative Study on Cyber Threat Intelligence: The Security Incident Response Perspective

TL;DR: This study examines the broader security incident response perspective from a standardization perspective, introducing 18 core concepts and providing a detailed analysis of 6 incident response formats.
Journal ArticleDOI

Intrusion detection based on Machine Learning techniques in computer networks

TL;DR: A comprehensive survey of ML-based intrusion detection approaches presented in the literature in the last ten years can be found in this article, where the authors present a comprehensive critical survey of machine learning techniques used for intrusion detection.
Journal ArticleDOI

Adaptive security-related data collection with context awareness

TL;DR: The proposed collector solves the issue of heterogeneity of network system by designing a Security-related Data Description Language (SDDL) to instruct security related data collection in various networking contexts and applies adaptive sampling algorithms to reduce the amount of collected data.
Journal ArticleDOI

A survey on analysis and detection of Android ransomware

TL;DR: This article provides a comprehensive survey on analysis and detection methods for Android ransomware since its beginning (2015) till date (2020); but also presents observations and suggestions for researchers and practitioners to carry out further research.
References
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Journal ArticleDOI

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