Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
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.read more
Citations
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Journal ArticleDOI
Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends
TL;DR: A novel taxonomy to classify existing IN-based ADSs and a discussion of open problems in the field of Big Data ADSs for INs that can lead to further development are presented.
Proceedings ArticleDOI
SoK: exploring the state of the art and the future potential of artificial intelligence in digital forensic investigation
Xiaoyu Du,Christopher Hargreaves,John Sheppard,Felix Anda,Asanka Sayakkara,Nhien-An Le-Khac,Mark Scanlon +6 more
TL;DR: In this article, the authors summarized existing artificial intelligence-based tools and approaches in digital forensics and highlighted the current challenges and future potential impact of artificial intelligence in digital forensic analysis.
Journal ArticleDOI
A Survey of Deep Learning Techniques for Cybersecurity in Mobile Networks
TL;DR: This paper presents a comprehensive survey of recent cybersecurity works that use DL in mobile and wireless networks, and identifies the most effective DL methods for the different threats and attacks.
Journal ArticleDOI
Machine Learning for Traffic Analysis: A Review
Nour Alqudah,Qussai Yaseen +1 more
TL;DR: A review of the techniques used in the traffic analysis is presented and different machine learning approaches for traffic analysis are discussed.
Journal ArticleDOI
Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction.
TL;DR: In this paper, a taxonomy of authentication and authorization schemes in IoT focusing on machine learning-based schemes is presented, and various criteria to achieve a high degree of AA resiliency in IoT implementations to enhance IoT security are evaluated.
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