Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
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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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A Survey of Deep Learning Methods for Cyber Security
TL;DR: This survey paper describes a literature review of deep learning methods for cyber security applications, including deep autoencoders, restricted Boltzmann machines, recurrent neural networks, generative adversarial networks, and several others.
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Deep Learning in Mobile and Wireless Networking: A Survey
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Toward Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions
TL;DR: In this paper, the authors present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission in the mMTC scenario and provide a detailed overview of the existing and emerging solutions toward addressing RAN congestion problem.
Journal ArticleDOI
Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review
TL;DR: A comprehensive study on the application of big data and machine learning in the electrical power grid introduced through the emergence of the next-generation power system—the smart grid (SG), with current limitations with viable solutions along with their effectiveness.
Journal ArticleDOI
An intrusion detection system for connected vehicles in smart cities
TL;DR: This work introduces an automated secure continuous cloud service availability framework for smart connected vehicles that enables an intrusion detection mechanism against security attacks and provides services that meet users’ quality of service (QoS) and quality of experience (QoE) requirements.
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