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
Latency-Optimal Network Intelligence Services in SDN/NFV-Based Energy Internet Cyberinfrastructure
TL;DR: The work presented in this paper will aid the communication service providers (CSP) in providing a secure and low-latency SDN/NFV-based cyberinfrastructure for the EI ecosystem.
Proceedings ArticleDOI
Hawkware: Network Intrusion Detection based on Behavior Analysis with ANNs on an IoT Device
TL;DR: Hawkware is a novel IDS named Hawkware, a lightweight ANN-based distributed NIDS that runs on an IoT device and analyzes the device’s runtime behavior in tandem with its network traffic, able to replace expensive, deep data analysis that has traditionally been used to detect advanced attacks.
Journal ArticleDOI
Optimization of vector convolutional deep neural network using binary real cumulative incarnation for detection of distributed denial of service attacks
TL;DR: In this paper, a tuned vector convolutional deep neural network (TVCDNN) is proposed by optimizing the structure and parameters of the deep neural networks using binary and real cumulative incarnation (CuI), respectively.
Proceedings ArticleDOI
Machine Learning Based Web-Traffic Analysis for Detection of Fraudulent Resource Consumption Attack in Cloud
TL;DR: This paper proposes a novel scheme for the detection of the FRC attack on a cloud based web-server by dividing the web-pages into a number of quantiles based on their popularity index and training an Artificial Neural Network model.
Journal ArticleDOI
Rummage of Machine Learning Algorithms in Cancer Diagnosis
TL;DR: The aim in this article is to present an overview of machine learning and to cover various algorithms of machineLearning and their present implementation in the healthcare sector.
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