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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Proceedings ArticleDOI
MalPhase: Fine-Grained Malware Detection Using Network Flow Data
TL;DR: In this paper, a multi-phase pipeline for malware detection, type and family classification is presented, which uses an extended set of network flow features and a simultaneous multi-tier architecture facilitates a performance improvement for deep learning models.
Journal ArticleDOI
Optimal Packet Camouflage Against Traffic Analysis
TL;DR: In this paper, the authors proposed a system that optimally prevents traffic feature leaks by mutating the packet lengths of a source app to those lengths from the target app having similar bin probability.
Book ChapterDOI
A Hybrid Deep Learning Ensemble for Cyber Intrusion Detection
TL;DR: In this article, a hybrid intrusion detection system (IDS) consisting of a 2-dimensional Convolutional Neural Network (2-D CNN), a RNN and a Multi-Layer Perceptron (MLP) was proposed.
Journal ArticleDOI
Distance-based classifier on the Quantum Inspire
TL;DR: A recently proposed distance-based classifier is extended and given explicit quantum circuit implementations, and a method to overcome restrictions on the data is given, present in the original work.
Book ChapterDOI
A Review on Network Intrusion Detection System Using Machine Learning
T. Rupa Devi,Srinivasu Badugu +1 more
TL;DR: A research method is provided that can be applied to develop a better network intrusion detection system and is compared to all the research papers specifying their merits and demerits.
References
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