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
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems
TL;DR: In this paper, the authors identify and model the real capabilities and circumstances required by attackers to carry out feasible and successful adversarial attacks and highlight the limits and merits that can result in actual adversarial attack.
Proceedings ArticleDOI
Machine Learning Techniques for Classifying Network Anomalies and Intrusions
TL;DR: Two deep learning recurrent neural networks with a variable number of hidden layers, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), are employed and evaluated to help detect network intrusions.
Posted Content
Security for 4G and 5G Cellular Networks: A Survey of Existing Authentication and Privacy-preserving Schemes
Mohamed Amine Ferrag,Leandros A. Maglaras,Antonios Argyriou,Dimitrios Kosmanos,Helge Janicke +4 more
TL;DR: A comprehensive survey of authentication and privacy-preserving schemes for 4G and 5G cellular networks can be found in this paper, where the authors provide an overview of existing surveys that deal with 4G communications, applications, standardization, and security.
Proceedings ArticleDOI
ZeroWall: Detecting Zero-Day Web Attacks through Encoder-Decoder Recurrent Neural Networks
Ruming Tang,Zheng Yang,Zeyan Li,Weibin Meng,Haixin Wang,Qi Li,Yongqian Sun,Dan Pei,Tao Wei,Yanfei Xu,Yan Liu +10 more
TL;DR: In the evaluation using 8 real-world traces of 1.4 billion Web requests, ZeroWall successfully detects real zero-day attacks missed by existing WAFs and achieves high F1-scores over 0.98, which significantly outperforms all baseline approaches.
Journal ArticleDOI
CyberLearning: Effectiveness analysis of machine learning security modeling to detect cyber-anomalies and multi-attacks
Iqbal H. Sarker,Iqbal H. Sarker +1 more
TL;DR: This paper presents a machine learning-based cybersecurity modeling with correlated-feature selection, and a comprehensive empirical analysis on the effectiveness of various machine learning based security models.
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