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
More filters
Journal ArticleDOI
Autoencoder Based Anomaly Detection for SCADA Networks
TL;DR: This paper proposes the use of autoencoders for unsupervised anomaly based intrusion detection using an appropriate differentiating threshold from the loss distribution and demonstrates improvements in results compared to other techniques for SCADA gas pipeline dataset.
Proceedings ArticleDOI
FANE: A Firewall Appliance for the Smart Home
Christoph Haar,Erik Buchmann +1 more
TL;DR: FANE, the concept for a Firewall AppliaNcE for Smart Home installations, is introduced and it is indicated that FANE can secure a wide range of IoT devices without requiring network-security expertise from the Smart Home user.
Journal ArticleDOI
WisdomNet: trustable machine learning toward error-free classification
Truong X. Tran,Ramazan S. Aygun +1 more
TL;DR: This paper develops a methodology for trustable learning and applies it to artificial neural networks and shows that it is possible to develop a classifier with 0% misclassification error, and proposes a novel neural network architecture named WisdomNet that could provide zero prediction error.
Proceedings ArticleDOI
Putting Together Wavelet-based Scaleograms and Convolutional Neural Networks for Anomaly Detection in Nuclear Reactors
TL;DR: This work presents a novel technique for anomaly detection on nuclear reactor signals through the combined use of wavelet-based analysis and convolutional neural networks, and indicates that the trained network achieves high levels of accuracy in failure detection, while at the same time being robust to noise.
Journal ArticleDOI
Industry 4.0 Implementation Challenges and Opportunities: A Technological Perspective
TL;DR: In this paper , the authors identify, codes, and defines the technological Industry 4.0 implementation challenges and identify main challenge themes important for system designers, and derive opportunities in the form of recommendations for overcoming current and future technological implementation challenges.
References
More filters
Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Collective dynamics of small-world networks
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Related Papers (5)
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
Robin Sommer,Vern Paxson +1 more