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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Book ChapterDOI
A Toolset for Intrusion and Insider Threat Detection
TL;DR: This work argues that incorporating expert knowledge and previous flows allow us to create more meaningful attributes for subsequent analysis methods, and tries to detect novel attacks while simultaneously limiting the number of false positives.
Journal ArticleDOI
Applications of machine learning methods in port operations – A systematic literature review
TL;DR: In this paper , a comprehensive systematic literature review on machine learning for port decision-making is presented to analyze the previous research from different perspectives such as area of the application, type of application, machine learning method, data, and location of the study.
Proceedings ArticleDOI
PcapGAN: Packet Capture File Generator by Style-Based Generative Adversarial Networks
TL;DR: The proposed PcapGAN that can augment pcap data, a kind of network data, includes an encoder, a data generator, and a decoder, which demonstrates the similarity between the generated data and original data, and validation of thegenerated data by increased performance of intrusion detection algorithms.
Journal ArticleDOI
AppCon: Mitigating Evasion Attacks to ML Cyber Detectors
Giovanni Apruzzese,Mauro Andreolini,Mirco Marchetti,Vincenzo Giuseppe Colacino,Giacomo Russo +4 more
TL;DR: The results demonstrate the effectiveness of AppCon in mitigating the dangerous threat of adversarial attacks in over 75% of the considered evasion attempts, while not being affected by the limitations of existing countermeasures, such as performance degradation in non-adversarial settings.
Posted Content
Efficient Learning of Discrete Graphical Models
TL;DR: In this paper, the authors provide a sample-efficient method based on the interaction screening framework that allows one to learn fully general discrete factor models with node-specific discrete alphabets and multi-body interactions.
References
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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.
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