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
In-depth Comparative Evaluation of Supervised Machine Learning Approaches for Detection of Cybersecurity Threats
TL;DR: The work detailed in this paper establishes a novel supervised machine learning performance baseline for CICIDS2017, a modern, labeled data set for testing intrusion detection systems.
Journal ArticleDOI
A Novel Intrusion Detection Approach Using Machine Learning Ensemble for IoT Environments
Parag Verma,Ankur Dumka,Rajesh Singh,Alaknanda Ashok,Anita Gehlot,Praveen Malik,Gurjot Singh Gaba,Mustapha Hedabou +7 more
TL;DR: In this paper, a binary classifier approach developed from a machine learning ensemble method to filter and dump malicious traffic to prevent malicious actors from accessing the IoT network and its peripherals is proposed.
Journal ArticleDOI
Managing Information System Security Under Continuous and Abrupt Deterioration
TL;DR: This study focuses on the maintenance of an intrusion detection system (IDS) that attempts to discriminate between benign and malicious traffic arriving at a firm, and proves the existence of a steady‐state level of discrimination ability that firms should strive to reach and maintain.
Proceedings ArticleDOI
Fast Intra Prediction Mode Decision for HEVC Using Random Forest
TL;DR: This paper extracted specific image features that represent CU texture, incorporate a machine learning technique, namely random forest, in HEVC intra prediction mode selection, to improve the performance of intra coding of HEVC.
Journal ArticleDOI
Risk Data Analysis of Cross Border E-commerce Transactions Based on Data Mining
Haohua Qing,Guokai Zheng,Die Fu +2 more
TL;DR: This paper establishes the risk data analysis of cross-border e-commerce transactions based on data mining, and analyzes the test values of neural network algorithm, seizure rate and inspection rate to achieve the goal of preventing and controlling the maximum risk with the lowest data mining cost.
References
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