Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
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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
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Change Point Models for Real-time V2I Cyber Attack Detection in a Connected Vehicle Environment
TL;DR: This study investigated the efficacy of two change point models, Expectation Maximization (EM) and Cumulative Sum (CUSUM), for real-time V2I cyber attack detection in a CV Environment and revealed that EM and CUSUM could detect these cyber attacks, DOS, impersonation, and false information, with an accuracy of 99, 100, and 98.
Proceedings ArticleDOI
Behavior-Aware Network Segmentation using IP Flows
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Proceedings ArticleDOI
Wart Treatment Selection with a Decision Tree-Based Approach
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TL;DR: The proposed decision tree based algorithm gave a good accuracy result in both treatment methods while predictive values in ROC Curves were very high which could help the physicians to select optimum treatment related to patient attributes, and time and cost will be saved for both physicians and patients.
Journal ArticleDOI
The Supply of Rural Public Cultural Services Relying on Data Mining Technology under the Rural Revitalization Strategy
TL;DR: In this article , the authors take advantage of the data mining technology under the platform of big data to gather data related to rural public cultural services and present the existing problems and countermeasures.
Journal ArticleDOI
Data Mining in the Analysis of Tree Harvester Performance Based on Automatically Collected Data
TL;DR: In this article , the authors used data from two mid-sized harvesters working in north-eastern Poland were analyzed using classical regression (linear and logarithmic), cluster analysis (dendrograms and k-means) and Principal Component Analysis (PCA).
References
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