A triangle area based nearest neighbors approach to intrusion detection
Pattern Recognition
CARRADS: Cross layer based adaptive real-time routing attack detection system for MANETS
Computer Networks: The International Journal of Computer and Telecommunications Networking
A new approach to intrusion detection using Artificial Neural Networks and fuzzy clustering
Expert Systems with Applications: An International Journal
Environmental Modelling & Software
Expert Systems with Applications: An International Journal
Design and analysis of genetic fuzzy systems for intrusion detection in computer networks
Expert Systems with Applications: An International Journal
Short communication: Ten guidelines for effective data visualization in scientific publications
Environmental Modelling & Software
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Expert Systems with Applications: An International Journal
Decision tree based light weight intrusion detection using a wrapper approach
Expert Systems with Applications: An International Journal
A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier
Expert Systems with Applications: An International Journal
Advanced probabilistic approach for network intrusion forecasting and detection
Expert Systems with Applications: An International Journal
Review: Intrusion detection system: A comprehensive review
Journal of Network and Computer Applications
Review Article: RePIDS: A multi tier Real-time Payload-based Intrusion Detection System
Computer Networks: The International Journal of Computer and Telecommunications Networking
A novel hybrid intrusion detection method integrating anomaly detection with misuse detection
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this paper, a four-angle-star based visualized feature generation approach, FASVFG, is proposed to evaluate the distance between samples in a 5-class classification problem. Based on the four angle star image, numerical features are generated for network visit data from KDDcup99, and an efficient intrusion detection system with less features is proposed. The FASVFG-based classifier achieves a high generalization accuracy of 94.3555% in validation experiment, and the average Mathews correlation coefficient reaches 0.8858.