Distributed representation of fuzzy rules and its application to pattern classification
Fuzzy Sets and Systems
Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
The base-rate fallacy and the difficulty of intrusion detection
ACM Transactions on Information and System Security (TISSEC)
Practical Intrusion Detection Handbook
Practical Intrusion Detection Handbook
Three objective genetics-based machine learning for linguisitc rule extraction
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Finding fuzzy classification rules using data mining techniques
Pattern Recognition Letters
The Case against Accuracy Estimation for Comparing Induction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Using Artificial Anomalies to Detect Unknown and Known Network Intrusions
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
A Neural Network Component for an Intrusion Detection System
SP '92 Proceedings of the 1992 IEEE Symposium on Security and Privacy
USTAT: A Real-Time Intrusion Detection System for UNIX
SP '93 Proceedings of the 1993 IEEE Symposium on Security and Privacy
Anomaly detection of web-based attacks
Proceedings of the 10th ACM conference on Computer and communications security
Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
Intrusion detection using a fuzzy genetics-based learning algorithm
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
A study in using neural networks for anomaly and misuse detection
SSYM'99 Proceedings of the 8th conference on USENIX Security Symposium - Volume 8
Incorporating soft computing techniques into a probabilistic intrusion detection system
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An artificial immune system architecture for computer securityapplications
IEEE Transactions on Evolutionary Computation
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
Hybridization of fuzzy GBML approaches for pattern classification problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Training a neural-network based intrusion detector to recognize novel attacks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Evolutionary computing for knowledge discovery in medical diagnosis
Artificial Intelligence in Medicine
Adaptive fuzzy rule-based classification systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A fuzzy-genetic approach to network intrusion detection
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
A triangle area based nearest neighbors approach to intrusion detection
Pattern Recognition
Review: Intrusion detection by machine learning: A review
Expert Systems with Applications: An International Journal
Review: The use of computational intelligence in intrusion detection systems: A review
Applied Soft Computing
Discovery and prevention of attack episodes by frequent episodes mining and finite state machines
Journal of Network and Computer Applications
Proceedings of the 2010 ACM Symposium on Applied Computing
Genetic algorithms for delays evaluation in networked automation systems
Engineering Applications of Artificial Intelligence
Approach based ensemble methods for better and faster intrusion detection
CISIS'11 Proceedings of the 4th international conference on Computational intelligence in security for information systems
An efficient local region and clustering-based ensemble system for intrusion detection
Proceedings of the 15th Symposium on International Database Engineering & Applications
Engineering Applications of Artificial Intelligence
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The security of networked computers plays a strategic role in modern computer systems. This task is so complicated because the determination of normal and abnormal behaviors in computer networks is hard, as the boundaries cannot be well defined. One of the difficulties in such a prediction process is the generation of false alarms in many anomaly based intrusion detection systems. However, fuzzy logic is an important solution to reduce the false alarm rate in determining intrusive activities. This paper proposes a parallel genetic local search algorithm (PAGELS) to generate fuzzy rules capable of detecting intrusive behaviors in computer networks. The system uses the Michigan's approach, where each individual represents a fuzzy rule which has the form ''if condition then prediction.'' In the presented algorithm the global population is divided into some subpopulations, each assigned to a distinct processor. Each subpopulation consists of the same class fuzzy rules. These rules evolve independently in the proposed parallel manner. Experimental results show that the presented algorithm produces fuzzy rules, which can be used to construct a reliable intrusion detection system.