IEEE Transactions on Software Engineering - Special issue on computer security and privacy
Intrusion detection with neural networks
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Techniques of Cluster Algorithms in Data Mining
Data Mining and Knowledge Discovery
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Fuzzy Data Mining: Effect of Fuzzy Discretization
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fuzzy Rule Selection By Data Mining Criteria And Genetic Algorithms
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
ADMIT: anomaly-based data mining for intrusions
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
An Architecture for Intrusion Detection Using Autonomous Agents
ACSAC '98 Proceedings of the 14th Annual Computer Security Applications Conference
An immunological model of distributed detection and its application to computer security
An immunological model of distributed detection and its application to computer security
Intrusion detection using sequences of system calls
Journal of Computer Security
Weighting fuzzy classification rules using receiver operating characteristics (ROC) analysis
Information Sciences: an International Journal
A parallel genetic local search algorithm for intrusion detection in computer networks
Engineering Applications of Artificial Intelligence
Autonomous decision on intrusion detection with trained BDI agents
Computer Communications
A fuzzy-genetic approach to network intrusion detection
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
An efficient classifier to diagnose of schizophrenia based on the EEG signals
Expert Systems with Applications: An International Journal
Characterizing network traffic by means of the NetMine framework
Computer Networks: The International Journal of Computer and Telecommunications Networking
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
A Framework for Designing a Fuzzy Rule-Based Classifier
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
TOD: Temporal outlier detection by using quasi-functional temporal dependencies
Data & Knowledge Engineering
Design and analysis of genetic fuzzy systems for intrusion detection in computer networks
Expert Systems with Applications: An International Journal
Alert correlation in collaborative intelligent intrusion detection systems-A survey
Applied Soft Computing
Fuzzy data mining: a literature survey and classification framework
International Journal of Networking and Virtual Organisations
Policy-enhanced ANFIS model to counter SOAP-related attacks
Knowledge-Based Systems
A distributed hebb neural network for network anomaly detection
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
Intelligent network security assessment with modeling and analysis of attack patterns
Security and Communication Networks
gNIDS: rule-based network intrusion detection system using genetic algorithms
International Journal of Intelligent Systems Technologies and Applications
Discovering frequent itemsets on uncertain data: a systematic review
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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The purpose of the work described in this paper is to provide an intelligent intrusion detection system (IIDS) that uses two of the most popular data mining tasks, namely classification and association rules mining together for predicting different behaviors in networked computers. To achieve this, we propose a method based on iterative rule learning using a fuzzy rule-based genetic classifier. Our approach is mainly composed of two phases. First, a large number of candidate rules are generated for each class using fuzzy association rules mining, and they are pre-screened using two rule evaluation criteria in order to reduce the fuzzy rule search space. Candidate rules obtained after pre-screening are used in genetic fuzzy classifier to generate rules for the classes specified in IIDS: namely Normal, PRB-probe, DOS-denial of service, U2R-user to root and R2L-remote to local. During the next stage, boosting genetic algorithm is employed for each class to find its fuzzy rules required to classify data each time a fuzzy rule is extracted and included in the system. Boosting mechanism evaluates the weight of each data item to help the rule extraction mechanism focus more on data having relatively more weight, i.e., uncovered less by the rules extracted until the current iteration. Each extracted fuzzy rule is assigned a weight. Weighted fuzzy rules in each class are aggregated to find the vote of each class label for each data item.