FuGeIDS: Fuzzy Genetic paradigms in Intrusion Detection Systems
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Summary
Two major machine learning paradigms used in Intrusion Detection System, Genetic Algorithms and Fuzzy Logic and how to apply them for intrusion detection are looked at.
- Type
- preprint
- Published
- 2012-04-28
- Cited by
- 23
- References
- 52
- Access
- Open access
- OpenAlex
- https://openalex.org/W1496376327
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1740593
Keywords
Intrusion detection system, Anomaly-based intrusion detection system, Intrusion prevention system, Countermeasure, Computer science
References
- FUZZY DATA MINING AND GENETIC ALGORITHMS APPLIED TO INTRUSION DETECTION
- Applying Genetic Programming to Intrusion Detection
- Evolving Fuzzy Classifiers for Intrusion Detection
- RISM - Reputation Based Intrusion Detection System for Mobile Ad hoc Networks
- A Novel Multipath Approach to Security in Mobile Ad Hoc Networks (MANETs)
- State of the Practice of Intrusion Detection Technologies
- Genetic Programming Approach for Multi-Category Pattern Classification Applied to Network Intrusions Detection
- Security Scheme for Distributed DoS in Mobile Ad Hoc Networks
- A software implementation of a genetic algorithm based approach to network intrusion detection
- Steganography and Steganalysis: Different Approaches
- Jigsaw-based secure data transfer over computer networks
- Fuzzy network profiling for intrusion detection
- A practical guide to biometric security technology
- Intrusion detection using a fuzzy genetics-based learning algorithm
- CompChall: addressing password guessing attacks
- A parallel genetic local search algorithm for intrusion detection in computer networks
- A new protocol to counter online dictionary attacks
- A distributed security scheme for ad hoc networks
- Detecting new forms of network intrusion using genetic programming
- The N/R one time password system
Cited by
- A Propose Neuro-Fuzzy-Genetic Intrusion Detection System
- A Review of Machine Learning based Anomaly Detection Techniques
- Host based Anomaly Detection using Fuzzy Genetic Approach (FGA)
- Evolving CSP Algorithm in Predicting the Path Loss of Indoor Propagation Models
- REFERENTIAL DISSECTION OF ANOMALY OPTIMIZATION TECHNIQUES
- An Intrusion Detection System Based on NSGA-II Algorithm
- Performance Comparison of Host based and Network based Anomaly Detection using Fuzzy Genetic Approach (FGA)
- Network intrusion detection using equality constrained-optimization-based extreme learning machines
- Computer and Network Security: Ontological and Multi-agent System for Intrusion Detection
- Fuzzy Approach for Intrusion Detection System: A Survey
- Improving the Efficiency of IDPS by using Hybrid Methods from Artificial Intelligence
- КЛАСТЕРИЗАЦІЯ ОЗНАК МЕРЕЖЕВИХ АТАК В ЗАДАЧАХ АНАЛІЗУ ЗАХИЩЕНОСТІ ІНФОРМАЦІЇ
- Improving the Performance of Intrusion Detection Systems Using the Development of Deep Neural Network Parameters
- Detection of Communication Network Intruders Using Artificial Neural Networks
- Mitigating Zero-Day Vulnerabilities in IIoT Systems: Challenges and Advances in AI-Powered Intrusion Detection Systems
- Machine Learning Techniques to Detect Anomalies in Surveillance Videos: Review
- Intrusion Detection with Genetic Algorithms and Fuzzy Logic
- A Survey on Machine Learning Techniques for Intrusion Detection Systems
- Network Intrusion Detection System Using Soft Computing Technique—Fuzzy Logic Versus Neural Network: A Comparative Study
- NETWORK INTRUSION DETECTION SYSTEM USING FUZZY IF-THEN RULES AND FUZZY REASONING: A SOFT COMPUTING TECHNIQUE
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