Add to ORKGAbstract: In this paper we have proposed an evolutionary algorithm to induct fuzzy classification rules. The algorithm uses an ant colony optimization based local searcher to improve the quality of final fuzzy classification system. The proposed algorithm is performed on Intrusion Detection as a high-dimensional classification problem. Results show that the implemented evolutionary ACO-Based algorithm is capable of producing a reliable fuzzy rule-based classifier for intrusion detection
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
An evolutionary fuzzy rule-learning algorithm is proposed in this paper. This algorithm utilizes a P...
An Intrusion Detection System should optimally be capable of detecting both known attacks (misuse de...
An Intrusion Detection System should optimally be capable of detecting both known attacks (misuse de...
ABSTRACT This paper presents a method for constructing intrusion detection systems based on efficie...
The quantity of network attacks and the harm from them is constantly increasing, so the detection of...
Fuzzy logic based methods together with the techniques from Artificial Intelligence have gained impo...
Abstract—Fuzzy sets and fuzzy logic can be used for efficient data classification by fuzzy rules and...
Abstract — This paper describes the generation of fuzzy signatures to detect some cyber attacks. Thi...
In this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. Th...
As information technology grows, network security is a significant issue and challenge. The intrusio...
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. T...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
An evolutionary fuzzy rule-learning algorithm is proposed in this paper. This algorithm utilizes a P...
An Intrusion Detection System should optimally be capable of detecting both known attacks (misuse de...
An Intrusion Detection System should optimally be capable of detecting both known attacks (misuse de...
ABSTRACT This paper presents a method for constructing intrusion detection systems based on efficie...
The quantity of network attacks and the harm from them is constantly increasing, so the detection of...
Fuzzy logic based methods together with the techniques from Artificial Intelligence have gained impo...
Abstract—Fuzzy sets and fuzzy logic can be used for efficient data classification by fuzzy rules and...
Abstract — This paper describes the generation of fuzzy signatures to detect some cyber attacks. Thi...
In this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. Th...
As information technology grows, network security is a significant issue and challenge. The intrusio...
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. T...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
This paper shows how a small number of fuzzy rules can be selected for designing interpretable fuzzy...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...
We describe the generation of fuzzy signatures to detect some cyber attacks. This approach is an enh...