Intrusion Detection in Agent-Based Virtual Knowledge Communities

Ogunleye, Gabriel Opeyemi; Ogunde, Adewale Opeoluwa

doi:10.5539/cis.v3n3p203

Cited by 2 publications

(3 citation statements)

References 13 publications

(13 reference statements)

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“…It has made a significant contribution to nations' economic development and has had a significant impact on the number of virtual network users [1]. However, the rise of internet accessibility is inextricably linked to the security of information systems, which is becoming increasingly sophisticated every day [2,3]. With its growing success, computer system expertise is progressing and improving daily.…”

Section: Introductionmentioning

confidence: 99%

“…In the past three years, data mining (DM) and ML procedures have been extensively researched in the development of intrusion detection systems using various intrusion detection datasets, and the most notable of which are the KDD-CUP 99 and NSL-KDD datasets. Rough groups, KNN [2,3], Naïve Bayes (NB), Neural Network (NN), and k-means [7,3,6] are some of the ML…”

Section: Introductionmentioning

confidence: 99%

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An Optimization Feature Extraction Technique using Intrusion Detection System

2023

IRJMETS

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As the alarming growth of computer connectivity and the significant number of computer-related applications increased lately, the challenge of achieving cyber-security has become progressively difficult. It also needs an adequate defense mechanism against a variety of cyber attacks. Detecting inconsistencies and threats in a computer network, as well as designing intrusion detection systems (IDS) that can help with cyber-security. A useful data-driven intrusion detection system has been developed using artificial intelligence (AI), particularly machine learning (ML) techniques. In this study, two different classification techniques for intrusion detection (ID) with each having its unique use cases were compared. Particle Swarm Optimization (PSO) algorithm was employed for dimensionality reduction before employing the two classifiers for the classification procedure. This study considered the classification techniques to categorize the network anomalies. The two classifiers employed are PSO + Decision Tree (PSO+DT) and PSO + K-Nearest Neighbor (PSO+KNN). The results of the detection techniques were verified using KDD-CUP 99 dataset. The usefulness of success indicators such as specificity, recall, f1-score, accuracy, precision, and consistency on cyber-security databases for different categories of cyber-attacks was employed on the result of the implementation. The two classifiers were also compared to deduce which of the classifier achieves exceedingly in terms of accuracy, detection rate (DR), and false-positive rate (FPR). Finally, the system was compared with the existing IDS. The results show that PSO+KNN outperformed the PSO+DT classifier algorithm in terms of identifying network anomalies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Optimization Feature Extraction Technique using Intrusion Detection System

2023

IRJMETS

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“…A mobile agent is a kind of software program that can migrate from one host to another in a heterogeneous network (Kuo-Huang et al, 2007). Also known as travelling agents, these programs will shuttle their being, code and state among resources (Ogunleye and Ogunde, 2010).…”

Section: End Functionmentioning

confidence: 99%

Service Oriented Application in Agent Based Virtual Knowledge Community

Yusuf¹,

Folorunso²,

Akinwale³

et al. 2011

CIS

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With the availability of the Internet, virtual communities are proliferating at an unprecedented rate. In-depth understanding of virtual community dynamics can help us to address critical organizational and information systems issues such as communities-of-practice, virtual collaboration, and knowledge management. The biggest challenge in fostering a virtual community is the supply of knowledge through services and the willingness to share knowledge with other members. This paper integrates the Service Oriented Architecture and Agent Based Theory to construct a Reinforced Concrete design (RCD) model for Reinforced Concrete Analysts and Designers in virtual communities. The aim of this paper is to elucidate the sharing of knowledge in virtual community from the perspective of RCD serviceability service. Results confirm that RC Designers will share knowledge; if their perceive benefit exceed the cost of their sharing behaviour. This study is useful for the developers of Service oriented Applications for virtual communities to insight into knowledge sharing in cyberspace for RCD.

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Intrusion Detection in Agent-Based Virtual Knowledge Communities

Cited by 2 publications

References 13 publications

An Optimization Feature Extraction Technique using Intrusion Detection System

An Optimization Feature Extraction Technique using Intrusion Detection System

Service Oriented Application in Agent Based Virtual Knowledge Community

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