A novel architecture for an integrated enterprise network security system

Thanudas, B.; Sreelal, S.; Raj, V. Cyril; Sairam, Anugolu Purnesh; Gajmoti, Vinay; Joshi, Palash

doi:10.1504/ijsn.2019.098919

IJSN

2019

DOI: 10.1504/ijsn.2019.098919

|View full text |Cite

A novel architecture for an integrated enterprise network security system

B. Thanudas

S. Sreelal

V. Cyril Raj

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…),Thanudas et al (2019),Yang et al (2019); • AgentMiningAlgorithm, AgentMiningModel and AgentMiningProcess can be found in several papers. Some papers even include instances for each of these three concepts (e.g Larsen et al (2019),Roldán et al (2018),Sethi et al (2019)…”

mentioning

confidence: 99%

Agent mining approaches: an ontological view

Strugeon

Oliveira

Zekri

et al. 2021

The Knowledge Engineering Review

View full text Add to dashboard Cite

Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

show abstract

mentioning

confidence: 99%

Agent mining approaches: an ontological view

Strugeon

Oliveira

Zekri

et al. 2021

The Knowledge Engineering Review

View full text Add to dashboard Cite

show abstract

A systematic mapping study on agent mining

Strugeon

Oliveira

Thilliez

et al. 2021

Journal of Experimental & Theoretical Artificial Intelligen

View full text Add to dashboard Cite

Design and implementation of marine information management network security system based on artificial intelligence embedded technology

Zhang,

Zhou,

Long

et al. 2024

IFS

View full text Add to dashboard Cite

The complexity of marine information types, data diversity, data collection difficulties and other aspects makes the network security of marine information management more and more prominent, and has become a major issue affecting the stability of the country and society, so it is urgent to establish a marine information management network security system. Traditional network security technology adopts a passive approach and cannot actively detect viruses, trojans, and other hidden objects in the network. Antivirus software would only be used when attacked. If the risk of network attack is too great, the consequences would be unimaginable. This paper designed a marine information management network security system based on artificial intelligence embedded technology, which improved the efficiency of marine information security management. This paper also applied the embedded technology of AI to the network security management, and proposed the k-means clustering algorithm (K-Means) of AI, which can greatly improve the network security. The experimental results in this paper showed that the intrusion detection rates of System 1 and System 2 were 56.3% and 78.3% respectively when the number of viruses was 50 at 30M, and 65.5% and 80.1% respectively when the number of viruses was 50 at 60M. It showed that the intrusion detection rate of System 2 was higher both at 30M and 60M.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A novel architecture for an integrated enterprise network security system

Cited by 3 publications

References 0 publications

Agent mining approaches: an ontological view

Agent mining approaches: an ontological view

A systematic mapping study on agent mining

Design and implementation of marine information management network security system based on artificial intelligence embedded technology

Contact Info

Product

Resources

About