A Model of a Pragmatic Secure Intrusion Detection System for Local Area Networks
B. I. Ele, U. R. Alo, B. C. E. Mbam, A. O. Ofem
Journal of Advances in Mathematics and Computer Science · pp. 1–15 · Published 2 Dec 2015
10.9734/BJMCS/2016/22190Abstract
Intrusion detection is very imperative in network systems due to outstanding vulnerabilities left unaddressed by current preventive network security measures such as firewalls and encryption software. The inefficiency, inaccuracy, high false alarm rates and lack of self-defensive mechanism of existing network security systems has continued to pose serious concern to network users, administrators and security professionals and thus needs urgent redress. Therefore, the target of this paper is to develop a model of a pragmatic secure intrusion detection system for local area networks using layered framework with conditional random fields that is capable of overcoming the apparent shortcomings of present intrusion detection systems. A critical analysis of existing IDSs was done using the structured system analysis and design methodology (SSADM) due to the sequential configuration of the proposed security system. Furthermore, a real-time response mechanism and a self-defensive mechanism for a network intrusion detection system (NIDS) was developed and implemented. The outcome of this study was a secured IDS that would proactively address potential security vulnerabilities by resisting and detecting attacks and security policy violations reliably and efficiently in local area networks, thus making it inevitable for use in our security conscious environment of the 21st century.
Cited by 0
No indexed citations yet.
Related research
- An Effective ODAIDS-HPS Approach for Preventing, Detecting and Responding to DDoS Attacks — shares topic coverage
- Advancing IoT Cybersecurity through AI and ML: A Comparative Study on Intrusion Detection and Privacy Protection — shares topic coverage
- Advanced Sequential Learning Models for IoT Intrusion Detection: A Comparative Analysis of Transformer, GRU and LSTM Architectures — shares topic coverage
- Machine learning Algorithm of Intrusion Detection System — shares topic coverage
- Resource Management in a Pervasive Computing Environment — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.