Towards a Novel Intrusion Detection Architecture using Artificial Intelligence

Document Type

Conference Proceeding

Source of Publication

ACM International Conference Proceeding Series

Publication Date

11-11-2020

Abstract

Artificial intelligence (AI) is a transformative technology for potential replacement of human tasks and activities within industrial, social, intellectual, and digital applications. Network intrusion detection is crucial to identify cyber-attacks in critical infrastructures where a dynamic collection and analysis of network traffic can be conducted using AI. In this research paper we develop a novel intrusion detection architecture to mitigate malicious traffic passing through cyber infrastructure of an organization. We propose to design scenarios based on AI for intelligent self-protection or alert system that will facilitate countering actual cyber-attacks. The system will utilize machine learning algorithm - Random Forest - to offer more flexibility to discover new attacks and to ensure training the system to predict them in the future. Moreover, we design spam filtering program on python to detect spam emails as per email is one of the main attacking vectors that threatens the security of critical infrastructures.

ISBN

9780000000000

Publisher

Association for Computing Machinery

First Page

185

Last Page

189

Disciplines

Computer Sciences

Keywords

Computer crime, Computer software, Critical infrastructures, Decision trees, Electronic mail, Machine learning, Network architecture, Network security, Public works, Random forests, Cyber infrastructures, Digital applications, Malicious traffic, Network intrusion detection, Network traffic, Research papers, Self protection, Spam filtering, Intrusion detection

Scopus ID

85099180486

Indexed in Scopus

yes

Open Access

no

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