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.
DOI Link
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
Recommended Citation
Khanji, Salam and Khattak, Asad, "Towards a Novel Intrusion Detection Architecture using Artificial Intelligence" (2020). All Works. 3700.
https://zuscholars.zu.ac.ae/works/3700
Indexed in Scopus
yes
Open Access
no