Zero Day Hunter : AI-Based Detection of Zero-Day Attacks in Modern Network Environment

Aniket Mehar

Title:
Zero Day Hunter : AI-Based Detection of Zero-Day Attacks in Modern Network Environment

Authors:
Aniket Mehar

Cite This Article :

Aniket Mehar "Zero Day Hunter : AI-Based Detection of Zero-Day Attacks in Modern Network Environment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.1782-1795, URL: https://www.ijtsrd.com/papers/ijtsrd102149.pdf

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Abstract :
The rise of artificial intelligence (AI) revolutionized both cybersecurity defenses and cyber-criminals’ methods to exploit vulnerabilities. Cybercriminals continue to exploit previously undiscovered vulnerabilities, known as zero-day attacks, posing severe threats to cyber security. These attacks are particularly challenging to detect, as they target unknown weaknesses in systems before security teams can respond or act. Traditional intrusion detection systems (IDS) rely heavily on pre-existing attack signatures, making them ineffective against zero-day threats. Machine learning (ML) algorithms have recently become a promising solution for enhancing IDS capabilities by identifying anomalies and predicting potential vulnerabilities in real time.

Keywords :
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Publication Details:

Unique Identification Number : IJTSRD102149

Published In : Special Issue | Smart Innovations in Computer Science and Applications, March 2026

Page Number(s) : 1782-1795

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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