Detection of Cyber Attacks Using AI/ML

Sunita Patil, Kirti Agarwal, Tanvi Baviskar, Prakhar Pandey, Dev Phadol

2025

Abstract

DDoS, as well as ransomware, is regarded as emerging threats in the modern digital platform. These forms of attacks could be exploited to cripple major businesses and organizations by disrupting business processes, significant financial losses, and compromise of sensitive information. Traditionally, the adoption of these security systems was not made since the threats are changing fast. To mitigate the foregoing challenge, we hereby proffer the development of an AI smart platform that would be able to identify and respond in real-time to DDoS and ransomware attacks. This platform shall primarily depend upon the use of ML(machine learning) to understand a network and its systems’ baseline behavior; thus, it can indicate anomalies that may signify potential threats. By having analysis of traffic and monitoring file activity, the solution can alert about unusual patterns and react in real-time by giving alarms or starting defense mechanisms. This solution suggested can be scalable and flexible, bringing not only rapid detection but also proactive defense capabilities for organizations to be ahead of the cyber attackers. The main objective of this platform is a means by which organizations can become more resilient and perhaps take steps forward in improving their state of resilience toward digital attacks.

Paper Citation

in Harvard Style

Patil S., Agarwal K., Baviskar T., Pandey P. and Phadol D. (2025). Detection of Cyber Attacks Using AI/ML. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 22-30. DOI: 10.5220/0013586100004664

in Bibtex Style

@conference{incoft25,
author={Sunita Patil and Kirti Agarwal and Tanvi Baviskar and Prakhar Pandey and Dev Phadol},
title={Detection of Cyber Attacks Using AI/ML},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={22-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013586100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Detection of Cyber Attacks Using AI/ML
SN - 978-989-758-763-4
AU - Patil S.
AU - Agarwal K.
AU - Baviskar T.
AU - Pandey P.
AU - Phadol D.
PY - 2025
SP - 22
EP - 30
DO - 10.5220/0013586100004664
PB - SciTePress