Title: Cybersecurity automation and managing cyber threats in network through smart techniques: an intelligent approach for future gen. systems

Authors: Rohit Rastogi; Vaibhav Sharma; Tushar Gupta; Vaibhav Gupta

Addresses: Department of CSE, ABES Engineering College, Ghaziabad, U.P., 201009, India ' Department of CSE, ABES Engineering College, Ghaziabad, U.P., 201009, India ' Department of CSE, ABES Engineering College, Ghaziabad, U.P., 201009, India ' Department of CSE, ABES Engineering College, Ghaziabad, U.P., 201009, India

Abstract: Cybersecurity has become a major concern in this digital era. Since, the cyberattacks and their types are increasing at an immense rate, it is not humanly possible to monitor, identify and take actions against the attacks. With the current automation systems majorly relying on supervised learning algorithms where they have already seen the type of attacks to monitor and manage the attacks, these systems have been rendered inefficient by zero day attacks. The immense potential of AI and utilise it to its full potential in the field of cybersecurity. If correctly applied, Artificial Intelligence can help to detect and deal with the cyberattacks more efficiently and can help protect users that are not very security conscious and are not aware about the dangers of these security breaches. The authors have decided to utilise machine learning algorithms like decision trees and knowledge discovery in database (KDD) to detect zero day attacks as well as handle other common cyberattacks.

Keywords: supervised learning; unsupervised learning; KDD; knowledge discovery in database; phishing; smashing; DDoS; distributed denial of services.

DOI: 10.1504/IJAACS.2025.147719

International Journal of Autonomous and Adaptive Communications Systems, 2025 Vol.18 No.3, pp.189 - 219

Received: 09 Jul 2023
Accepted: 01 Mar 2024
Published online: 28 Jul 2025 *

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