Title: An effective network security scrutinising method based on deep learning

Authors: K. Sivakumar; C. Rajesh; S. Julia Faith; S. Narasimha Prasad

Addresses: Department of Electronics and Communication Engineering, Panimalar Engineering College, Chennai – 600123, India ' Department of Artificial Intelligence and Data Science, Vel Tech Multi Tech Dr. Rangarajan, Dr. Sakunthala Engineering College, Chennai – 600062, India ' Department of Information Technology, S.A. Engineering College, Chennai – 600077, India ' Department of Electronics and Communication Engineering, Dhanalakshmi College of Engineering, Anna University, Chennai, India

Abstract: The field of network security is constantly evolving. Future dangers are difficult to predict and even more challenging to prepare for. In order to effectively confront future network security concerns, this article discusses efforts made to construct a vital support capability for an autonomous network security testing system. The purpose of this system is to simulate future network attacks on vital infrastructure in order to better protect against them. A novel attack paradigm is proposed, one that allows for more awareness and control inside a network of compromised nodes. The suggested attack framework has low memory and network requirements while still allowing for the retrieval and execution of arbitrary attacks. This framework makes it easier to conduct rapid, autonomous penetration tests and assess the state of detection systems and procedures ahead of time for autonomous network-attacks.

Keywords: network security; cybersecurity; deep learning; artificial intelligence.

DOI: 10.1504/IJESDF.2024.139656

International Journal of Electronic Security and Digital Forensics, 2024 Vol.16 No.4, pp.464 - 473

Received: 16 Dec 2022
Accepted: 27 Feb 2023

Published online: 05 Jul 2024 *

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