Klein Bottle-Inspired Network Segmentation for Untraceable Data Flows in Secure IT Systems

• Author(s): Syed Khundmir Azmi
• Paper ID: 1711014
• Page: 852-862
• Published Date: 31-10-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 4 October-2024

Abstract

In this paper, the authors investigate the usage of Klein Bottle-based network segmentation, which enables the increased security of IT systems and facilitates the untraceable data flows. Conventional network segmentation models are not always adequate to curb unauthorized access of data as well as system integrity. The article presents a new solution, which uses the topological structure of the Klein Bottle to establish highly secure and interconnected networks that render data flows obscure and hard to track and manipulate sensitive information by attackers. The major observations are that this technique can greatly decrease the probability of information attacks as it avoids horizontal traffic in networks thereby providing a high level of information isolation. The research also indicates that this type of segmentation can be applied in practice, which can be a valuable solution to organizations that aim to improve their cybersecurity condition. The value of this study is that it uses topological principles in network security in an original way, offering a novel scheme of attaining untraceable data streams and overall IT system protection against emerging cyberattacks.

Keywords

Network Segmentation, Data Breach, Lateral Movement, Network Security, Data Flow, Security Solutions

Citations

IRE Journals:
Syed Khundmir Azmi "Klein Bottle-Inspired Network Segmentation for Untraceable Data Flows in Secure IT Systems" Iconic Research And Engineering Journals Volume 8 Issue 4 2024 Page 852-862

IEEE:
Syed Khundmir Azmi "Klein Bottle-Inspired Network Segmentation for Untraceable Data Flows in Secure IT Systems" Iconic Research And Engineering Journals, 8(4)