Title: A future prediction for cyber-attacks in the network domain with the visualisation of patterns in cyber-security tickets with machine learning

Authors: E. Sivajothi; S. Mary Diana; M. Rekha; R. Babitha Lincy; P. Damodharan; J. Jency Rubia

Addresses: Department of Computer Science and Engineering, Vel. Tech. Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu 600062, India ' Department of Information Technology, DMI College of Engineering, Chennai, India ' Department of Information Technology, R. M. K. Engineering College, Tamil Nadu 601206, India ' Department of Computer and Communication Engineering, Sri Eshwar College of Engineering, Kinathukadavu, Coimbatore, 641005, India ' Department of Computer Engineering, Marwadi University, Rajkot, India ' Department of Electronics and Communication Engineering, Vel. Tech. Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India

Abstract: Support ticket systems have gained popularity as a result of the increase in the use of virtual systems. Since new team members are typically hired during the course of a project, they must be familiar with the features that have already been implemented in the majority of software projects. The goal of this paper is to make clear how using tickets, new team members can be assisted in understanding the features that have been implemented in a project. A novel approach is proposed to categorise tickets using machine learning. The proposed method calculates the number of categories and categorises tickets automatically. While ticket feature visualisation displays the connections between ticket categories and keywords of ticket categories, ticket lifetime visualisation demonstrates time series change to review tickets quickly. Future visualisation designers can overcome comparable difficulties in the field of cyber security by learning about these techniques.

Keywords: cyber security; cyber-attack; network domains; machine learning.

DOI: 10.1504/IJESDF.2024.140758

International Journal of Electronic Security and Digital Forensics, 2024 Vol.16 No.5, pp.648 - 661

Received: 16 Jan 2023
Accepted: 06 Jun 2023
Published online: 02 Sep 2024 *

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