Bulletin of Social Informatics Theory and Application
Vol. 8 No. 1 (2024)

Ransomware detection: patterns, algorithms, and defense strategies

Amro, Manar Y (Unknown)
Dwieb, Mohamed (Unknown)
Hammad, Jehad A.H (Unknown)
Wibawa, Aji Prasetya (Unknown)



Article Info

Publish Date
08 May 2024

Abstract

In the contemporary digital landscape, rapid technological advancements present unprecedented challenges for developers in the hardware and software realms. The ubiquitous presence of the Internet, the Internet of Things (IoT), and widespread digital solutions bring numerous benefits and escalating risks. This study investigates the pervasive threat of ransomware attacks, a daily menace that imperils the operational and security dimensions of the digital sphere for enterprises and individuals. The research objective is to identify the most effective algorithm for detecting ransomware viruses, a persistent and evolving threat that significantly challenges institutions, companies, and governmental organizations. The dynamic nature of ransomware necessitates robust detection mechanisms to safeguard sensitive data. To achieve this goal, we conducted a comparative analysis of four prominent algorithms recognized for their efficacy in combating and detecting viruses. Emphasis was placed on the algorithm exhibiting the most promising results. A detailed examination of its impact on existing data involved comprehensive analysis and a comparative assessment against previous studies. Results, derived from extensive studies and experiments on a diverse dataset, illuminate the critical role of ransomware detection algorithms and underscore their effectiveness. The findings contribute valuable insights to the ongoing discourse on cybersecurity strategies, providing a foundation for enhanced ransomware defense measures.

Copyrights © 2024






Journal Info

Abbrev

businta

Publisher

Subject

Computer Science & IT Social Sciences

Description

Bulletin of Social Informatics Theory and Application (ISSN 2614-0047) is an interdisciplinary scientific journal for researchers from Computer Science, Informatics, Social Sciences, and Management Sciences to share ideas and opinions, and present original research work on studying the interplay ...