A Study on Computer Viruses and Sustainable Solutions for Cybersecurity

In modern society, computers form the backbone of critical infrastructure, enabling essential activities such as food distribution, water supply, energy management, and financial transactions. However, this dependency on computerized systems introduces significant vulnerabilities, particularly from cyber threats like spam, software bugs, denial-of-service (DoS) attacks, and malicious software (malware). Among these, malware poses the most complex and multifaceted threat, often acting as a catalyst for other cyber risks.This study focuses on examining malware's impact on computer security and developing strategies to enhance system resilience against cyber threats. Key objectives include understanding and categorizing malware types, analysing their operational mechanisms, and identifying vulnerabilities in existing security systems. Advanced technologies such as machine learning, big data analytics, and cloud-based approaches are leveraged to design robust detection, prevention, and mitigation frameworks.Furthermore, the study emphasizes intrinsic protection strategies over reliance on third-party antivirus solutions, explores real-time threat detection techniques, and establishes metrics for evaluating security measures' effectiveness. By enhancing user awareness and proposing actionable insights, this research aims to develop comprehensive and adaptive solutions for future malware threats, ultimately safeguarding the critical infrastructure of modern society. The findings underscore the importance of a multi-layered defence strategy that combines technological innovation, systemic improvements, and user education to address the evolving landscape of cyber threats.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.15719588
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

A Study on Computer Viruses and Sustainable Solutions for Cybersecurity

Zenodo (CERN European Organization for Nuclear Research)
Internet of Things and AI
article

A Study on Computer Viruses and Sustainable Solutions for Cybersecurity

article en

Abstract

In modern society, computers form the backbone of critical infrastructure, enabling essential activities such as food distribution, water supply, energy management, and financial transactions. However, this dependency on computerized systems introduces significant vulnerabilities, particularly from cyber threats like spam, software bugs, denial-of-service (DoS) attacks, and malicious software (malware). Among these, malware poses the most complex and multifaceted threat, often acting as a catalyst for other cyber risks.This study focuses on examining malware's impact on computer security and developing strategies to enhance system resilience against cyber threats. Key objectives include understanding and categorizing malware types, analysing their operational mechanisms, and identifying vulnerabilities in existing security systems. Advanced technologies such as machine learning, big data analytics, and cloud-based approaches are leveraged to design robust detection, prevention, and mitigation frameworks.Furthermore, the study emphasizes intrinsic protection strategies over reliance on third-party antivirus solutions, explores real-time threat detection techniques, and establishes metrics for evaluating security measures' effectiveness. By enhancing user awareness and proposing actionable insights, this research aims to develop comprehensive and adaptive solutions for future malware threats, ultimately safeguarding the critical infrastructure of modern society. The findings underscore the importance of a multi-layered defence strategy that combines technological innovation, systemic improvements, and user education to address the evolving landscape of cyber threats.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 38%
Internet of Things and AI
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