Comparative Analysis of AI based Antivirus Software Programs Ensuring Cyber Security

In today’s digital arena security of the computer systems is one of the most important factors for users and businesses, as an attack on a system via the internet (cyber-attack) may cause heavy data loss and considerable harm to businesses. The increasing range of cyber-attacks has made traditional anti-virus scanners inefficient and are not fulfilling the desired need for protection. Hence, an advanced level of skill is required for the development of anti-attacking tools embedded with Artificial Intelligence to combat cyber threats. Modern warfare and international cybercrime have also increasingly involved cyber-attacks including targeted distribution attacks or highly networked spying, resulting in extremely dangerous malware attacks that were explicitly designed and released by nations to cause large-scale damage to organizations or infrastructure. Because of such evolving threats, more advanced tools for malware detection, prevention, and recovery are increasing in demand which would aim at defending computing networks from attack. This paper introduces a comparison between some of the best-rated artificial intelligence-embedded antivirus software programs so that a well-suited one could be used by users or enterprises accordingly. This report draws a basic understanding of the technological features provided by each of the software programs and also shows some evident drawbacks, if present. Meanwhile, it also points out some facts related to the use of AI in antiviruses and the scope of Artificial Intelligence in Cyber security.

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Publication Details

Journal
International Journal of Innovative Research in Computer Science & Technology
Published
2025-03-01
DOI
https://doi.org/10.55524/ijircst.2025.13.2.3
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49
Controls
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article

Comparative Analysis of AI based Antivirus Software Programs Ensuring Cyber Security

Binay Kumar Mishra, K.P. Mishra, Zahra Jabeen
1 citations
International Journal of Innovative Research in Computer Science & Technology
Advanced Malware Detection Techniques
1.49
article

Comparative Analysis of AI based Antivirus Software Programs Ensuring Cyber Security

Binay Kumar Mishra, K.P. Mishra, Zahra Jabeen
article en
1 citations

Abstract

In today’s digital arena security of the computer systems is one of the most important factors for users and businesses, as an attack on a system via the internet (cyber-attack) may cause heavy data loss and considerable harm to businesses. The increasing range of cyber-attacks has made traditional anti-virus scanners inefficient and are not fulfilling the desired need for protection. Hence, an advanced level of skill is required for the development of anti-attacking tools embedded with Artificial Intelligence to combat cyber threats. Modern warfare and international cybercrime have also increasingly involved cyber-attacks including targeted distribution attacks or highly networked spying, resulting in extremely dangerous malware attacks that were explicitly designed and released by nations to cause large-scale damage to organizations or infrastructure. Because of such evolving threats, more advanced tools for malware detection, prevention, and recovery are increasing in demand which would aim at defending computing networks from attack. This paper introduces a comparison between some of the best-rated artificial intelligence-embedded antivirus software programs so that a well-suited one could be used by users or enterprises accordingly. This report draws a basic understanding of the technological features provided by each of the software programs and also shows some evident drawbacks, if present. Meanwhile, it also points out some facts related to the use of AI in antiviruses and the scope of Artificial Intelligence in Cyber security.

International Journal of Innovative Research in Computer Science & TechnologyVol. 13(2)
Veer Kunwar Singh University (IN)
Openalex Percentile: Top 22%
Advanced Malware Detection Techniques
1.49
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