Evaluating antivirus software : a comparative analysis of detection methodologies and performance metrics in modern antivirus solutions

Abstract

By reviewing existing literature, this study identifies and evaluates the key aspects of antivirus programs, focusing on their malware detection capabilities, system performance, and user experience. Key methods of malware detection, such as signature-based, heuristic-based, and behavior-based detection, are analyzed for their ability to identify both known and emerging threats. The impact of antivirus software on system performance is explored, with attention to resource consumption, scanning speed, and boot time. Additional security features such as real-time protection, firewall, phishing defense, ransomware detection, and VPN support are also discussed in detail. The research highlights the importance of regular software updates, cross- platform compatibility, and customer support in enhancing the user experience. Furthermore, the comparison between free and paid antivirus versions is reviewed, considering whether advanced features justify the cost. Independent evaluations from reputable testing organizations, such as AV Test and AV Comparatives, are also incorporated to provide an objective measure of antivirus performance. The study concludes by offering insights into the most effective antivirus solutions for different user needs and scenarios, emphasizing the growing role of artificial intelligence in improving software efficiency and security.