Abstract
With rapid technological advancement, security has become a major issue due to the increase in malware activity that poses a serious threat to the security and safety of computer systems. The threats and damages from malicious software are alarming and for that antivirus vendors tend to combat by designing more efficient antivirus software. Antivirus programmers have implemented new techniques such as emulation techniques and heuristic scanning. These methods are helpful in detecting encrypted polymorphic viruses. Some of the modern antivirus software is programmed for static and dynamic heuristics, rootkit heuristics, learning, neural networks, data mining, hidden Markov models, and many other methods to remove almost every virus hidden anywhere in the computer. In this paper, the focus is on the comparative performance analysis of various antivirus software (Avast, Avira, AVG, Eset Nod32, Panda, Malwarebytes). Testing was performed on the following computer configurations: Windows 10 operating system, 8 GB RAM, 64-bit operating system type, CPU Intel (R) Core (TM) i7-2670QM 2.20GHz. A clean, reinstalled operating system was prepared for testing. Antivirus software have been tested in the same way, that is, the same environment was prepared for each. The goal of testing is ranking antivirus software according to its functionalities and choosing the most effective one. Based on the comparative performance analysis of various antivirus software, the parameters that offer the utmost performance considering malware detection, removal rate, the memory usage of the installed antivirus, and the interface launch time is recommended as the best.
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Acknowledgments
This research was conducted with the late Professor Edin Mujčić at the University of Bihać, Technical faculty. Professor Edin Mujčić died on January 6, 2023. I want to dedicate this research to him as a thank-you for everything he taught me
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Drakulić, U., Mujčić, E. (2023). A Comparative Performance Analysis of Various Antivirus Software. In: Ademović, N., Kevrić, J., Akšamija, Z. (eds) Advanced Technologies, Systems, and Applications VIII. IAT 2023. Lecture Notes in Networks and Systems, vol 644. Springer, Cham. https://doi.org/10.1007/978-3-031-43056-5_30
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DOI: https://doi.org/10.1007/978-3-031-43056-5_30
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