Multi-criteria Decision-Making Problems Based Antivirus Software Selection Using Intuitionistic Fuzzy VIKOR

Recent widespread use of computers and the Internet puts security concerns regarding malicious malware and information system protection provided by antivirus software on the table. To protect the security of computer systems, the information business nowadays develops a wide range of antivirus software. The best antivirus application to protect our information systems must be chosen, and this is a multi-attribute decision-analysis issue that calls for the investigation of a number of different factors. There are, however, many different kinds of security programs available that may have an impact on consumers’ choices. A multi-criteria decision-making (MCDM) problem can also be categorized as choosing the best antivirus software. For the complex systems’ multi-criteria optimization, the VIKOR approach was created. This approach concentrates on rating and selecting from a set of options with conflicting criteria. This work aims to extend the VIKOR methodology to problems involving decision-making when the weighing factors of the criteria are completely unknown and assessments of the alternatives are expressed as intuitionistic fuzzy (IF) sets. We develop a model of entropy weights that may be used to calculate the weights of a set of criteria expressed in fuzzy sets that are intuitionistic. In addition, the VIKOR is modified using a unique nonlinear normalizing approach. The primary MCDM structures that need to be resolved using the suggested technique are ten criteria and four alternatives for choosing antivirus software. The outcome has demonstrated that McAfee Groupshield and Webshield are the most effective antivirus program that satisfies the requirements. This outcome will aid users in making the best antivirus recommendation to their employer, particularly computer software professionals in a particular firm.