Information security risk analysis in food processing industry using a fuzzy inference system

Recently, different attempts have been made to characterize information security threats, particularly in the industrial sector. Yet, there have been a number of mysterious threats that could jeopardize the safety of food processing industry data, information, and resources. This research paper aims to increase the efficiency of information security risk analysis in food processing industrial information systems, and the participants in this study were experts in executive management, regular staff, technical and asset operators, third-party consultancy companies, and risk management professionals from the food processing sector in Sub-Saharan Africa. A questionnaire and interview with a variety of questions using qualitative and quantitative risk analysis approaches were used to gather the risk identifications, and the fuzzy inference system method was also applied to analyze the risk factor in this paper. The findings revealed that among information security concerns, electronic data in a data theft threat has a high-risk outcome of 75.67%, and human resource management (HRM) in a social engineering threat has a low-risk impact of 26.67%. Thus, the high-probability risk factors need quick action, and the risk components with a high probability call for rapid corrective action. Finally, the root causes of such threats should be identified and controlled before experiencing detrimental effects. It's also important to note that primary interests and worldwide policies must be taken into consideration while examining information security in food processing industrial information systems.