Use of Fuzzy Logic in Cyber Security System: Cyber Threat Intelligence

Abstract

Purpose of the study: Fuzzy logic is a mathematical concept that allows for the handling of uncertain or imprecise data. In cyber security, fuzzy logic can be used to improve the accuracy and efficiency of security systems. Cyber threat intelligence plays a crucial role in modern cybersecurity by enabling organizations to proactively identify, analyse, and respond to potential cyber threats. With the increasing complexity and sophistication of cyber threats, effective cyber threat intelligence has become a critical component of modern cybersecurity. Traditional approaches often struggle to handle the inherent uncertainties and complexities in threat intelligence data.
 Methodology: Through a comprehensive literature review, examines the current state of cyber threat intelligence and the principles of fuzzy logic. The paper presents a detailed analysis of how fuzzy logic can be applied to various aspects of cyber threat intelligence, including threat modelling, detection and classification, risk assessment, and decision support systems.
 Main Findings: The findings highlight the benefits of using fuzzy logic in cyber threat intelligence and pave the way for further research and development in this promising field. The future prospects and challenges of integrating fuzzy logic with other advanced technologies such as machine learning and artificial intelligence.
 Applications of this study: The proposed approach has the potential to significantly improve the analysis and decision-making processes in agriculture, helping farmers to make more informed decisions about crop treatments and ultimately increasing crop yields.
 Novelty/Originality of this study: The outcomes of this research contribute to advancing the field of cyber threat intelligence and provide valuable insights into the practical implementation of fuzzy logic for better threat analysis and mitigation strategies.