In this modern world, the cloud aids organizations by implementing newer applications, innovative computing tools, etc with greater versatility, flexibility in upgrades, and minimum capital investment demands. Moreover, the use of the cloud by financial organizations is becoming more significant since cost-effectiveness and security are major concerns. Evolving fuzzy logic techniques can provide and select effective cloud service providers to address users concerns regarding security, storage, financial applications, and quality of service (QoS). An advanced fuzzy logic framework helps cloud providers to set up reliable, high-performing, resilient, and dynamic infrastructure for financial applications and others. Cloud network security challenges in the financial sector are complex, and resource-intensive, and include cyber threats. There is a need to secure remote access to financial data, and manage scalability and flexibility. Most financial services are in the early stages and advanced cloud strategies are required.

An increasing number of organizations have experienced security issues in public cloud infrastructure by virtue of security misconfigurations, inaccurate data sharing, compromised accounts, and vulnerability exploitation. While many organizations have already moved to the cloud, there is an increased need for cloud security due to increased challenges that include security breaches, operational performance issues, fraud, etc which may delay the adoption of cloud computing models. Evolving cloud-based applications and data must be protected and prevented from attack and unauthorized access following applicable regulations. Advances in fuzzy-based intelligent anomaly detection can aid organizations with accurate, real-time insights into the growing threats, developing anti-fraud systems and fraud investigations for reducing the uncertainty of conventional technologies.

This Special Issue focuses on the fuzzy logic-based techniques that increase customer engagement in adopting the cloud for advancing financial applications and that strategically analyze and improve accurate performance evaluation models. Original research and review articles based on advanced fuzzy logic are invited for this Special Issue.

Potential topics include but are not limited to the following:

• Fuzzy logic in cloud-based infrastructures for stacking up data and critical financial applications
• Fuzzy logic and machine learning for real-time anomaly detection in cloud security for managing financial crime
• Fuzzy logic-based resources allocation approaches for the cloud financial services
• Fuzzy logic-based secured modeling for financial management and cloud economics
• Fuzzy logic-based techniques for robust, reliable network security in mitigating cyber threats to financial organizations
• Fuzzy logic-based strategies in early warning systems for financial risk predictions
• Fuzzy logic in cloud-based network security for controlling and preventing ransomware and financial applications
• Fuzzy logic and cloud-based software to optimize financial analytics for real-world applications
• Impact of advanced fuzzy logic on current web attacks in the financial sector
• Recent trends of fuzzy logic in mitigating the obstacles of cloud adoption for financial applications