A fuzzy set is a tool that deals with reasoning. Unlike conventional logic, fuzzy sets enhance the capability of human decision-making by modelling the uncertainties present in our daily life issues. Fuzzy logic takes several possibilities as input. In return, it gives a definite output.

Fuzzy sets can be implemented in large networks, microcontrollers, workstation-based systems. It can even be initiated by combining software and hardware. Thus far, a handful number of algorithms are developed based on fuzzy notions. These fuzzy notions help us solve artificial intelligence and machine learning problems (e.g. decision-making algorithms, clustering algorithms, algorithms for pattern recognition based on information measures, classification algorithms, deep learning algorithms, fuzzy relation-based algorithms, fuzzy rule-based algorithms, algorithms to investigate communication networks and algorithms for knowledge-based systems). In recent years, the notion of a fuzzy set has been further developed by generalizing the concept of membership function. Several flexible extensions of fuzzy sets include the framework of Atanassov’s intuitionistic fuzzy sets, Pythagorean fuzzy sets, generalized orthopair fuzzy sets, picture fuzzy sets, spherical and T-spherical fuzzy sets and neutrosophic sets. All these fuzzy frameworks are extensively used in many practical situations under uncertainties.

The aim of this Special Issue is to bring together original research review articles discussing security and communication problems based on machine learning and artificial intelligence algorithms in fuzzy environments.

Potential topics include but are not limited to the following:

• Deep learning techniques involving fuzziness in security algorithms
• Decision-making algorithms for security based on extended fuzzy frameworks
• Information measure-based algorithms for security problems under uncertainties
• Knowledge-based systems for communication networks
• Security of networks based on fuzzy rules
• Fuzzy pattern recognition for security assessment
• Knowledge management and information retrieval algorithms involving fuzziness
• Fuzzy graph algorithms to investigate communication networks
• Algorithms for transportation systems under uncertainty
• Classification algorithms involving fuzziness
• Clustering algorithms based on extended fuzzy frameworks