Hybrid intelligence system using fuzzy inference in cluster architecture for secured group communication
The complication of efficient group communication design in real-world application has been continuously increasing. More factors have to be taken into account continuously before any decision about the rekeying process in cluster architecture could be derived. In this scenario the decision-making process should be efficient and optimal; therefore, fuzzy inference system can be implemented for fast decision making in rekeying process. Secured and efficient group communication can be attained by deploying fuzzy-based inference system in hybrid clustered architecture of group communication. The aim of this proposed model is to reduce the communication and computation complexity of the system using fuzzy-based inference system. In this proposed model, a fuzzy inference system is designed with the function for membership in the group, and the manipulation on input–output relations is concluded. Moreover, by implementing the proposed system, complexity overhead is reduced due to efficient framework and minimized key management. Simulation is done to verify the efficiency of proposed model for the members, to subscribe the service pack with a requested time slot.
KeywordsFuzzy inference system Hybrid intelligence Secure group communication Rekeying Computation complexity
Compliance with ethical standards
Conflict of interest
Authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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