Adaptive security Models: Leveraging RSA and intuitionistic fuzzy logic for robust cryptography

• Greater structural complexity of I F G N resists cryptanalysis and ensures secure transmission of confidential messages. • The method combines I F G concepts with RSA encryption to handle uncertainty and imprecision in real-world data. • Efficient domination helps utilize network resources effectively without reducing cryptographic strength. • The I F G N framework is adaptable and applicable to areas such as cloud computing, IoT, and defence communication. • Multi-layer encryption using I F G N improves data confidentiality compared with traditional approaches. In modern communication systems, the processes of encryption and decryption require solid mechanisms that can handle uncertainty, incompleteness, and imprecision of real-world data. The Intuitionistic fuzzy graphs ( I F G s) are certainly a potent mathematical construct to describe these uncertainties and it is quite appropriate that they are applied in the more sophisticated cryptography. The purpose of this work is to suggest a best Intuitionistic Fuzzy Graph Network ( I F G N ) based on the idea of an efficient domination and consequently use it to carry out the process of secure encryption and decryption of confidential messages. It has been suggested that a multi-layer system of encryption is organized and secure that involves the representation of a hidden message, RSA cryptographic methods, normalization in integer data, and effective domination in I F G s. Efficient dominating sets have been used to reduce redundancy and maximize the network performance without loss of cryptographic strength. The resulting I F G N will increase the security since it makes the structure more complex and offer some resistance to cryptanalysis. The primary emphasized point of work is associated with the enhanced degree of confidentiality, the optimal use of resources, and adaptable management of the uncertainty. The importance of this study is that it combines graph-theoretic fuzzy concepts with classical cryptography, and therefore, it proposes a scalable and adaptive encryption mechanism. The proposed framework would be especially useful in the secure transmission of data over cloud computing, IoT, and defense communication.