Meaningful Cipher Data Generation: Novel Encipher using Fuzzy Logic For Reducing Cyber Data Attacks
Ch. Rupa · 2023
Novel encryption approaches are required to protect the data from the hackers. As per the Palo alto reports, attacks on cipher data increasing over the years. Hackers can access the original data by decrypting it using a variety of techniques. Stealing the encryption key directly is the method that is used most frequently. Intercepting the data is another common method, either before the sender encrypts it or after the recipient decrypts it. A new cipher is proposed in this paper, to improve confidentiality over existing ciphers that produce meaningless and unintelligible formatted ciphers with external key sharing. It causes hackers to begin conducting active attacks through passive attacks, i.e traffic analysis. The proposed cipher combines non-distributable external key sharing and fuzzy logic to generate meaningful cipher images. This approach consists of 4 modules named Rule Base Module, Fuzzification Module, Inference Engine Module and Defuzzification Module. Rule Base consists of user-defined constraints. Fuzzification module performs the encryption process. Inference Engine Module performs the generation of Meaningful cipher images. Defuzzification module performs Key Extraction and Decryption of the image. The security and confidentiality of images are greatly reliant on key management. Here, the key is not distributed which provides controlled access and reduces the key exposure. The combination of fuzzy logic and non-distributable external key sharing provides a better solution for protecting image confidentiality. The proposed approach performance is measured in terms of various metrics such as Mean squared error, Structured Similarity Index, and Histogram analysis.