Abstract
In cryptographic communications, messages may be transmitted in plain form or in encrypted form with same encryption keys due to customer’s mistakes and system’s weaknesses. Such communications should never happen in any situation as it is very dangerous and can be misused by adversaries. Identification of plain messages and crypts with same encryption keys is a very important problem to analyze such communications. In the paper, we consider the problem of identification to segregate traffic of encrypted visual messages as such form of messages are being used widely over communication networks in current era of information technology. We use bit-plane specific image measures and fuzzy computing scheme in our methodology of identification of plain images and encrypted images with same keys from encrypted images. Bit-plane specific measures are the row-wise (column-wise) frequency of ones, maximum run length and correlation between adjacent rows (columns) which exhibit characteristics of images and help to analyze images at bit-plane level. The results indicate that the methodology presented is able to identify plain images and encrypted images with same keys successfully.
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Arvind, Ratan, R. (2020). Analysis of Cryptographic Communications Using Bit-Plane Measures and Fuzzy Computing. In: Pant, M., Sharma, T., Verma, O., Singla, R., Sikander, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1053. Springer, Singapore. https://doi.org/10.1007/978-981-15-0751-9_90
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DOI: https://doi.org/10.1007/978-981-15-0751-9_90
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