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International Journal of Computational Science and Engineering Research
Volume 2, Issue 4 (October-December)
Article type: Original Article
Published: 23 September 2026 |Pages: 1 - 7 |ISSN: 3107 - 8605
https://doi.org/10.63328/IJCSER-V2RI4P1
Copyright © 2025 M. Pavan et al.
International Journal of Computational Science and Engineering Research
Open Access publication.

An Effective Cryptographic Algorithm For Multimodal Datasets Cryptanalysis Using Deep Learning

M. PavaniD1, and S. Dilli BabuiD2

Abstract

The cryptanalysis of multimodal datasets is particular, given the distinct statistics formats and cryptographic strategies that pose demanding situations to analysis. In this studies paintings, an green cryptographic algorithm for boosting the robustness and accuracy of cryptanalysis the usage of deep mastering is proposed. This method includes the usage of CNNs and transformer-based totally architectures in a systematic evaluation of multimodal datasets along with textual content, pictures, and numerical statistics to pick out the cryptographic styles and vulnerabilities. The model consists of feature extraction, modality fusion, and automated key inference to decode encrypted information with progressed efficiency.

Keywords: Kidney disease classification, CT images, CNN- LSTM, Deep learning, Grad-CAM, Medical imaging

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How to cite this article

M. Pavan , S. Dilli Babu , " An Effective Cryptographic Algorithm For Multimodal Datasets Cryptanalysis Using Deep Learning " , International Journal of Computational Sciences and Engineering Research (IJCSER) , Volume 2, Issue 4 , pp 1 - 7 , October 2025. CrossRef DOI: https://doi.org/10.63328/ijcser-v2ri3p8