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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 12, 2023.
Abstract: Ensuring the security of sensitive data and protecting user privacy remains one of the most significant challenges in our contemporary landscape. Organizations Companies cannot adopt a new technology without reassurance regarding data confidentiality. To address these challenges, we present an innovative system that draws upon extensive knowledge and expertise in the field of cryptography, especially in encryption methods. This system tailors its strategies to align with specific scenarios, prioritizing data confidentiality. Our solution is based on one of the Artificial Intelligence techniques, which is Knowledge-Based Systems (KBS) and extends the intelligent encryption methods from our previous research. However, this new system has taken a novel approach by reconfiguring this within KBS architecture. We have introduced additional technical components, including knowledge bases, an inference engine, and the Nearest Neighbor (NN) search algorithm. As a result, this revised architecture not only enhances security and system performance but also showcases improved maintainability and scalability.
Bouchra Boulahiat, Salima Trichni, Mohammed Bougrine and Fouzia Omary, “Artificial Intelligence for Confidential Information Sharing Based on Knowledge-Based System” International Journal of Advanced Computer Science and Applications(IJACSA), 14(12), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141259
@article{Boulahiat2023,
title = {Artificial Intelligence for Confidential Information Sharing Based on Knowledge-Based System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141259},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141259},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {12},
author = {Bouchra Boulahiat and Salima Trichni and Mohammed Bougrine and Fouzia Omary}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.