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A new multimedia cryptosystem using chaos, quaternion theory and modular arithmetic


4th International Congress on AI and Machine Learning

August 24-25, 2023 | Webinar

Luis E Mendez

Universidad Distrital Francisco Jos�© de Caldas, Colombia

ScientificTracks Abstracts: RRJET

Abstract

Statement of the problem: Before COVID the consumption of multimedia on Internet had been increasing, and then the pandemic started and increased the consumption drastically. This is quantified by The Canadian company Sandvine, in its annual report 2023, it shows that multimedia consumption all over the world had reached 60% in 2020 and 65% in 2022, also during the first two years of pandemic the upstream increased about a 100% and the downstream 44%, therefore is necessary to strengthen encryption schemes for multimedia data sources. Methodology & theoretical orientation: A new cryptosystem for multimedia files was designed using quaternion numbers, residual matrices and chaotic attractors, also the key employed is generated from an image of the Julia Quaternion ensuring a wide and sensitive range for its chaotic nature together with the physics characteristics from the 3d space, some research that were useful and its contribution are: Julia Quaternion encryption images based systems residual classes algorithms and quaternion based cryptosystem. Conclusion: The schema proposed was tested with different metrics obtaining excellent results, but further work is necessary to improve robustness analysis. Also, the key generated from the Julia Quaternion image was demonstrated that has high sensibility and a key space of 2^360.

Biography

Engr. studied systems engineering at the Universidad Francisco Jose de Caldas. Where he researched about chaos applications, machine learning, multimedia processing, number theory, cryptography and computer science since 2015. He did scientific work at the same university since 2017 on machine learning and multimedia encryption systems. When he was a student, he went to Saitama, Japan under the Sakura exchange program where learn about image recognition with neural networks, robotics, chemistry and other topics at the (University of Saitama).