A survey on quantum cryptography for ecommerce applications
K. S. Niraja, J. Kavitha, Fahmina Taranum · IET conference proceedings. · 2024
Cryptography which involves mathematical notations and algorithms to transform plaintext into cipher text for secure communication of data protection, data confidentiality though benefit from Machine Learning techniques with enhance security. Machine Learning models used in cryptography may be susceptible to confrontational attacks. There is a need to develop robust and resistant computing techniques to overcome attacks especially in ecommerce applications where the expected growth rate is by 10.75% on annual basis which will reach $107.3 billion by the end of 2023.Quantum computing is going to play a key role in near future through which quantum cryptography techniques can be applied on different Machine Learning models to enhance secure transactions in ensuring the privacy, integrity, efficiency in data-driven application and authenticity of sensitive information. In associated learning environments, where models are trained across numerous devices or servers, quantum cryptography can be utilized to provide secure communication and parameter updates while keeping the data decentralized and private. This paper focus on open issues and challenges of Machine Learning cryptography with quantum computing cryptography through Machine Learning Models in ecommerce.