Visible to the public Application Research Based on Machine Learning in Network Privacy Security

TitleApplication Research Based on Machine Learning in Network Privacy Security
Publication TypeConference Paper
Year of Publication2020
AuthorsXu, Yizheng
Conference Name2020 International Conference on Computer Information and Big Data Applications (CIBDA)
Date PublishedApril 2020
ISBN Number978-1-7281-9837-8
Keywordsauthentication, Bioinformatics, Communication networks, composability, control theory, feature extraction, Human Behavior, machine learning, Network security, privacy, privacy protection, pubcrawl, resilience, Resiliency, Scalability
AbstractAs the hottest frontier technology in the field of artificial intelligence, machine learning is subverting various industries step by step. In the future, it will penetrate all aspects of our lives and become an indispensable technology around us. Among them, network security is an area where machine learning can show off its strengths. Among many network security problems, privacy protection is a more difficult problem, so it needs more introduction of new technologies, new methods and new ideas such as machine learning to help solve some problems. The research contents for this include four parts: an overview of machine learning, the significance of machine learning in network security, the application process of machine learning in network security research, and the application of machine learning in privacy protection. It focuses on the issues related to privacy protection and proposes to combine the most advanced matching algorithm in deep learning methods with information theory data protection technology, so as to introduce it into biometric authentication. While ensuring that the loss of matching accuracy is minimal, a high-standard privacy protection algorithm is concluded, which enables businesses, government entities, and end users to more widely accept privacy protection technology.
Citation Keyxu_application_2020