Abstract
There are few laws and regulations related to privacy protection in the existing artificial intelligence data sharing environment, lack of practical operability, and low feasibility. The weakening of administrative management and industry self-discipline also reflects my country’s current weak protection of big data privacy. In order to solve the problem of sharing artificial intelligence data and algorithms, it becomes very important to study the legal protection of artificial intelligence data and algorithms from the perspective of Internet of Things resource sharing. This article is aimed at studying the use of laws to protect artificial intelligence data and algorithms. Aiming at reducing the bullwhip effect, a most effective bullwhip effect model derivation algorithm is proposed. This method can not only share customer demand information with members at all levels in the supply chain but also achieve information sharing among members at all levels. Calculate the proportion of the overall time of the program through multiple statistical data ( m = 30 , k = 12 ; and m = 60 , k = 15 ), and extract two special values representing the overall situation ( m = 30 , k = 12 ; m = 60 , k = 15 ). Most of the time consumption of this program is concentrated in the secret distribution stage, accounting for about 80% on average.
Highlights
IntroductionIf the privacy protection problem of the Wireless Communications and Mobile Computing artificial intelligence data sharing environment is not effectively solved and regulated, this will undoubtedly cause serious threats and severe challenges to the information order and security
With the rapid development of mobile internet technology, the Internet of Things, and other technologies, the era of intelligence has come, and human society has once again entered a new, large-scale production sharing and application data space represented by artificial intelligence, and an artificial intelligence data sharing environment
There are few existing laws and regulations related to privacy protection in the artificial intelligence data sharing environment, lack of practical operability, and low feasibility
Summary
If the privacy protection problem of the Wireless Communications and Mobile Computing artificial intelligence data sharing environment is not effectively solved and regulated, this will undoubtedly cause serious threats and severe challenges to the information order and security. The current privacy protection laws and regulations and protection models still cannot meet my country’s effective and standardized management of the artificial intelligence data sharing environment, and further improvements are urgently needed. That is, smart phone applications that collect user data within their authority beyond their original functions, is quickly becoming one of the most serious potential security hazards in smart cities In this article, he examines the current state of data overcollection and studies some of the most common cases of data overcollection. This solution is mainly aimed at cloud computing service providers rather than trustworthy, so the corresponding threshold strategy is adopted to reduce the threat of data leakage from a single untrusted service provider, and private data such as identity information is authorized by the data provider
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