Copyright Protection and Data Reliability of AI-Written Literary Creations in Smart City

Abstract

The purpose is to solve copyright disputes over artificial intelligence (AI)-written literary creations and protect copyright by legislation through data reliability research. Accordingly, this work makes a detailed study of the criteria for the copyright protection of AI-written literary creation and the creation process. It constructs the model of swarm intelligence (SI) perception. Then, the Preservation Trustworthiness Incentives Sense (PTISense) scheme is designed based on the encryption algorithm for the SI perception model. The performance of the proposed PTISense scheme is verified and analyzed through experiments. Mainly, it analyzes the impact of PTISense on the accuracy of the reputation model, its robustness against malicious users, and the actual feasibility. The results show that when users complete 50 tasks, the false-positive rate is only 0.1, and the corresponding false-negative rate approximates 0. After each task, the user reputation will be updated, and the data will be evaluated for trust. The trust model of the proposed PTISense scheme based on encryption technology is more accurate. When η (the number of malicious users) is small, the more tasks are performed, the faster the reputation value decreases and tends to zero. The proposed PTISense scheme-based reputation evaluation model can better protect the data submitted by good users. It is robust against malicious users and protects the data and privacy of good users. Further, entities’ computing overhead in different SI perception stages is calculated. It is found that the proposed PTISense scheme is feasible for user data privacy protection. Compared with other schemes, it can achieve a safe and reliable SI perception process with a lower computing overhead. It can better ensure the authenticity and reliability of data.