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Authors = Binting Su

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14 pages, 439 KiB  
Article
Efficient Identity-Based Universal Designated Verifier Signature Proof Systems
by Yifan Yang, Xiaotong Zhou, Binting Su and Wei Wu
Mathematics 2025, 13(5), 743; https://doi.org/10.3390/math13050743 - 25 Feb 2025
Viewed by 483
Abstract
The implementation of universal designated verifier signatures proofs (UDVSPs) enhances data privacy and security in various digital communication systems. However, practical applications of UDVSP face challenges such as high computational overhead, onerous certificate management, and complex public key initialization. These issues hinder UDVSP [...] Read more.
The implementation of universal designated verifier signatures proofs (UDVSPs) enhances data privacy and security in various digital communication systems. However, practical applications of UDVSP face challenges such as high computational overhead, onerous certificate management, and complex public key initialization. These issues hinder UDVSP adoption in daily life. To address these limitations, existing solutions attempt to eliminate bilinear pairing operations, but their proposal still involves cumbersome certificate management and inherent interactive operations that can sometimes significantly degrade system efficiency. In this paper, we first utilize the identity-based (ID-based) SM2 digital signature scheme to construct an ID-based UDVSP system which sidesteps the cumbersome certificate management issue. To further remove the interactive requirement, we also employ the OR proof and Fiat–Shamir technologies to design the other ID-based UDVSP system. Our designs not only possess the same bilinear pairing-free advantage as Lin et al.’s proposal, but also achieve the certificate-free or non-interactive goals. Security proofs and performance analysis confirm the viability and efficiency of our systems. Full article
(This article belongs to the Special Issue Advances in Mathematics Computation for Software Engineering)
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20 pages, 5182 KiB  
Article
A Cross-Platform Personalized Recommender System for Connecting E-Commerce and Social Network
by Jiaxu Zhao, Binting Su, Xuli Rao and Zhide Chen
Future Internet 2023, 15(1), 13; https://doi.org/10.3390/fi15010013 - 27 Dec 2022
Cited by 5 | Viewed by 3490
Abstract
In this paper, we build a recommender system for a new study area: social commerce, which combines rich information about social network users and products on an e-commerce platform. The idea behind this recommender system is that a social network contains abundant information [...] Read more.
In this paper, we build a recommender system for a new study area: social commerce, which combines rich information about social network users and products on an e-commerce platform. The idea behind this recommender system is that a social network contains abundant information about its users which could be exploited to create profiles of the users. For social commerce, the quality of the profiles of potential consumers determines whether the recommender system is a success or a failure. In our work, not only the user’s textual information but also the tags and the relationships between users have been considered in the process of building user profiling model. A topic model has been adopted in our system, and a feedback mechanism also been design in this paper. Then, we apply a collative filtering method and a clustering algorithm in order to obtain a high recommendation accuracy. We do an empirical analysis based on real data collected on a social network and an e-commerce platform. We find that the social network has an impact on e-commerce, so social commerce could be realized. Simulations show that our topic model has a better performance in topic finding, meaning that our profile-building model is suitable for a social commerce recommender system. Full article
(This article belongs to the Section Techno-Social Smart Systems)
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