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Jun Li, Chenyang Zhang, Jianyi Zhang and Yanhua Shao
To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obsc...
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Xingchen Wang and Peng Li
With the widespread adoption of cloud computing, the face verification process often requires the client to upload the face to an untrusted cloud server to obtain the verification results. Privacy leakage issues may arise if the client?s private informat...
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Zeming Wei, Jiawen Fang, Zhicheng Hong, Yu Zhou, Shansi Ma, Junlang Zhang, Chufeng Liang, Gansen Zhao and Hua Tang
Blockchain is a distributed ledger technology that possesses characteristics such as decentralization, tamper resistance, and programmability. However, while blockchain ensures transaction openness and transparency, transaction privacy is also at risk of...
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Keundug Park and Heung-Youl Youm
The volume of the asset investment and trading market can be expanded through the issuance and management of blockchain-based security tokens that logically divide the value of assets and guarantee ownership. This paper proposes a service model to solve ...
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Xin Liao and Khoi D. Hoang
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular form...
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Jiawei Han, Qingsa Li, Ying Xu, Yan Zhu and Bingxin Wu
Artificial intelligence-generated content (AIGC) technology has had disruptive results in AI, representing a new trend in research and application and promoting a new era of AI. The potential benefits of this technology are both profound and diverse. How...
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Bin Cheng, Ping Chen, Xin Zhang, Keyu Fang, Xiaoli Qin and Wei Liu
With the rapid development of ubiquitous data collection and data analysis, data privacy in a recommended system is facing more and more challenges. Differential privacy technology can provide strict privacy protection while reducing the risk of privacy ...
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Fan Huang , Nan Yang, Huaming Chen , Wei Bao and Dong Yuan
With the widespread use of end devices, online multi-label learning has become popular as the data generated by users using the Internet of Things devices have become huge and rapidly updated. However, in many scenarios, the user data are often generated...
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Muneerah Al Asqah and Tarek Moulahi
The Internet of Things (IoT) compromises multiple devices connected via a network to perform numerous activities. The large amounts of raw user data handled by IoT operations have driven researchers and developers to provide guards against any malicious ...
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Sapdo Utomo, Adarsh Rouniyar, Hsiu-Chun Hsu and Pao-Ann Hsiung
Smart city applications that request sensitive user information necessitate a comprehensive data privacy solution. Federated learning (FL), also known as privacy by design, is a new paradigm in machine learning (ML). However, FL models are susceptible to...
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