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Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.09.059
Abstract: In online social communities, many recommender systems use collaborative filtering, a method that makes recommendations based on what are liked by other users with similar interests. Privacy issues arise in this process, as sensitive personal…
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Keywords:
recommendation;
privacy preserving;
efficient privacy;
privacy ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2911924
Abstract: Recent years have witnessed that the new mobility Intelligent Transportation System is booming, especially the development of Vehicular Ad Hoc Networks (VANETs). It brings convenience and a good experience for drivers. Unfortunately, VANETs are suffering…
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Keywords:
vehicular hoc;
efficient privacy;
scheme;
authentication ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3078629
Abstract: Analysis and utilization of massive meter data can help decision-makers provide reasonable decisions. Therefore, multi-functional meter data processing has received considerable attention in recent years. Nevertheless, it might compromise users’ privacy, such as releasing users’…
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Keywords:
efficient privacy;
privacy preserving;
massive data;
preserving massive ... See more keywords
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Published in 2018 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2017.2766701
Abstract: With the pervasiveness of location-aware mobile terminals and the popularity of social applications, location-based social networking service (LBSNS) has brought great convenience to people’s life. Meanwhile, proximity detection, which makes LBSNS more flexible, has aroused…
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Keywords:
proximity detection;
query;
social applications;
efficient privacy ... See more keywords
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Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3426536
Abstract: In recent years, electric vehicles (EVs) have emerged as a promising mode of transportation. With the development of Internet of Robotic Things (IoRT) technology, charging stations are employing interconnected robots to charge EVs, automating the…
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Keywords:
privacy preserving;
internet robotic;
charging scheme;
privacy ... See more keywords
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Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3516515
Abstract: Federated learning (FL) has emerged as a promising approach for collaborative machine learning while respecting data privacy. However, directly aggregating local models during FL training can expose sensitive information, as adversaries may analyze model parameters…
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Keywords:
privacy preserving;
authentication;
privacy;
internet things ... See more keywords
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Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3525731
Abstract: Federated learning (FL) is a distributed machine learning framework that allows for model training across multiple clients without requiring access to their local data. However, FL poses some risks, for example, curious clients might conduct…
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Keywords:
inference attacks;
privacy preserving;
privacy;
universal efficient ... See more keywords
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Published in 2017 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2015.2432814
Abstract: Protecting the privacy of mobile phone user participants is extremely important for mobile phone sensing applications. In this paper, we study how an aggregator can expeditiously compute the minimum value or the $k$ th minimum…
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Keywords:
preserving min;
privacy preserving;
min min;
min computations ... See more keywords
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Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3231785
Abstract: The advance of cloud computing has driven a new paradigm of outsourcing large-scale data and data-driven services to public clouds. Due to the increased awareness of privacy protection, many studies have focused on addressing security…
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Keywords:
privacy preserving;
preserving set;
privacy;
set reverse ... See more keywords
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Published in 2025 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2025.3536612
Abstract: Federated graph attention networks (FGATs) are gaining prominence for enabling collaborative and privacy-preserving graph model training. The attention mechanisms in FGATs enhance the focus on crucial graph features for improved graph representation learning while maintaining…
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Keywords:
graph attention;
privacy preserving;
attention;
privacy ... See more keywords
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Published in 2022 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3175945
Abstract: The rapid development of Internet of Things (IoT) stimulates the innovation for the health-related devices such as remote patient monitoring, connected inhalers and ingestible sensors. Simultaneously, with the aid of numerous equipments, a great number…
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Keywords:
enhanced federated;
federated edge;
efficient privacy;
privacy enhanced ... See more keywords