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  1. No Access

    Article

    Privacy preserving machine unlearning for smart cities

    Due to emerging concerns about public and private privacy issues in smart cities, many countries and organizations are establishing laws and regulations (e.g., GPDR) to protect the data security. One of the mo...

    Kongyang Chen, Yao Huang, Yiwen Wang, **aoxue Zhang… in Annals of Telecommunications (2024)

  2. No Access

    Chapter and Conference Paper

    Member Inference Attacks in Federated Contrastive Learning

    In the past, the research community has studied privacy issues in federated learning, self-supervised learning, and deep models. However, privacy investigations into the domain of federated contrast learning a...

    Zixin Wang, Bing Mi, Kongyang Chen in Artificial Intelligence Security and Privacy (2024)

  3. No Access

    Article

    Model architecture level privacy leakage in neural networks

    Privacy leakage is one of the most critical issues in machine learning and has attracted growing interest for tasks such as demonstrating potential threats in model attacks and creating model defenses. In rece...

    Yan Li, Hongyang Yan, Teng Huang, Zijie Pan… in Science China Information Sciences (2023)

  4. Article

    Open Access

    Point-wise spatial network for identifying carcinoma at the upper digestive and respiratory tract

    Artificial intelligence has been widely investigated for diagnosis and treatment strategy design, with some models proposed for detecting oral pharyngeal, nasopharyngeal, or laryngeal carcinoma. However, no co...

    Lei Zhou, Huaili Jiang, Guangyao Li, Jiaye Ding, Cuicui Lv… in BMC Medical Imaging (2023)

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  5. No Access

    Chapter and Conference Paper

    Data Reconstruction from Gradient Updates in Federated Learning

    Federated learning has become an emerging technology to protect data privacy in the distributed learning area, by kee** each client user’s data locally. However, recent work shows that client users’ data mig...

    **aoxue Zhang, Junhao Li, Jianjie Zhang, Jijie Yan… in Machine Learning for Cyber Security (2023)

  6. No Access

    Chapter and Conference Paper

    Data Leakage with Label Reconstruction in Distributed Learning Environments

    Distributed learning is commonly applied for the high demands of computation resources while training models with large-scale data. However, existing solutions revealed that it may lead to information leakage ...

    **aoxue Zhang, **uhua Zhou, Kongyang Chen in Machine Learning for Cyber Security (2023)

  7. No Access

    Article

    CRSM: a practical crowdsourcing-based road surface monitoring system

    Detecting road potholes and road roughness levels is key to road condition monitoring, which impacts transport safety and driving comfort. We propose a crowdsourcing-based road surface monitoring system, simpl...

    Kongyang Chen, Guang Tan, Mingming Lu, Jie Wu in Wireless Networks (2016)