دانلود مقاله انگلیسی رایگان:فدراسیون دانش: یک چارچوب متحد و سلسله مراتبی حفظ حریم خصوصی هوش مصنوعی - 2020
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  • Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework
    Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework


    ترجمه فارسی عنوان مقاله:

    فدراسیون دانش: یک چارچوب متحد و سلسله مراتبی حفظ حریم خصوصی هوش مصنوعی


    منبع:

    IEEE - 2020 IEEE International Conference on Knowledge Graph (ICKG);2020; ; ;10.1109/ICBK50248.2020.00022


    نویسنده:

    Hongyu Li, Dan Meng, Hong Wang, Xiaolin Li


    چکیده انگلیسی:

    With strict protections and regulations of data privacy and security, conventional machine learning based on centralized datasets is confronted with significant challenges, making artificial intelligence (AI) impractical in many missioncritical and data-sensitive scenarios, such as finance, government, and health. In the meantime, tremendous datasets are scattered in isolated silos in various industries, organizations, different units of an organization, or different branches of an international organization. These valuable data resources are well underused. To advance AI theories and applications, we propose a comprehensive framework (called Knowledge Federation - KF) to address these challenges by enabling AI while preserving data privacy and ownership. Beyond the concepts of federated learning and secure multi-party computation, KF consists of four levels of federation: (1) information level, low-level statistics and computation of data, meeting the requirements of simple queries, searching and simplistic operators; (2) model level, supporting training, learning, and inference; (3) cognition level, enabling abstract feature representation at various levels of abstractions and contexts; (4) knowledge level, fusing knowledge discovery, representation, and reasoning. We further clarify the relationship and differentiation between knowledge federation and other related research areas. We have developed a reference implementation of KF, called iBond Platform, to offer a productionquality KF platform to enable industrial applications in finance, insurance, marketing, and government. The iBond platform will also help establish the KF community and a comprehensive ecosystem and usher in a novel paradigm shift towards secure, privacy-preserving and responsible AI. As far as we know, knowledge federation is the first hierarchical and unified framework for secure multi-party computing (statistics, queries, searching, and low-level operations) and learning (training, representation, discovery, inference, and reasoning).
    Index Terms: Knowledge Federation |Knowledge | Federated Learning | Secure Multi-party Computation | Secure Multi-party Learning


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 8
    حجم فایل: 539 کیلوبایت

    قیمت: رایگان


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