| 期刊全称 | Big Data Privacy Preservation for Cyber-Physical Systems | | 影响因子2023 | Miao Pan,Jingyi Wang,Zhu Han | | 视频video | | | 发行地址 | This book addresses the processing limitations of massive data without disclosing users’ privacy in various CPS applications, a major concern in real-time big data analytics to achieve better data man | | 学科分类 | SpringerBriefs in Electrical and Computer Engineering | | 图书封面 |  | | 影响因子 | .This SpringerBrief mainly focuses on effective big data analytics for CPS, and addresses the privacy issues that arise on various CPS applications. The authors develop a series of privacy preserving data analytic and processing methodologies through data driven optimization based on applied cryptographic techniques and differential privacy in this brief. This brief also focuses on effectively integrating the data analysis and data privacy preservation techniques to provide the most desirable solutions for the state-of-the-art CPS with various application-specific requirements. .Cyber-physical systems (CPS) are the “next generation of engineered systems,” that integrate computation and networking capabilities to monitor and control entities in the physical world. Multiple domains of CPS typically collect huge amounts of data and rely on it for decision making, where the data may include individual or sensitive information, for e.g., smart metering, intelligent transportation, healthcare, sensor/data aggregation, crowd sensing etc. This brief assists users working in these areas and contributes to the literature by addressing data privacy concerns during collection, computation or | | Pindex | Book 2019 |
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发表于 2025-3-21 17:49:25
