000 04326nam a22004575i 4500
710 2 _aSpringerLink (Online service)
_9106996
999 _c111057
_d111057
001 111057
003 ES-MaUEC
005 20230102113452.0
006 a||||fo|||| 00| 0
007 cr nn nnnaamaa
008 190325s2019 gw a o |||| 0|eng d
020 _a9783030133702
024 7 _a10.1007/978-3-030-13370-2
_2doi
040 _bspa
_dES-MaUEC
_cES-MaUEC
050 4 _aQA76.9.A25
_b2019 EB
100 1 _aPan, Miao,
_eautor
_4aut
_9673181
_d1981-
245 1 0 _aBig Data Privacy Preservation for Cyber-Physical Systems
_cby Miao Pan, Jingyi Wang, Sai Mounika Errapotu, Xinyue Zhang, Jiahao Ding, Zhu Han.
264 1 _aCham
_bSpringer International Publishing :
_bImprint: Springer
_c2019.
300 _a1 recurso en línea (IX, 73 páginas)
_b25 ilustraciones, 23 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aEngineering (Springer-11647)
490 0 _aSpringerBriefs in Electrical and Computer Engineering
_x2191-8112
505 0 _aChapter 1 Cyber-Physical Systems -- Chapter 2 Preliminaries -- Chapter 3 Spectrum Trading with Secondary Users' Privacy Protection -- Chapter 4 Optimization for Utility Providers with Privacy Preservation of Users' Energy Profile -- Chapter 5 Caching with Users' Differential Privacy Preservation in Information-Centric Networks -- Chapter 6 Clock Auction Inspired Privacy Preservation in Colocation Data Centers.
520 3 _aThis 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 big data analysis in these large scale systems. Data breaches result in undesirable loss of privacy for the participants and for the entire system, therefore identifying the vulnerabilities and developing tools to mitigate such concerns is crucial to build high confidence CPS. This Springerbrief targets professors, professionals and research scientists working in Wireless Communications, Networking, Cyber-Physical Systems and Data Science. Undergraduate and graduate-level students interested in Privacy Preservation of state-of-the-art Wireless Networks and Cyber-Physical Systems will use this Springerbrief as a study guide. .
988 _aPrimersemestre_2019_Engineering
650 7 _2embne
_9495511
_aDatos masivos
_xMedidas de seguridad
700 1 _aDing, Jiahao.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aErrapotu, Sai Mounika.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aHan, Zhu
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_999469
700 1 _aWang, Jingyi.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aZhang, Xinyue.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
776 0 8 _iPrinted edition:
_z9783030133696
776 0 8 _iPrinted edition:
_z9783030133719
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-13370-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _dz
_feng
_ggw
_h0
_b04/2020
_ea
_zSI