Titlebook: Big Data Privacy Preservation for Cyber-Physical Systems; Miao Pan,Jingyi Wang,Zhu Han Book 2019 The Author(s), under exclusive license to

符合規(guī)定

Continuation on Tubular Domains,uncertain and individual SU’s traffic portfolio contains private information. In this chapter, we propose a data-driven spectrum trading scheme which maximizes PUs’ revenue and preserves SUs’ demand differential privacy. Briefly, we introduce a novel network architecture consisting of the PSP, the S

AVID

Continuation on Tubular Domains,ta collected by smart meters helps utility providers accurately predict users’ demands and significantly reduce power generation cost, while it imposes severe privacy risks on consumers and may discourage them from using those “espionage meters”. To enjoy the benefits of smart meter measured data wi

neologism

不連貫

Continuation on Tubular Domains,ption during emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers (e.g., Google), this work studies EDR in multi-tenant colocation data centers (e.g., Equinix) where servers are owned and managed by individual tenants and which

NOMAD

Miao Pan,Jingyi Wang,Zhu HanThis 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

思想流動

SpringerBriefs in Electrical and Computer Engineeringhttp://image.papertrans.cn/b/image/185656.jpg

itinerary

Big Data Privacy Preservation for Cyber-Physical Systems978-3-030-13370-2Series ISSN 2191-8112 Series E-ISSN 2191-8120

個人長篇演說

變態(tài)

https://doi.org/10.1007/978-3-030-13370-2Big Data Analytics; Wireless big data privacy; differential privacy; data-driven optimization; ADMM; mach

悄悄移動