Applied Stochastic Processes
Auteur : Liao Ming
Many Smart Grid books include "privacy" in their title, but only touch on privacy, with most of the discussion focusing on cybersecurity. Filling this knowledge gap, Data Privacy for the Smart Grid provides a clear description of the Smart Grid ecosystem, presents practical guidance about its privacy risks, and details the actions required to protect data generated by Smart Grid technologies. It addresses privacy in electric, natural gas, and water grids and supplies two different perspectives of the topic?one from a Smart Grid expert and another from a privacy and information security expert.The authors have extensive experience with utilities and leading the U.S. government?s National Institute of Standards and Technologies (NIST) Cyber Security Working Group (CSWG)/Smart Grid Interoperability Group (SGIP) Privacy Subgroup. This comprehensive book is understandable for all those involved in the Smart Grid. The authors detail the facts about Smart Grid privacy so readers can separate truth from myth about Smart Grid privacy. While considering privacy in the Smart Grid, the book also examines the data created by Smart Grid technologies and machine-to-machine (M2M) applications and associated legal issues.The text details guidelines based on the Organization for Economic Cooperation and Development Privacy Guidelines and the U.S. Federal Trade Commission Fair Information Practices. It includes privacy training recommendations and references to additional Smart Grid privacy resources. After reading the book, readers will be prepared to develop informed opinions, establish fact-based decisions, make meaningful contributions to Smart Grid legislation and policies, and to build technologies to preserve and protect privacy. Policy makers; Smart Grid and M2M product and service developers; utility customer and privacy resources; and other service providers and resources are primary beneficiaries of the information provided in
Probability and Stochastic Processes. Poisson Processes. Renewal Processes. Discrete-Time Markov Chains. Continuous-Time Markov Chains. Brownian Motion and Beyond. Bibliography. Index.
Ming Liao is a professor in the Department of Mathematics and Statistics at Auburn University. He has published 45 research papers and one monograph on probability theory. He received a Ph.D. from Stanford University.
Date de parution : 07-2013
15.6x23.4 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 208,65 €
Ajouter au panierDate de parution : 09-2019
15.6x23.4 cm
Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).
Prix indicatif 74,82 €
Ajouter au panierThèmes d’Applied Stochastic Processes :
Mots-clés :
Total Queue Length; Conditional Expectation; Queuing System; Discrete Time MC; Poisson Process; Transition Probabilities Pij; Markov Property; Nonhomogeneous Poisson Process; Delayed Renewal Process; Positive Recurrent; Stationary Renewal Process; Continuous Time MC; Stochastic Integral; Cycle Time; Stochastic Dierential Equations; Irreducible Continuous Time MC; Renewal Reward Process; Phase Type Distribution; MC Xn; Optimal Hedging Portfolio; Option Price Process; Homogeneous Poisson Process; Simple Random Walk; Cycle Time Distribution; Renewal Cycle