With "Obfuscation," Finn Brunton and Helen Nissenbaum mean to start a revolution. They are calling us not to the barricades but to our computers, offering us ways to fight today's pervasive digital surveillance -- the collection of our data by governments, corporations, advertisers, and hackers. To the toolkit of privacy protecting techniques and projects, they propose adding obfuscation: the deliberate use of ambiguous, confusing, or misleading information to interfere with surveillance and data collection projects. Brunton and Nissenbaum provide tools and a rationale for evasion, noncompliance, refusal, even sabotage -- especially for average users, those of us not in a position to opt out or exert control over data about ourselves. "Obfuscation" will teach users to push back, software developers to keep their user data safe, and policy makers to gather data without misusing it. Brunton and Nissenbaum present a guide to the forms and formats that obfuscation has taken and explain how to craft its implementation to suit the goal and the adversary. They describe a series of historical and contemporary examples, including radar chaff deployed by World War II pilots, Twitter bots that hobbled the social media strategy of popular protest movements, and software that can camouflage users' search queries and stymie online advertising. They go on to consider obfuscation in more general terms, discussing why obfuscation is necessary, whether it is justified, how it works, and how it can be integrated with other privacy practices and technologies.
A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.
The essays in Digital Media and Democratic Futures provide deep insights into the complex and context-dependent relationship between media and democracy and show that there is no single outcome for democracy in the digital age, only possible futures.
Data Protection by Design and Default for the Internet of Things
Author: Aurelia Tamò-Larrieux
This book discusses the implementation of privacy by design in Europe, a principle that has been codified within the European Data Protection Regulation (GDPR). While privacy by design inspires hope for future privacy-sensitive designs, it also introduces the need for a common understanding of the legal and technical concepts of privacy and data protection. By pursuing an interdisciplinary approach and comparing the problem definitions and objectives of both disciplines, this book bridges the gap between the legal and technical fields in order to enhance the regulatory and academic discourse. The research presented reveals the scope of legal principles and technical tools for privacy protection, and shows that the concept of privacy by design goes beyond the principle of the GDPR. The book presents an analysis of how current regulations delegate the implementation of technical privacy and data protection measures to developers and describes how policy design must evolve in order to implement privacy by design and default principles.
This book examines privacy in public space from both legal and regulatory perspectives. With on-going technological innovations such as mobile cameras, WiFi tracking, drones and augmented reality, aspects of citizens’ lives are increasingly vulnerable to intrusion. The contributions describe contemporary challenges to achieving privacy and anonymity in physical public space, at a time when legal protection remains limited compared to ‘private’ space. To address this problem, the book clearly shows why privacy in public space needs defending. Different ways of conceptualizing and shaping such protection are explored, for example through ‘privacy bubbles’, obfuscation and surveillance transparency, as well as revising the assumptions underlying current privacy laws.