An indispensable survival guide for anyone in the media industry and the lawyers who serve them Especially now, in an age of instant global access through digital media, it is vitally important that journalists, authors and publishers, as well as the lawyers who serve them, be fully up on the laws governing media, worldwide. The ultimate resource for all the media content providers and purveyors, this fully updated and expanded Third Edition of the critically-acclaimed handbook offers you instant access to relevant libel and privacy laws and important legal rulings in the Europe, Asia, the Middle East and the Americas. It clearly and concisely explains risks publishers should know about prior to publication, steps they can take in order to avoid legal conflicts, and legal defences available to them in the event of a claim. Offers nation-by-nation summaries of libel and privacy law written by local practitioners in an easy-to-use reference format Expanded to include coverage of important emerging territories--Mexico, Israel, and Argentina, et al--as well as the latest libel and privacy rulings Features new chapters on emerging media markets--including Israel, Mexico, Argentina, Jordan, and others--as well as valuable updates to the Middle East section Provides updates on all major media markets and nations, along with coverage of changes in libel laws in key jurisdictions, including Australia, the UK, Hungary and Germany

The definitive guide for ensuring data privacy and GDPR compliance Privacy regulation is increasingly rigorous around the world and has become a serious concern for senior management of companies regardless of industry, size, scope, and geographic area. The Global Data Protection Regulation (GDPR) imposes complex, elaborate, and stringent requirements for any organization or individuals conducting business in the European Union (EU) and the European Economic Area (EEA)—while also addressing the export of personal data outside of the EU and EEA. This recently-enacted law allows the imposition of fines of up to 5% of global revenue for privacy and data protection violations. Despite the massive potential for steep fines and regulatory penalties, there is a distressing lack of awareness of the GDPR within the business community. A recent survey conducted in the UK suggests that only 40% of firms are even aware of the new law and their responsibilities to maintain compliance. The Data Privacy and GDPR Handbook helps organizations strictly adhere to data privacy laws in the EU, the USA, and governments around the world. This authoritative and comprehensive guide includes the history and foundation of data privacy, the framework for ensuring data privacy across major global jurisdictions, a detailed framework for complying with the GDPR, and perspectives on the future of data collection and privacy practices. Comply with the latest data privacy regulations in the EU, EEA, US, and others Avoid hefty fines, damage to your reputation, and losing your customers Keep pace with the latest privacy policies, guidelines, and legislation Understand the framework necessary to ensure data privacy today and gain insights on future privacy practices The Data Privacy and GDPR Handbook is an indispensable resource for Chief Data Officers, Chief Technology Officers, legal counsel, C-Level Executives, regulators and legislators, data privacy consultants, compliance officers, and audit managers.

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

Businesses are rushing to collect personal data to fuel surging demand. Data enthusiasts claim personal information that's obtained from the commercial internet, including mobile platforms, social networks, cloud computing, and connected devices, will unlock path-breaking innovation, including advanced data security. By contrast, regulators and activists contend that corporate data practices too often disempower consumers by creating privacy harms and related problems. As the Internet of Things matures and facial recognition, predictive analytics, big data, and wearable tracking grow in power, scale, and scope, a controversial ecosystem will exacerbate the acrimony over commercial data capture and analysis. The only productive way forward is to get a grip on the key problems right now and change the conversation. That's exactly what Jules Polonetsky, Omer Tene, and Evan Selinger do. They bring together diverse views from leading academics, business leaders, and policymakers to discuss the opportunities and challenges of the new data economy.

'The Handbook of Privacy Studies' is the first book in the world that brings together several disciplinary perspectives on privacy, such as the legal, ethical, medical, informatics and anthropological perspective. Privacy is in the news almost every day: mass surveillance by intelligence agencies, the use of social media data for commercial profit and political microtargeting, password hacks and identity theft, new data protection regimes, questionable reuse of medical data, and concerns about how algorithms shape the way we think and decide. This book offers interdisciplinary background information about these developments and how to understand and properly evaluate them. The book is set up for use in interdisciplinary educational programmes. Each chapter provides a structured analysis of the role of privacy within that discipline, its characteristics, themes and debates, as well as current challenges. Disciplinary approaches are presented in such a way that students and researchers from every scientific background can follow the argumentation and enrich their own understanding of privacy issues.

This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts of demographic, diagnosis, medication, and genomic information. It presents privacy-preserving methods for medical data, ranging from laboratory test results to doctors’ comments. The reuse of EMR data can greatly benefit medical science and practice, but must be performed in a privacy-preserving way according to data sharing policies and regulations. Written by world-renowned leaders in this field, each chapter offers a survey of a research direction or a solution to problems in established and emerging research areas. The authors explore scenarios and techniques for facilitating the anonymization of different types of medical data, as well as various data mining tasks. Other chapters present methods for emerging data privacy applications and medical text de-identification, including detailed surveys of deployed systems. A part of the book is devoted to legislative and policy issues, reporting on the US and EU privacy legislation and the cost of privacy breaches in the healthcare domain. This reference is intended for professionals, researchers and advanced-level students interested in safeguarding medical data.

The rapid development of information technology has exacerbated the need for robust personal data protection, the right to which is safeguarded by both European Union (EU) and Council of Europe (CoE) instruments. Safeguarding this important right entails new and significant challenges as technological advances expand the frontiers of areas such as surveillance, communication interception and data storage. This handbook is designed to familiarise legal practitioners not specialised in data protection with this emerging area of the law. It provides an overview of the EU’s and the CoE’s applicable legal frameworks. It also explains key case law, summarising major rulings of both the Court of Justice of the European Union and the European Court of Human Rights. In addition, it presents hypothetical scenarios that serve as practical illustrations of the diverse issues encountered in this ever-evolving field.

The whirlwind of social media, online dating, and mobile apps can make life a dream—or a nightmare. For every trustworthy website, there are countless jerks, bullies, and scam artists who want to harvest your personal information for their own purposes. But you can fight back, right now. In The Smart Girl’s Guide to Privacy, award-winning author and investigative journalist Violet Blue shows you how women are targeted online and how to keep yourself safe. Blue’s practical, user-friendly advice will teach you how to: –Delete personal content from websites –Use website and browser privacy controls effectively –Recover from and prevent identity theft –Figure out where the law protects you—and where it doesn’t –Set up safe online profiles –Remove yourself from people-finder websites Even if your privacy has already been compromised, don’t panic. It’s not too late to take control. Let The Smart Girl’s Guide to Privacy help you cut through the confusion and start protecting your online life.

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.