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Covering classical cryptography, modern cryptography, and steganography, this volume details how data can be kept secure and private. Each topic is presented and explained by describing various methods, techniques, and algorithms. Moreover, there are numerous helpful examples to reinforce the reader's understanding and expertise with these techniques and methodologies. Features & Benefits: * Incorporates both data encryption and data hiding * Supplies a wealth of exercises and solutions to help readers readily understand the material * Presents information in an accessible, nonmathematical style * Concentrates on specific methodologies that readers can choose from and pursue, for their data-security needs and goals * Describes new topics, such as the advanced encryption standard (Rijndael), quantum cryptography, and elliptic-curve cryptography. The book, with its accessible style, is an essential companion for all security practitioners and professionals who need to understand and effectively use both information hiding and encryption to protect digital data and communications. It is also suitable for self-study in the areas of programming, software engineering, and security.
This comprehensive reference covers the laws governing every area where data privacy and security is potentially at risk -- including government records, electronic surveillance, the workplace, medical data, financial information, commercial transactions, and online activity, including communications involving children.
Engineer privacy into your systems with these hands-on techniques for data governance, legal compliance, and surviving security audits. In Data Privacy you will learn how to: Classify data based on privacy risk Build technical tools to catalog and discover data in your systems Share data with technical privacy controls to measure reidentification risk Implement technical privacy architectures to delete data Set up technical capabilities for data export to meet legal requirements like Data Subject Asset Requests (DSAR) Establish a technical privacy review process to help accelerate the legal Privacy Impact Assessment (PIA) Design a Consent Management Platform (CMP) to capture user consent Implement security tooling to help optimize privacy Build a holistic program that will get support and funding from the C-Level and board Data Privacy teaches you to design, develop, and measure the effectiveness of privacy programs. You’ll learn from author Nishant Bhajaria, an industry-renowned expert who has overseen privacy at Google, Netflix, and Uber. The terminology and legal requirements of privacy are all explained in clear, jargon-free language. The book’s constant awareness of business requirements will help you balance trade-offs, and ensure your user’s privacy can be improved without spiraling time and resource costs. About the technology Data privacy is essential for any business. Data breaches, vague policies, and poor communication all erode a user’s trust in your applications. You may also face substantial legal consequences for failing to protect user data. Fortunately, there are clear practices and guidelines to keep your data secure and your users happy. About the book Data Privacy: A runbook for engineers teaches you how to navigate the trade-off s between strict data security and real world business needs. In this practical book, you’ll learn how to design and implement privacy programs that are easy to scale and automate. There’s no bureaucratic process—just workable solutions and smart repurposing of existing security tools to help set and achieve your privacy goals. What's inside Classify data based on privacy risk Set up capabilities for data export that meet legal requirements Establish a review process to accelerate privacy impact assessment Design a consent management platform to capture user consent About the reader For engineers and business leaders looking to deliver better privacy. About the author Nishant Bhajaria leads the Technical Privacy and Strategy teams for Uber. His previous roles include head of privacy engineering at Netflix, and data security and privacy at Google. Table of Contents PART 1 PRIVACY, DATA, AND YOUR BUSINESS 1 Privacy engineering: Why it’s needed, how to scale it 2 Understanding data and privacy PART 2 A PROACTIVE PRIVACY PROGRAM: DATA GOVERNANCE 3 Data classification 4 Data inventory 5 Data sharing PART 3 BUILDING TOOLS AND PROCESSES 6 The technical privacy review 7 Data deletion 8 Exporting user data: Data Subject Access Requests PART 4 SECURITY, SCALING, AND STAFFING 9 Building a consent management platform 10 Closing security vulnerabilities 11 Scaling, hiring, and considering regulations
Author : June M. Sullivan Publisher : American Bar Association Page : 274 pages File Size : 30,30 MB Release : 2004 Category : Law ISBN : 9781590313961
This concise, practical guide helps the advocate understand the sometimes dense rules in advising patients, physicians, and hospitals, and in litigating HIPAA-related issues.
As the world has adapted to the age of digital technology, present day business leaders are required to change with the times as well. Addressing and formatting their business practices to not only encompass digital technologies, but expand their capabilities, the leaders of today must be flexible and willing to familiarize themselves with all types of global business practices. Global Business Leadership Development for the Fourth Industrial Revolution is a collection of advanced research on the methods and tactics utilized to succeed as a leader in the digital age. While highlighting topics including data privacy, corporate governance, and risk management, this book is ideally designed for business professionals, administrators, managers, executives, researchers, academicians, and business students who want to improve their understanding of the strategic role of digital technologies in the global economy, in networks and organizations, in teams and work groups, in information systems, and at the level of individuals as actors in digitally networked environments
This book provides an overview of the most recent developments in Internet of Things (IoT) security and data protection. It presents the results of several international research projects addressing this topic from complementary angles. It starts by analyzing the main privacy and security threats on IoT, as well as the evolution of data protection norms, such as the European General Data Protection Regulation (GDPR), and their impact on IoT. Through a comprehensive and systematic approach, the contributors present new perspectives on IoT & Cloud Computing security requirements. They discuss the most recent approach to support trusted IoT, including new models of privacy risk assessment, labeling and certification, and contractual tools (such as Privacy PACT). Practical implementations, such as in the European Large Scale Pilots on IoT for Smart Cities (Synchronicity), are presented, explaining how they address security, privacy and data protection. Finally, innovative models to secure IoT systems are presented for the network and end-nodes security, including network threats analysis.
In recent years, technological advances have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Privacy and Security Policies in Big Data is a pivotal reference source for the latest research on innovative concepts on the management of security and privacy analytics within big data. Featuring extensive coverage on relevant areas such as kinetic knowledge, cognitive analytics, and parallel computing, this publication is an ideal resource for professionals, researchers, academicians, advanced-level students, and technology developers in the field of big data.
Privacy and data protection in police work and law enforcement cooperation has always been a challenging issue. Current developments in EU internal security policy, such as increased information sharing (which includes the exchange of personal data between European law enforcement agencies and judicial actors in the area of freedom, security and justice (Europol, Eurojust, Frontex and OLAF)) and the access of EU agencies, in particular Europol and Eurojust, to data stored in European information systems such as the SIS (II), VIS, CIS or Eurodac raise interesting questions regarding the balance between the rights of individuals and security interests. This book deals with the complexity of the relations between these actors and offers for the first time a comprehensive overview of the structures for information exchange in the area of freedom, security and justice and their compliance with data protection rules in this field.
It is essential for an organization to know before involving themselves in cloud computing and big data, what are the key security requirements for applications and data processing. Big data and cloud computing are integrated together in practice. Cloud computing offers massive storage, high computation power, and distributed capability to support processing of big data. In such an integrated environment the security and privacy concerns involved in both technologies become combined. This book discusses these security and privacy issues in detail and provides necessary insights into cloud computing and big data integration. It will be useful in enhancing the body of knowledge concerning innovative technologies offered by the research community in the area of cloud computing and big data. Readers can get a better understanding of the basics of cloud computing, big data, and security mitigation techniques to deal with current challenges as well as future research opportunities.
With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.