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Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Mayana Pereira, and Michael Shoemate explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases
Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases
Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases
This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.
The author examines issues such as the rightness of web-based applications, the programming language renaissance, spam filtering, the Open Source Movement, Internet startups and more. He also tells important stories about the kinds of people behind technical innovations, revealing their character and their craft.
Threat modeling is one of the most essential--and most misunderstood--parts of the development lifecycle. Whether you're a security practitioner or a member of a development team, this book will help you gain a better understanding of how you can apply core threat modeling concepts to your practice to protect your systems against threats. Contrary to popular belief, threat modeling doesn't require advanced security knowledge to initiate or a Herculean effort to sustain. But it is critical for spotting and addressing potential concerns in a cost-effective way before the code's written--and before it's too late to find a solution. Authors Izar Tarandach and Matthew Coles walk you through various ways to approach and execute threat modeling in your organization. Explore fundamental properties and mechanisms for securing data and system functionality Understand the relationship between security, privacy, and safety Identify key characteristics for assessing system security Get an in-depth review of popular and specialized techniques for modeling and analyzing your systems View the future of threat modeling and Agile development methodologies, including DevOps automation Find answers to frequently asked questions, including how to avoid common threat modeling pitfalls
If you're a leader in Cybersecurity, then you know it often seems like no one cares about--or understands--information security. Infosec professionals struggle to integrate security into their companies. Most are under resourced. Most are at odds with their organizations. There must be a better way. This essential manager's guide offers a new approach to building and maintaining an information security program that's both effective and easy to follow. Author and longtime infosec leader Todd Barnum upends the assumptions security professionals take for granted. CISOs, CSOs, CIOs, and IT security professionals will learn a simple seven-step process that will help you build a new program or improve your current program. Build better relationships with IT and other teams within your organization Align your role with your company's values, culture, and tolerance for information loss Lay the groundwork for your security program Create a communications program to share your team's contributions and educate your coworkers Transition security functions and responsibilities to other teams Organize and build an effective infosec team Measure your progress with two key metrics: your staff's ability to recognize and report security policy violations and phishing emails.
If you hope to outmaneuver threat actors, speed and efficiency need to be key components of your cybersecurity operations. Mastery of the standard command-line interface (CLI) is an invaluable skill in times of crisis because no other software application can match the CLI’s availability, flexibility, and agility. This practical guide shows you how to use the CLI with the bash shell to perform tasks such as data collection and analysis, intrusion detection, reverse engineering, and administration. Authors Paul Troncone, founder of Digadel Corporation, and Carl Albing, coauthor of bash Cookbook (O’Reilly), provide insight into command-line tools and techniques to help defensive operators collect data, analyze logs, and monitor networks. Penetration testers will learn how to leverage the enormous amount of functionality built into nearly every version of Linux to enable offensive operations. In four parts, security practitioners, administrators, and students will examine: Foundations: Principles of defense and offense, command-line and bash basics, and regular expressions Defensive security operations: Data collection and analysis, real-time log monitoring, and malware analysis Penetration testing: Script obfuscation and tools for command-line fuzzing and remote access Security administration: Users, groups, and permissions; device and software inventory
This book addresses the three fundamental properties of V-V resultative constructions in Mandarin Chinese: their generation, their syntactic structure, and their alternations. This book is original and new in the following aspects. First, adopting the ‘inner vs. outer domain’ theory, it provides new analysis and evidence that these compounds are generated in syntax, not in lexicon. Second, this book argues that the two subclasses of V-V resultative constructions, object-oriented vs. subject-oriented V-V resultatives, actually have different structures. Their syntactic contrasts have not been observed in the literature before. Third, this book is new in determining the syntactic structure of the V-V resultative constructions through their adverbial modification properties. It demonstrates that the previous isomorphism analysis of the syntactic structure of Chinese V-V resultatives does not hold. Finally, this book provides a new analysis of the issue of the alternations of V-V resultatives. In contrast to previous analyses, which generally view the causative alternation as the idiosyncratic property of particular V-V compounds, this book provides a principled analysis. This book makes a substantial improvement of the current understanding of the issues in the syntax of Mandarin Chinese and gives new support to certain theories of the generative grammar from the perspective of Mandarin Chinese.
This book provides a database researcher or designer a complete, yet concise, overview of differential privacy and its deployment in database systems.