Data Privacy: A Runbook for Engineers
暫譯: 數據隱私:工程師運行手冊
Bhajaria, Nishant
- 出版商: Manning
- 出版日期: 2022-02-15
- 售價: $1,750
- 貴賓價: 9.5 折 $1,663
- 語言: 英文
- 頁數: 384
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617298999
- ISBN-13: 9781617298998
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相關分類:
資料庫、Data Science、資訊安全
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商品描述
Engineer privacy into your systems with these hands-on techniques for data governance, legal compliance, and surviving security audits.
"I wish I had had this text in 2015 or 2016 at Netflix, and it would have been very helpful in 2008–2012 in a time of significant architectural evolution of our technology."
Neil Hunt, Former CPO, Netflix
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.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
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.
Editorial Reviews
Review
"I wish I had had this text in 2015 or 2016 at Netflix, and it would have been very helpful in 2008-2012 in a time of significant architectural evolution of our technology."
—From the Foreword by Neil Hunt, Former Chief Product Officer, Netflix
"Nishant's timely and powerful book is a must read, must share and must commit to action gem in the hands of every leader in the digital economy of today and forevermore. We can't uninvent fire & won't stop observing and sharing data."
—Michelle Finneran Dennedy, former Chief Privacy Officer at Cisco and author of The Privacy Engineer's Manifesto
"An indispensable guide for practitioners -- engineers, data scientists, and attorneys -- on how to build a world-class privacy program."
—Matthew G Olsen, former Uber Chief Trust and Security Officer.
"Bhajaria's succinct and practical frameworks are required reading for anyone who needs to quickly understand how privacy is operationalized to reduce business and engineering friction."
-—Melanie Ensign, Founder and CEO, Discernible Inc and advisor to "The Rise of Privacy Tech"
"The best parts are the personal elements you add to the narrative. I also enjoyed the case studies that help to illustrate the examples you provide throughout."
—Ayana Miller, Privacy & Data Protection Advisor, former Privacy specialist at the Federal Trade Commission (FTC)
"Your guide to building privacy into the fabric of your organization."
—John Tyler, Vice President at JPMorgan Chase
"The most comprehensive resource you can find about privacy."
—Diego Casella, Sr. Software Engineer at InvestSuite
"Offers some valuable insights and direction for enterprises looking to improve the privacy of their data."
—Dr. Peter White, Lecturer at Charles Sturt University
商品描述(中文翻譯)
工程師在系統中融入隱私,使用這些實用技術來進行數據治理、法律合規以及應對安全審計。
「我希望在2015或2016年於Netflix時能擁有這本書,這在2008年至2012年我們技術架構重大演變的時期會非常有幫助。」
——Neil Hunt,前Netflix首席產品官
在《數據隱私》中,您將學習如何:
- 根據隱私風險對數據進行分類
- 建立技術工具以編目和發現系統中的數據
- 使用技術隱私控制共享數據,以衡量重新識別風險
- 實施技術隱私架構以刪除數據
- 設置數據導出技術能力,以滿足法律要求,如數據主體資產請求(DSAR)
- 建立技術隱私審查流程,以幫助加速法律隱私影響評估(PIA)
- 設計同意管理平台(CMP)以捕捉用戶同意
- 實施安全工具以幫助優化隱私
- 建立一個全面的計劃,以獲得C級高管和董事會的支持和資金
《數據隱私》教您設計、開發和衡量隱私計劃的有效性。您將從作者Nishant Bhajaria那裡學習,他是行業知名的專家,曾在Google、Netflix和Uber負責隱私。隱私的術語和法律要求都以清晰、無行話的語言解釋。這本書對商業需求的持續關注將幫助您平衡取捨,確保用戶的隱私可以在不增加時間和資源成本的情況下得到改善。
購買印刷版書籍包括免費的PDF、Kindle和ePub格式電子書,來自Manning Publications。
關於技術
數據隱私對任何企業都是至關重要的。數據洩露、模糊的政策和糟糕的溝通都會侵蝕用戶對您應用程序的信任。您還可能面臨未能保護用戶數據的重大法律後果。幸運的是,有明確的實踐和指導方針可以保持您的數據安全,並讓您的用戶滿意。
關於這本書
《數據隱私:工程師的運行手冊》教您如何在嚴格的數據安全和現實商業需求之間進行取捨。在這本實用的書中,您將學習如何設計和實施易於擴展和自動化的隱私計劃。沒有官僚程序——只有可行的解決方案和智能的現有安全工具的重新利用,以幫助設定和實現您的隱私目標。
內容包括:
- 根據隱私風險對數據進行分類
- 設置符合法律要求的數據導出能力
- 建立審查流程以加速隱私影響評估
- 設計同意管理平台以捕捉用戶同意
關於讀者
適合希望提供更好隱私的工程師和商業領導者。
編輯評價
「我希望在2015或2016年於Netflix時能擁有這本書,這在2008-2012年我們技術架構重大演變的時期會
作者簡介
Nishant Bhajaria leads the Technical Privacy and Strategy teams for Uber. He heads a large team that includes data scientists, engineers, privacy experts and others as they seek to improve data privacy for the customers and the company. His role has significant levels of cross-functional visibility and impact. Previously he worked in compliance, data protection, security, and privacy at Google. He was also the head of privacy engineering at Netflix. He is a well-known expert in the field of data privacy, has developed numerous courses on the topic, and has spoken extensively at conferences and podcasts.
作者簡介(中文翻譯)
Nishant Bhajaria 目前負責 Uber 的技術隱私與策略團隊。他領導著一個龐大的團隊,成員包括數據科學家、工程師、隱私專家等,致力於改善客戶和公司的數據隱私。他的角色具有顯著的跨功能可見性和影響力。之前,他曾在 Google 從事合規性、數據保護、安全性和隱私相關的工作。他也曾擔任 Netflix 的隱私工程部門負責人。他是數據隱私領域的知名專家,開發了多個相關課程,並在各種會議和播客中廣泛發表演講。
目錄大綱
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
目錄大綱(中文翻譯)
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