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Author: Guy Bunker
Publisher: John Wiley & Sons
ISBN: 0470474645
Category : Computers
Languages : en
Pages : 572
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Book Description
Data leaks expose your customers to identity theft and your business to security risks. But how do you set up a data loss prevention plan? Start with Data Leaks For Dummies! Now more than ever, it’s critical to keep your company data locked up tighter than Fort Knox. Data Leaks For Dummies has the scoop on what’s at risk, how leaks happen, how to keep your data safe without being inflexible, and even what to do if the worst happens. It shows you how to: Identify risk by learning to see your data the way a criminal would Recognize how innocent mistakes, common carelessness, and malicious insiders also pose a threat Learn how to defend against phishing, e-mail threats, and wireless security breaches Be alert for social engineering attacks, suspicious contract workers, dumpster divers, and plain old eavesdroppers Plan for safe disposal of old hardware, use caution with SMS and e-mail archives, and be aware of how Webcasts and conference calls can be invaded Discover how crooks steal data in public places such as Internet cafes Develop a recovery plan, build a team, and even manage press coverage should data loss occur You’ll learn why free data storage devices could cost you a lot, how to protect mobile devices, why data corruption might be even worse than data loss, and how you can help software developers build safer applications. Data Leaks For Dummies will help you protect your customers, the reputation of your business, and your bottom line.
Author: Guy Bunker
Publisher: John Wiley & Sons
ISBN: 0470474645
Category : Computers
Languages : en
Pages : 572
Get Book Here
Book Description
Data leaks expose your customers to identity theft and your business to security risks. But how do you set up a data loss prevention plan? Start with Data Leaks For Dummies! Now more than ever, it’s critical to keep your company data locked up tighter than Fort Knox. Data Leaks For Dummies has the scoop on what’s at risk, how leaks happen, how to keep your data safe without being inflexible, and even what to do if the worst happens. It shows you how to: Identify risk by learning to see your data the way a criminal would Recognize how innocent mistakes, common carelessness, and malicious insiders also pose a threat Learn how to defend against phishing, e-mail threats, and wireless security breaches Be alert for social engineering attacks, suspicious contract workers, dumpster divers, and plain old eavesdroppers Plan for safe disposal of old hardware, use caution with SMS and e-mail archives, and be aware of how Webcasts and conference calls can be invaded Discover how crooks steal data in public places such as Internet cafes Develop a recovery plan, build a team, and even manage press coverage should data loss occur You’ll learn why free data storage devices could cost you a lot, how to protect mobile devices, why data corruption might be even worse than data loss, and how you can help software developers build safer applications. Data Leaks For Dummies will help you protect your customers, the reputation of your business, and your bottom line.
Author: Asaf Shabtai
Publisher: Springer Science & Business Media
ISBN: 1461420520
Category : Computers
Languages : en
Pages : 98
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Book Description
SpringerBriefs present concise summaries of cutting-edge research and practical applications across a wide spectrum of fields. Featuring compact volumes of 50 to 100 pages (approximately 20,000- 40,000 words), the series covers a range of content from professional to academic. Briefs allow authors to present their ideas and readers to absorb them with minimal time investment. As part of Springer’s eBook collection, SpringBriefs are published to millions of users worldwide. Information/Data Leakage poses a serious threat to companies and organizations, as the number of leakage incidents and the cost they inflict continues to increase. Whether caused by malicious intent, or an inadvertent mistake, data loss can diminish a company’s brand, reduce shareholder value, and damage the company’s goodwill and reputation. This book aims to provide a structural and comprehensive overview of the practical solutions and current research in the DLP domain. This is the first comprehensive book that is dedicated entirely to the field of data leakage and covers all important challenges and techniques to mitigate them. Its informative, factual pages will provide researchers, students and practitioners in the industry with a comprehensive, yet concise and convenient reference source to this fascinating field. We have grouped existing solutions into different categories based on a described taxonomy. The presented taxonomy characterizes DLP solutions according to various aspects such as: leakage source, data state, leakage channel, deployment scheme, preventive/detective approaches, and the action upon leakage. In the commercial part we review solutions of the leading DLP market players based on professional research reports and material obtained from the websites of the vendors. In the academic part we cluster the academic work according to the nature of the leakage and protection into various categories. Finally, we describe main data leakage scenarios and present for each scenario the most relevant and applicable solution or approach that will mitigate and reduce the likelihood and/or impact of the leakage scenario.
Author: Lawrence C. Miller
Publisher:
ISBN: 9780470443262
Category : Computer networks
Languages : en
Pages : 0
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Book Description
Author: Lawrence C. Miller
Publisher:
ISBN: 9780470900680
Category : Compliance
Languages : en
Pages : 68
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Book Description
Author: Asaf Shabtai
Publisher: Springer Science & Business Media
ISBN: 1461420539
Category : Computers
Languages : en
Pages : 98
Get Book Here
Book Description
SpringerBriefs present concise summaries of cutting-edge research and practical applications across a wide spectrum of fields. Featuring compact volumes of 50 to 100 pages (approximately 20,000- 40,000 words), the series covers a range of content from professional to academic. Briefs allow authors to present their ideas and readers to absorb them with minimal time investment. As part of Springer’s eBook collection, SpringBriefs are published to millions of users worldwide. Information/Data Leakage poses a serious threat to companies and organizations, as the number of leakage incidents and the cost they inflict continues to increase. Whether caused by malicious intent, or an inadvertent mistake, data loss can diminish a company’s brand, reduce shareholder value, and damage the company’s goodwill and reputation. This book aims to provide a structural and comprehensive overview of the practical solutions and current research in the DLP domain. This is the first comprehensive book that is dedicated entirely to the field of data leakage and covers all important challenges and techniques to mitigate them. Its informative, factual pages will provide researchers, students and practitioners in the industry with a comprehensive, yet concise and convenient reference source to this fascinating field. We have grouped existing solutions into different categories based on a described taxonomy. The presented taxonomy characterizes DLP solutions according to various aspects such as: leakage source, data state, leakage channel, deployment scheme, preventive/detective approaches, and the action upon leakage. In the commercial part we review solutions of the leading DLP market players based on professional research reports and material obtained from the websites of the vendors. In the academic part we cluster the academic work according to the nature of the leakage and protection into various categories. Finally, we describe main data leakage scenarios and present for each scenario the most relevant and applicable solution or approach that will mitigate and reduce the likelihood and/or impact of the leakage scenario.
Author: Arthur J. Deane
Publisher: John Wiley & Sons
ISBN: 111964836X
Category : Computers
Languages : en
Pages : 371
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Book Description
Secure your CSSP certification CCSP is the world’s leading Cloud Security certification. It covers the advanced technical skills and knowledge to design, manage, and secure data, applications, and infrastructure in the cloud using best practices, policies, and procedures. If you’re a cloud security professional seeking your CSSP certification, this book is a perfect way to prepare for the exam. Covering in detail all six domains, the expert advice in this book gives you key information you'll need to pass the exam. In addition to the information covered on the exam, you'll get tips on setting up a study plan, tips for exam day, and access to an online test bank of questions. Key information for all six exam domains Test -taking and exam day tips and tricks Free online practice questions and flashcards Coverage of the core concepts From getting familiar with the core concepts to establishing a study plan, this book is all you need to hang your hat on that certification!
Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1119626110
Category : Computers
Languages : en
Pages : 768
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Book Description
Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 398
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Book Description
Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms. Cut through the equations, Greek letters, and confusion, and discover the specialized data preparation techniques that you need to know to get the most out of your data on your next project. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively prepare your data for predictive modeling with machine learning.
Author: Daniel Vaughan
Publisher: "O'Reilly Media, Inc."
ISBN: 1098146433
Category : Computers
Languages : en
Pages : 244
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Book Description
This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
Author: My T. Thai
Publisher: Springer Nature
ISBN: 3031589238
Category :
Languages : en
Pages : 425
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Book Description
