Protect your data from attack by using SQL Server technologies to implement a defense-in-depth strategy, performing threat analysis, and encrypting sensitive data as a last line of defense against compromise.
The multi-layered approach in this book helps ensure that a single breach doesn't lead to loss or compromise of your data that is confidential and important to the business.
Database professionals in today's world deal increasingly often with repeated data attacks against high-profile organizations and sensitive data.
It is more important than ever to keep your company's data secure.
Securing SQL Server demonstrates how administrators and developers can both play their part in the protection of a SQL Server environment. This book provides a comprehensive technical guide to the security model, and to encryption within SQL Server, including coverage of the latest security technologies such as Always Encrypted, Dynamic Data Masking, and Row Level Security.
Most importantly, the book gives practical advice and engaging examples on how to defend your data -- and ultimately your job! -- against attack and compromise. Covers the latest security technologies, including Always Encrypted, Dynamic Data Masking, and Row Level SecurityPromotes security best-practice and strategies for defense-in-depth of business-critical database assets Gives advice on performing threat analysis and reducing the attack surface that your database presents to the outside worldWhat You Will LearnPerform threat analysisImplement access level control and data encryptionAvoid non-reputability by implementing comprehensive auditingUse security metadata to ensure your security policies are enforcedApply the latest SQL Server technologies to increase data securityMitigate the risk of credentials being stolenWho This Book Is For SQL Server database administrators who need to understand and counteract the threat of attacks against their company's data.
The book is also of interest to database administrators of other platforms, as several of the attack techniques are easily generalized beyond SQL Server and to other database brands.