Published: 01 Aug 2014
In the rush to capitalize on big data, many companies forget that developing an ecosystem of structured and unstructured data means higher risk of leaks and loss and greater exposure to threats.
What technologies should be in place to enforce data security controls on-premises and in the cloud? How can organizations have visibility into third-party providers that access or store their data?
Find out how some enterprises are trying to protect their big-data ecosystems with encryption, security data analysis, visualization and other strategies.
Feature: The NoSQL challenge: What's in store for big data and security
Big data offers horizontal scalability, but how do you get your database security to scale along with it?
Webcast: Adrian Lane on protecting big data with NoSQL security architectures
Big data clusters require a different security model. Four common approaches can help security teams migrate beyond familiar RDBMS techniques, to the tools and processes required in new database environments.
Tip: Is Kerberos the key to big data authentication?
Many Hadoop variants offer fully integrated Kerberos, with facilities to improve setup and link to your existing identity repository.
About the expert: Adrian Lane is a Securosis senior security strategist who specializes in database architecture, data security and secure code development. Prior to joining Securosis, he was the chief technology officer at database security firm IPLocks, vice president of engineering at Touchpoint, and CTO of the secure payment and digital rights management firm Transactor/Brodia. He holds a degree in computer science from the University of California at Berkeley, and did post-graduate work in operating systems at Stanford University.