Database security should be priority, says Forrester

By Erin Kelly | Jun 22, 2009

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When the economy is in a downturn and the fear of layoffs loom, enforcing database security using database monitoring and database encryption tools is fundamental to defending against data leakage and can be implemented even on a tight budget, said Jonathon Penn, principal analyst at Forrester Research Inc.

"[The database] is a target for external attack, it's also a target for abuse and misuse by internal people," Penn said. "So protecting that is important, whether it be monitoring for large downloads by authorized people or monitoring the extent to which they're interacting with the database, whether [their activity] be suspicious or indicate they're taking information with them because they're leaving the company or worried about layoffs."

In the recent report, "TechRadar For SRM Professionals: Database and Server Data Security, Q2 2009," Forrester investigated the current state of eight significant technologies: centralized key management, data classifiers for security, data discovery scanners, database encryption, database monitoring and protecting, outbound Web application filtering and tape and backup encryption.

"We found protecting data is an incredibly complex task, and there is no single technology or process you can put in place in order to safeguard your information," Penn said. "On top of that, threats have become more sophisticated, more targeted, and the criminals behind these attacks have excellent resources at their disposal."

Penn recommended desktop, laptop and full disk encryption as some of the easiest and most cost-effective ways to manage security. However, he stressed that a cost-effective approach is not always about what you go out and buy, but can be as simple as implementing security measures on an ongoing basis.

The report, authored by Forrester senior analyst Andrew Jaquith, claims brute-force technologies like encryption will remain popular and monitoring technologies will also see an uptake in adoption, yet data classification and data discovery technologies that span multiple technology domains still have complexities that need to be worked through.

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