Machine Learning and Behavioral Analysis Enables DBN-6300 to Immediately Identify Advanced Persistent Threats

SAN DIEGO, April 14, 2015 /PRNewswire/ -- DB Networks, an innovator of intelligent continuous monitoring, today announced that the machine learning and behavioral analysis capabilities of the DBN-6300 immediately identify Advanced Persistent Threats (APTs) in the earliest phases of their operation.

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APTs continue to threaten the databases of government agencies and enterprises across all sectors ­and have become a truly systemic issue for cybersecurity professionals. APTs have been the criminal's weapon of choice in many high-profile database attacks including the 2013 Target Corporation breach and the recent Anthem breach. In addition, in 2014 more than half of the cybersecurity incidents reported to the Department of Homeland Security's (DHS) Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) involved APTs.

"APT is a targeted zero-day attack by its very nature. Therefore, signature-based cybersecurity defenses that require having seen the threat previously are simply ineffective," said Brett Helm, Chairman and CEO of DB Networks. "Machine learning and behavioral analysis cybersecurity technologies are uniquely suited to immediately identify the APT class of cyber attack."

DB Networks' DBN-6300 automatically learns the behavioral nature of an organization's entire database infrastructure and identifies anomalies that could pose a risk. Although there are many different behaviors expressed by APTs, common themes include attempting to gain unauthorized access to financial, corporate or intellectual property stored on databases. Attackers often attempt to gain unauthorized access into numerous databases across an organization in order to obtain the specific information they are seeking.

The DBN-6300 will generate alerts when a client demonstrates abnormal behavior. For example, when a client that has never before accessed a particular database does so for the first time an alarm will be raised. Often this capability alone will identify an APT in its earliest phase before any information has been breached. However, the DBN-6300 offers capabilities far beyond this in identifying complex APTs. The DBN-6300 will identify when a database interaction crosses a trust boundary, when database traffic trends changes by volume or time of day, and when rogue SQL statements are dispatched from an application during a SQL injection attack.

Further, the DBN-6300 offers security analysts a suite of analytical and visualization tools to quickly perform a comprehensive analysis of any threat that has been identified. This is a game changer because presently APTs are identified on average 205 days after the victim has been compromised, according to Mandiant M-Trends, whereas the DBN-6300 identifies APTs immediately.

For a personal demonstration of the DB Networks' DBN-6300 and the opportunity to meet with members of the team, visit DB Networks at the RSA Conference - Booth # 907 South Hall at the Moscone Center in San Francisco from April 20-24. 

About DB Networks®

DB Networks® innovates cybersecurity through intelligent continuous monitoring. Our customers include the world's largest financial institutions, healthcare providers, manufacturers and governments. DB Networks' unique approach to database security utilizes machine learning to automatically create a model of each application's proper database interactions and then applies behavioral analysis to accurately and immediately identify attacks. With no signature files to deal with or endless false positives to chase down, operational support becomes trivial. DB Networks is a privately held company headquartered in San Diego, California. For more additional information call (800) 598-0450 or visit our website, Twitter page, LinkedIn page, Google+ page, and YouTube channel.

Contact:  
Rita Rheinecker
(800) 598-0450
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SOURCE DB Networks

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