I've been involved in the data analytics and high-tech industries long enough to have seen plenty of new technologies subjected to a degree of hype so great they could never ever measure up. Some of these (fuzzy logic or Google Glass, anyone?) flamed out quickly; others, like artificial intelligence (AI), have had seesawing fortunes spanning decades -- here subject to the loftiest expectations only to be followed there by a'trough of disillusionment' (one of Gartner's hype-cycle stages, and a term I like) as physical, technical and other limitations became evident. Within the sub-domain of AI for security, a collection of technologies known as user behavior analytics (UBA) is now enjoying its own moment of high expectations, much as security information and event management (SIEM) systems did about a decade ago. UBA differs from SIEM in not just aggregating and correlating alerts from different network events but by using a combination of AI and analytical approaches -- including rules-based, pattern-matching and statistical methods, plus supervised and unsupervised machine learning -- to establish baselines of how systems, networks and devices typically behave, and then to detect significant anomalies in their behavior and send alerts to security teams for further investigation. Gartner industry analysts in particular have spent lots of time thinking about UBA.

In this special guest feature, Sekhar Sarukkai, Chief Scientist at Skyhigh Networks, discusses the power of machine learning and user behavior analytics in detecting and mitigating the effects of cyberattacks before financial loss occurs. Sekhar is responsible for driving innovations in cloud security technology. He brings more than 20 years of experience in enterprise networking, security, and cloud services development. Prior to founding Skyhigh Networks, Sekhar was a Sr. Director of Engineering at Cisco Systems responsible for delivering Cisco's market leading network access control products, including Cisco's Identity Services Engine. He started his career at NASA Ames Research Center after obtaining his MS/PhD in Computer Science from Indiana University.

DB Networks pioneered Artificial Intelligence based database security. Its customers include the world's largest financial institutions, healthcare providers, manufacturers, and governments. Customers gain insights by discovering all active databases, identifying tables being accessed, and the specific applications accessing the databases. In addition, analyzing application database access that deviates from the model of normal application behavior immediately identifies compromised credentials and database attacks. DB Networks is a privately held company headquartered in San Diego, Calif. For more information, call (800) 598-0450 or visit the company's website.

Talking about the relationship between cyber security and machine learning, we need to first identify a concept change. In the past, cyber security focuses on blocking the intruders from outside of our network, but today, we have to believe that intruders are among us. They have invaded our systems and they are doing or going to do damages to us. Whatever the compromised device or machine is doing, it's acting abnormally. So, cyber security means anomaly detection.