San Francisco -- While "Big Data Security" is now the industry buzzword and defines a way to get enterprise customers into a new method of threat detection based on mining massive amounts of security-event and business data to pinpoint threats, the response from a few IT shops seems to be"thanks, but no thanks."
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"I don't call it Big Data," I call it garbage data," said Jerry Sto. Tomas, director of global information security at healthcare company Allergan, who with other panelists at the RSA Conference this week discussed the challenges that security managers face today in getting solid threat intelligence for network defense out of what already feels like too much security-event data. Adoption of cloud services is only adding another wrinkle on centralizing that plan.
His colleagues on the panel, Stephen Moloney, manager enterprise information security at insurance firm Humana and David Hannigan, information security officer at e-commerce retailer Zappos.com, were also uninspired by the industry's call for Big Data Security.
The Big Data Security idea so far appears to amount to investing in a massive centralized repository, likely based on Hadoop, to use the latest security analytics engines to discern attacks by sorting through information provided by a vendor's security information and event-management (SIEM). It's an idea put forward most prominently by IBM, HP (which just this week put forward its strategy) and RSA, the security division of EMC, as where the most cutting-edge security is headed. But are chief information security officers ready to head in that direction?
It's not that they don't use SIEM to collect security-event information and log data today. But that in itself is problematic.
"With SIEM, we underestimated how much data there was," said Hannigan about what happens daily at Zappos. As it gets refined, the amount of data "explodes" and "people keep sending you more," he pointed out. Zappos uses Splunk to correlate data. Because Zappos suffered a data breach last year, the company has pushed hard to boost security, particularly by intensively monitoring the safety of customer accounts.
Sto. Tomas of Allergan expressed similar sentiments. "The data is too much. With SIEM, once you've got one log correlated to another, it's very addicting. You want more." But it also brings "too much garbage." Allergan uses tools that include RSA enVision, Nitro Security and Splunk. But Allergan is also adopting cloud services such as Salesforce and Box for business purposes, as well as Zscaler for cloud-based security. The challenge is obtaining needed logs from cloud providers and integrating it. His job as security manager requires interaction with business units on security matters not sitting in front of a dashboard, he said. The business value from tools such as SIEM is in explaining security risk and impact to business units and you can't overwhelm them with data, he noted.
Sometimes SIEM needs to be changed. Moloney, for example, said Humana's operations team is in the process of migrating from the RSA enVision SIEM to the Sensage SIEM that is going to be used to collect and correlate data associated with intrusion-detection systems, firewalls and other corporate infrastructure. With enVision, the problem was that it wasn't scaling to do the analysis that Humana needed as the population at Humana grew from 5,000 to 55,000, said Moloney.
However, the IT security managers aren't giving up hope that security vendors, who acknowledge Big Data Security represents a cutting-edge approach, will eventually have something they will be taking a look at.
"Big Data will be our future, at least to address APTs (advanced persistent threats)" said Sto. Tomas, who added he'll be watching what happens with the technology over the next few years. But for now, "Big Data is a big challenge when it comes to security," he concluded.
Ellen Messmer is senior editor at Network World, an IDG publication and website, where she covers news and technology trends related to information security. Twitter: MessmerE. E-mail: email@example.com.