Distinguished Speakers Series #2
Splunk’s Sriharsha visits Uncountable
The security expert shares the latest threat detection methods
In the second session of Uncountable’s Distinguished Speaker Series, the engineering team invited Splunk’s Vice President of Engineering Ram Sriharsha to talk about the state of data security today. He offered his insights on how best to protect client’s data against external threats and the latest technological advances in proactive data security.
Customer privacy and data security have always been central considerations when constructing the Uncountable platform. While we are a data-driven company — streamlining, modeling, and predicting experimental results — none of that would be possible without effective data security systems. Our goal, like Splunk’s, is not only to protect our platform and our customers against existing threats, but also to identify future attacks and points of potential vulnerability.
Because we are proactive about security, Uncountable’s platform is always evolving to meet the growing capabilities of malware and other such threats. We are perpetually updating our security systems, trying to identify and respond to future threats.
Sriharsha’s presentation provided an insightful glimpse into the kind of work that Splunk does to ensure its customer’s data security against these ever-morphing threats. As he explained, traditional attacks generally attempt to gain access to a system so that an external actor will have remote control and can execute malicious commands.
While many attacks do follow this playbook, it is equally important to be on the lookout for new pathways of potential attacks. Uncountable and Splunk need to ensure that their customers feel safe entering their private data into their systems — safe against both infiltration and exfiltration threats. To this end, Splunk combines historical use cases with data and analytics in an User Entity Behavioral Analysis (UEBA) which can detect known threats like malicious insiders and compromised user accounts. At the core of the UEBA is the belief that modelling normal employee behavior can provide crucial insights into detecting abnormal behavior and protecting sensitive data.
When Uncountable’s customers input their proprietary data into our system, they need to be confident that their data is secure and protected. However, as Sriharsha would be the first to tell you: data security is difficult, and developing detection software is doubly challenging, given the sheer amount of available data. Even more shocking is the fact that without the proper detection techniques, you wouldn’t know that you missed an attack. Internally, Uncountable’s team is always asking itself: what do we need to enable in our system to protect against potential threats?
Sriharsha’s years of experience in the field have taught him the importance of relying on a series of interlocking protection techniques to track a wide range of threats. Traditional security software often relies on matching malware to known signatures, but the security industry as a whole is moving rapidly towards more flexible and dynamic detection methods. With the popularization of machine learning, paradigms like UEBA are now possible at scale.
Sriharsha also discussed how his research team has been pushing forward with new ways of leveraging large amounts of data. In particular, he spoke about how instead of learning what normal behavior looks like and flagging deviant observations, detection systems can learn to characterize malicious behavior directly. Moreover, this malicious behavior can be learned from publicly-available data sources without always needing to access customers’ data.
In the end, there is not one security metric or tool that will be able to identify and protect a product or brand against every conceivable intrusion. As Sriharsha attests, no single detection method is perfect, nor will ever be perfect forever. To meet this flexible threat, Uncountable is perpetually pushing the bounds of the thinkable, trying to protect our customers against the attacks of tomorrow.
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