Cybersecurity is a Big Data Problem
Finding, triaging and investigating cyberthreats has never been more time-consuming, difficult or important for enterprises.
But cybersecurity teams are overwhelmed trying to deal with the massive amount of data generated by the security products they have deployed in their networks, on their endpoints and in their datacenters. With hundreds of new security incidents to deal with every week, and each one often taking days to investigate fully, SOC analysts can quickly fall behind and suffer alert fatigue as they manually try to add context to the data, often missing important signals in all the noise they must deal with.
Adding to this frustration is the huge number of false positives that waste precious time. With more data traffic, an expanding security footprint, the adoption of new technologies like IIOT, analyst turnover, and a huge worldwide shortage of skilled cybersecurity professionals, the problem will only get worse.
In this environment, cybercriminals, cyberterrorists and hacktivists alike seemingly have the clear upper hand. Their attacks have become more sophisticated and difficult to detect and defend, and as a result, it’s become more challenging to protect sensitive customer data and intellectual property, and prevent a breach. Profitability, share price, brand reputation, and even customer and staff safety, are on the line. Which is why cyber risk management, and solving this big data problem, have become an executive- and board-level priority.
This white paper provides a detailed description of Cysiv’s modern, data science-driven approach to more quickly, effectively and efficiently detecting and investigating cyber threats, and the security operations and analytics platform, which many would consider a next-gen security information and event management (SIEM), that enables it.