The business case to unify network, endpoint, and cloud data
April 5, 2019
Security teams often lack the visibility and automation required to stop attacks. Siloed tools like endpoint detection and response (EDR) and network traffic analysis (NTA) collect large amounts of data, but they also force analysts to pivot from console to console to verify threats, increasing complexity and slowing down investigations.
Faced with a shortage of cybersecurity professionals, teams must simplify their operations, or they will struggle to investigate and stop attacks.
A system needs to be put in place detection and response natively integrates network, endpoint, and cloud data to stop sophisticated attacks. Leveraging behavioral analytics, it should identify unknown and highly evasive threats targeting your network with behavioral analytics. Machine learning and AI models should be leveraged to uncover threats from any source, including managed and unmanaged devices.
A tool that could integrate all three would speed alert triage and incident response by providing a complete picture of each threat and revealing the root cause automatically. By stitching different types of data together and simplifying investigations, such a system would reduce the time and experience required at every stage of security operations, from triage to threat hunting. Tight integration with enforcement points would let the Security Operations Center (SOC) respond to threats quickly as well as apply the knowledge gained from investigations to detect similar attacks in the future. Native integration with cloud-based threat intelligence would ensure prevention is coordinated across your network, endpoint, and cloud security products.