Logs are the cornerstone in today’s cybersecurity monitoring, investigation, and forensics. According to a Fortune 500 report, an organization’s IT infrastructure can generate up to 10 Terabytes of log data per month. In this post, we will learn about log aggregation and monitoring; then analyze how they can help businesses to strength their cybersecurity posture.
Use Case 6: SIEM Security with Artificial Intelligence
SIEM security that is equipped with Artificial Intelligence (AI) and user behavior analytics can deal with internal threats. AI capabilities in SIEM help security professionals to automate tasks that are otherwise manual and repetitive. Doing so can also help to swiftly detect threats and suspicious activities in network traffic and event logs.
Data is a raw material, which is often unstructured, extracted in massive quantity, and requires processing before calling it an information and actionable intelligence. A good example is the Indicators of Compromise (IoCs). A big list of domain names or IP addresses can be ingested into the SIEM system to identify whether this list contains any malicious IP or not. If any suspicious IP is detected, then we can term this data as an actionable intelligence which has been evaluated from reliable sources, processed and enriched. Now, it can be used to identify trends, attack profile, and possible threats. In this article, we will see how data is gathered, processed, and act as an actionable delivery.