Data Science and Automation

Threat detection and hunting are “big data” problems

Cybersecurity teams are often overwhelmed by the massive amount of data generated by the security products deployed in their networks, endpoints, data centers, and cloud workloads.

With hundreds of new security incidents to deal with every week—each often taking days to investigate fully—SOC analysts can quickly fall behind. They often miss important signals within all the “noise” as they manually try to add context to the data by gathering information from multiple sources and tools.

The huge number of false positives adds to this frustration and wastes precious time. False negatives can be even more worrisome. With more data traffic, an expanding security footprint, the adoption of new technologies like IIOT, analyst turnover, and a worldwide shortage of skilled cybersecurity professionals, the problem will only get worse.

The data science solution

Cysiv rigorously applies data science techniques and technologies, developed to automate, accelerate, and improve the process of finding and prioritizing threats, including:

  • Exploratory data analysis
  • Auto-enrichment
  • Cyber intel integration
  • An indicator-detection engine
  • Entity attribution
  • A range of detection techniques (signature-, behavior-, statistics- and algorithm/ML-based).

Cysiv uses data science to more efficiently and effectively convert raw logs and data from other relevant sources into actionable, high-quality, high-confidence detections and security incidents that warrant deeper human investigation.

Let’s discuss how Cysiv data science can improve the effectiveness of your security.