Context Relevant's Cybersecurity Application
Cyber attacks and advanced persistent threats are on the front pages every day. The sophistication of these attacks and the complexity of the modern enterprise present a gargantuan, permeable threat surface that is often too large and weak for humans (and existing tools) to monitor. Without a new approach, we are in trouble.
Context Relevant’s cybersecurity application brings our full Automated Data Science platform to bear on the problem. It adapts in real-time to unique behaviors and characteristics within your enterprise network, surfacing highly-contextualized and automatically-generated Threat Cases to your security operations team.
Context Relevant didn’t start with a cybersecurity thesis, and then bolt on some machine learning. Rather, we built our application on top of our machine learning platform to create a world class product that addresses cybersecurity’s most difficult challenges. This distinction may seem subtle, but the results are significant.
How It Works
Our cybersecurity application combines various network, endpoint, and end-user data signals from across your infrastructure. The underlying machine learning platform models this data, learns expected and normal behaviors, and predicts anomalous behavior in a manner customized to your enterprise and without using any predefined, black-box models.
The Context Relevant machine learning platform enables us to iteratively build and test hundreds of models and then correlate anomalies across time, endpoints, applications, and users, automatically discovering how various anomalies are related to a single attack, while at the same time disregarding false-positives.
The resulting Threat Cases are contextualized and coherent summaries of a chain of well-founded anomalous events, giving analysts everything they need to investigate.
Our cybersecurity application does not need to wait for Exfiltration (stage 5) for confirmation of breach; instead, it makes highly accurate predictions of breach even at the Recon (3), and Staging (4) stages of an attack:
Our cybersecurity application delivers:
- Higher value results to your security team: By automatically selecting and correlating the highest impact events into an intuitive narrative.
- Highly contextualized Threat Cases: Where it correlates across potentially thousands of anomalies to deliver a single amalgamated view of a breach.
- Earlier detection of breach: Threat Cases allow your Security team to find breaches far sooner than the industry average of >200 days by identifying breach markers and differentiating them from random behavioral noise at stages (3) and (4) of the kill chain, and alerting you before that data has been exfiltrated from your network (5).
Lower business risks
About Context Relevant
Context Relevant delivers predictive analytics software that can anticipate changes in operations, customer behavior, product pricing, and even what attackers may do next. This allows you to find answers from your data faster, more easily, and more cost effectively than ever before.