Anticipate
Anticipate the latest cyber threats and prevent digital risk.
DetailMany customers base their threat detection only on logs or on endpoint data. The challenge with this approach is that not everything is logged, and not all endpoints can run detection agents. Or indeed, there may be third party endpoints not owned by your organization. Network-based threat detection provides an optimal way to get the full view of threats traversing the network without blind spots caused by machines without endpoint sensors or missing log data.
To address these challenges, Orange Cyberdefense offers a managed service that leverages machine learning (ML) for detecting threats based on network traffic. And, by applying supervised ML techniques, the service can detect threats that have never been seen before based on their behavior. Alongside this, unsupervised machine learning maps and adapts to your unique network profile continuously over time, meaning that the service has greater context around activities that are unique to your environment and therefore, reliably detects what is anomalous.
The service maps to the MITRE ATT&CK framework and allows you to measure progress and model improvements.
Our risk-based detection methods allow us to include more data for our analysts while reducing the number of incidents, in turn alleviating the reliance on your team for extra context.
Our proprietary asset database helps you measure your risk and attack trends over time, including high risk machines or users, as well as kill chain activity across the business.
Attackers are not static. They often have to enhance their position. And when they do, we must catch them in the act.
Discover our approach in the datasheet
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