Service overview

DataSense delivers data streaming services for data driven organisations needing to harvest critical data from a vast array of systems and devices, from almost any location, and to transform, enrich, filter and stream these data to specific processing service services. This transfer of data is undertaken at scale, in a secure, forensically sound and automated manner.

Data Harvesting

DataSense can be configured to harvest data from a vast array of IT systems, devices and applications (log sources) out of the box. The service is easily extensible to include additional log sources from a diverse range of environments, including IoT, OT, smart buildings and autonomous vehicles. Even one-off unique systems can quite easily be harvested for log and machine data.

Security and Integrity

DataSense utilises the renowned data integrity features of ALM-SIEM, ensuring that harvested data are securely transferred into the SOC infrastructure and strong data integrity is assured. The original and complete data can be stored in the ALM-SIEM secure store, can be re-processed any number of times and can be archived to very low cost offline store, using the built-in archiving features.

Data Enrichment

Automated data enrichment options include watchlist lookups and matches from a wide range of external threat intelligence feeds, both commercial and open source. In addition, DataSense can be configured to apply selected filtering processes in order to reduce noise, reduce data volumes generally and to increase analyst focus on critical events.

Custom Lookups

Harvested data can also be enriched using specific user defined enrichment data, such as threat intelligence feeds. This includes user defined threat data, such as context, location, asset value, risk value, white lists etc., so the data streaming service can be customised to reflect specific client requirements and risks, in addition to the out of the box threat intelligence data.

Assuria DataSense: Secure Movement of Enriched, Filtered and Normalised Critical Data