Advanced AI solution for enterprise malware detection
Cybersecurity, anti-malware solutions
- Detect and prevent ransomware attacks
- Monitor the storage usage
- IT Services
- Data centers
- Custom software development
- Product development
Project type ＿
- Distributed backend
- NetApp Clustered Data ONTAP
- REST endpoints
- AWS virtualisation
- Machine learning
An application that runs on an enterprise’s datacentre storage systems (SAN) and does real time monitoring of the SAN I/O activity. It employs an advanced AI solution for anomaly detection that allows blocking malware from corrupting enterprise data.
Since malware can hit in many different forms and have a heavy impact on the final user, we have to:
- Provide a powerful solution that protects against all threats (both known and new / unknown).
- Ensure the best malware detection accuracy, while keeping false positives at minimum (or zero).
- Deliver real-time detection and protection that spans across the whole SAN network.
- Keep SAN performance unaffected.
We met client’s high expectations with a series of cross-technology solutions:
- AI anomaly detection techniques that determine what is “normal” traffic and allow it to pass while “suspicious” traffic is blocked.
- Model training and evaluation with extensive real data, collected from production SAN logs.
- Processing and enhancement of collected data set, to obtain an even greater synthetic “real-like” dataset.
- Setting up of simulated SAN environments; and release of malware to collect footprints.
- Model parameters tweaking, to ensure highest precision and recall scores.
- Implementation of distributed architecture, with sensors on each SAN node and dedicated processing nodes to run the detection model.
- Development of a home-grown decision tree variant that is both accurate and lightweight enough for the use case.
- Hyperparameter tuning to minimize the model while maintaining the accuracy.