Later this week, Carole Boijaud, a cybersecurity engineer with Credit Agricole Group Infrastructure Platform (CA-GIP), “will provide a return on experience on how Credit Agricole’s SOC Team tries to use its own made machine learning, focusing on how we used it to prevent data leakage and detail how we are leveraging our detection process with a live demo.”
Note
- With the rate of data flowing into centralized logging, you need every trick to identify anomalous behavior, while eliminating both false positives and negatives. The point is that thresholds, our old standbys, aren’t sufficient in today’s environment. You need mechanisms that adapt and learn based on events seen. If you already have tools intended to do this, make sure they are enabled and configured; it’s going to take time to get them tuned/trained, but you may find you discover anomalous behavior previously overlooked.
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