In our previous blog, Identifying stolen credential use in AWS CloudTrail logs with high confidence using categorical anomaly detection, we discussed the “False-positive reducing” power of analyzing the categorical data in AWS CloudTrail logs to identify novel behaviors. We...
The move to the cloud represents new challenges for enterprise security teams. Systems are more distributed and the impact of credential theft is greater than ever. Running your services in a public cloud vendor like AWS requires you to...
Since the launch of thatDot’s Real-time Anomaly Detector for Categorical data in November, we have received numerous feature requests for additional data exploration and data transformation capabilities. We are excited to announce the addition of these key functions in...
Too many false positives! Traditionally, monitoring alerts are produced comparing metrics against thresholds to identify behavior outside the norm. This approach of metrics-based alert definitions often generates too many false positives that lead to wasted human time and effort or...
An Industry First: Anomaly Detection for Categorical Data in Real-Time thatDot is excited to share the general availability of the world’s first real-time categorical anomaly detector. Data Engineers, Developers, and Data Scientists can now generate a real-time score showing the...
Cloud architectures enable and encourage a new level of integration with 3rd party systems and data sources to deliver the enriched and personalized services our users and customers are looking for. Today’s data-driven services place significant new demands on...
7 Minutes Read Imagine if the next time your video streaming operations dashboard-of-choice warns you that 100 users experienced video start failures in the last minute, it was only one click to see each of those sessions and that they...
