The New AI system thatDot Novelty Detector Speeds Up Detecting of Malicious Activity
The new patented technology thatDot Novelty Detector uses categorical variables to speed up real-time detection of malicious activity with fewer false positives and less operator involvement.
Traditional detection of abnormal network activity does not use categorical data, but numerical data and statistical analysis, which do not work due to the high dimensionality of the data and create a huge number of false positives. Malicious activity goes undetected or its detected occurs too late.
Let me remind you that the following messages from the news on the threat detection front may be interesting to you: Microsoft Defender Is Now Available with Built-In Troubleshooting Mode, as well as Google Cloud Got a Tool for Detecting Cryptocurrency Miners.
Novelty Detector evaluates the novelty level of streaming data in real time as soon as it arrives. Using previous data and the power of charting models, Novelty Detector significantly reduces false positives, scaling to millions of events per second.
The public version of Novelty Detector also includes a new self-learning feature. The system receives data, calibrates and trains itself, and then evaluates each piece of data in real time for anomalies. With the new capability, malware and credential theft threats are detected automatically.