Seculert’s attack detection and analytics platform combines machine learning-based analytics and threat intelligence to automatically detect cyber attacks inside the network, revealing exactly which devices and users are compromised.CISOs can measure and prove the effectiveness of their existing threat prevention systems, without deploying additional staff, hardware, or software.
|2013||Jun 2013 09:00 PM||10.0||4316|
|2012||Jun 2012 09:00 PM||5.4||4316|
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Exit Events and Acquisitions
AI Technology Stack
Multidisciplinary research with a proven ability to develop fast prototyping and implement them in production from end to end. Hands on experience in developing multiple big-data (based on spark) cyber malware defense classification algorithms based on data intelligence and crowdsourcing. Develop novel command and control malware classifiers. Malware similarity engines based on graph algorithms, distance metrics and natural language processing (NLP). Research various data sources for User Behavior Analytics (UBA) protection solution that is designed to detect insider threats, external attacks and lateral movements inside the organization using unsupervised and supervised machine learning. Transfer raw unstructured log information to accurate and enriched information. Develop novel deep learning algorithms which transfer knowledge from threat intelligence to UBA attack detection.