Come join our upcoming webinar “Real-Time AI Threat Detection Using Kafka” explore how Kafka, combined with cutting-edge AI technologies, can be wielded to detect and counter cybersecurity threats as they occur.
Our session will include a hands-on demo and code-share where we'll utilize a deep learning model and similarity search to identify and classify network intrusion traffic. The demonstration will be grounded on a dataset of labeled traffic events which are then transformed into vector embeddings to represent network traffic events comprehensively. These embeddings will serve as a linchpin for measuring similarity between different network events, aiding in the identification and classification of benign and malicious events.
What You’ll Learn:
How to set up Kafka for real-time data processing and threat detection.
Applying SingleStoreDB's similarity search for identifying infrequent occurrences in network traffic.
Utilizing a deep learning model to transform network traffic data into vector embeddings for effective similarity measurement.
Hands-on approach to constructing a network intrusion detection system that can classify events as benign or malicious.
Speakers:
Akmal Chaudhri, Senior Technical Evangelist at SingleStore
Arnaud Comet, Director of Product Management at SingleStore
Senior Technical Evangelist at SingleStore
Director of Product Management at SingleStore
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