Building a streaming anomaly detection solution at TELUS using Pub/Sub, Dataflow, and BigQuery ML

Опубликовано 15 сентября 2020, 16:23

Securing its internal networks from malware and security threats is critical at TELUS. With an ever-changing malware landscape and the explosion of activities in IoT and M2M, existing signature-based solutions for malware detection are no longer sufficient. The TELUS cyber security team is pushing the boundaries on state-of-the-art technologies to detect suspicious behavior in its wireless networks.

Learn how Google and the TELUS team have worked together to modernize a security analytics platform from an on-premises Hadoop/Spark-based data lake. This session includes a live demo of a streaming analytics pipeline using Beam/Dataflow which processes thousands of network log events/sec, aggregates, and finds outliers in near real time based on a k-means clustering model using BigQuery ML. See the power of streaming analytics using machine learning.

Speakers: Masud Hasan, Abdul Rahman Sattar

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event: Google Cloud Next 2020; re_ty: Publish; product: Cloud - Data Analytics - PubSub, Cloud - Data Analytics - Dataflow, Cloud - Data Analytics - BigQuery; fullname: Masud Hasan, Abdul Rahman Sattar;