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Brivo adds Anomaly Detection to access control service

Brivo—a cloud-based access control and smart building technologies enterprise—announced the release of Anomaly Detection in its flagship access control solution, Brivo Access. Anomaly Detection is a patent-pending technology that uses analytics with machine learning algorithms to compare massive amounts of user and event data to identify events that are out of the ordinary or look suspicious, and issues priority alerts for immediate follow up.

The company has stated that with Anomaly Detection, businesses can get a nuanced understanding of security vulnerabilities across their facility portfolio and take action on early indicators of suspicious user behaviours that may otherwise go unnoticed.

“With Anomaly Detection, Brivo is incorporating the latest data and machine learning technology in ways never before seen in physical security,” said Steve Van Till, Founder and CEO of Brivo, in a statement.

“Along with our recently released Brivo Snapshot capability, Anomaly Detection uses AI to simplify access management by notifying customers about abnormal situations and prioritizing them for further investigation. After training, each customer’s neural network will know more about traffic patterns in their space than the property managers themselves. This means that property managers can stop searching for the needle in the haystack. We identify it and flag it for them automatically.”

Anomaly Detection’s AI engine learns the unique behavioural patterns of each person in each property they use to develop a signature user and spatial profile, which is continuously refined as behaviours evolve. This dynamic real-time picture of normal activity complements static security protocols, permissions, and schedules. In practice, when someone engages in activity that is a departure from their past behaviour, Anomaly Detection creates a priority alert in Brivo Access Event Tracker indicating the severity of the aberration. This programmed protocol helps organizations prioritize what to investigate.

As more companies roll out hybrid work policies for employees, most businesses are poised to see a lot of variation in office schedules and movement, according to Brivo. For human operators, learning these new patterns could be time-consuming, particularly analyzing out-of-the-ordinary behaviours that are technically still within the formal bounds of acceptable use. With Anomaly Detection in Brivo Access, security teams can gain better visibility and understanding as the underlying technology continuously learns users’ behaviours and patterns as they transition over time.