Fighting Unwanted Notifications with Machine Learning in Chrome

https://news.ycombinator.com/rss Hits: 5
Summary

Notifications in Chrome are a useful feature to keep up with updates from your favorite sites. However, we know that some notifications may be spammy or even deceptive. We’ve received reports of notifications diverting you to download suspicious software, tricking you into sharing personal information or asking you to make purchases on potentially fraudulent online store fronts. To defend against these threats, Chrome is launching warnings of unwanted notifications on Android. This new feature uses on-device machine learning to detect and warn you about potentially deceptive or spammy notifications, giving you an extra level of control over the information displayed on your device. When a notification is flagged by Chrome, you’ll see the name of the site sending the notification, a message warning that the contents of the notification are potentially deceptive or spammy, and the option to either unsubscribe from the site or see the flagged content. An example of a notification flagged as possibly spam. If you choose to see the notification you will still see the option to unsubscribe or you can choose to always allow notifications from that site and not see warnings in the future. What you see when viewing a flagged notification. How It Works Chrome uses a local, on-device machine learning model to analyze notification content. This model identifies notifications that are likely to be unwanted. The model is trained on the textual contents of the notification, like the title, body, and action button texts. Notifications are end to end encrypted. The analysis of each message is done on-device and notification contents are not sent to Google, to protect user privacy. Due to the sensitive nature of notifications content, the model was trained using synthetic data generated by the Gemini large language model (LLM). The training data was evaluated against real notifications Chrome security team collected by subscribing to a variety of websites that were then classified by...

First seen: 2025-05-10 02:17

Last seen: 2025-05-10 06:17