DLP leans on Google’s extensive machine learning capabilities—image recognition and machine vision, natural language processing, and context analysis all come into play—to seek out overlooked or unexpected sensitive data and automatically redact it. And while the Data Loss Prevention API can be customized based on specific types of data an administrator wants to catch—like patient information in a medical setting, or credit card numbers in a business—DLP also needs to be comprehensive enough to catch things organizations don’t know they’re looking for.

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Android security team was feeling pleased with itself. The group had detected, analyzed, and neutralized a sophisticated botnet built on tainted apps that all worked together to power ad and SMS fraud. Dubbed Chamois, the malware family had already cropped up in 2016 and was being distributed both through Google Play and third-party app stores. So the Android team started aggressively flagging and helping to uninstall Chamois until they were sure it was dead.

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IF YOU USE a smart speaker, you know all of the convencies and delights that make it more than just a glorified paper weight. But, admit it, you’ve probably given it some privacy side-eye from time to time. After all, it is a microphone that just sits in your house waiting for a wake word to start recording what you say. Here’s how to tighten the reins on what Alexa, Google Assistant, and Siri can hear, when, and how it gets used.

 

That practice makes sense if you know that algorithms need to train on human-vetted examples to refine and improve their accuracy. But there’s no reason that Alexa users wouldknow that! And Amazon had not been forthcoming about its Alexa auditors. Apple and Google, who make popular smart speakers as well, aren’t shouting it from the rooftops either, but both companies had mentioned previously that they use human reviewers as well.

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