Technology Other News 31 Jan 2018 Google goes strict o ...

Google goes strict on 7,00,000 apps using AI

DECCAN CHRONICLE.
Published Jan 31, 2018, 5:40 pm IST
Updated Jan 31, 2018, 6:29 pm IST
99 per cent of apps with abusive contents were identified and rejected before anyone could install them,” says the company in its blog post.
Google has targeted Potentially Harmful Apps (PHA), apps which include trojans, malware and SMS fraud.
 Google has targeted Potentially Harmful Apps (PHA), apps which include trojans, malware and SMS fraud.

Google through its Machine Learning techniques has taken down more than 7,00,000 apps which were violating the Google Play policy rules. The company says it is 70 per cent more apps compared to last year.

”Not only did we remove more bad apps, we were able to identify and action against them earlier. In fact, 99 per cent of apps with abusive contents were identified and rejected before anyone could install them,” says the company in its blog post.

 

This major detection and deletion of bad, inappropriate content or malware apps have been possible through Google’s machine learning techniques. Primarily the company has taken down copycat apps, which were impersonating as famous apps and misleading the users. The company has taken down more than a quarter of a million of impersonating apps.

Google PlayStore has undergone some serious allegations last year about inappropriate/pornographic content especially in the kid's applications. Google using its detection method have taken down these apps as well.

 

Further, Google has targeted Potentially Harmful Apps (PHA), apps which include trojans, malware and SMS fraud. These potentially harmful apps are a major threat to the users and Google invests a lot on these to keep them away from the PlayStore. Such investments lead the company to introduce Google Play Protect feature for Android last year, which has taken down the PHA rates by 50 per cent.

This is a major move by Google, as it is focusing on protecting its billion Android app users by using its machine learning algorithms and harmful app detection techniques.

 

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