Adobe: Thinks It Has Solved Netflix's Password Sharing Problem

Η Adobe πιστεύει ότι έχει την απάντηση στο πρόβλημα της “κοινής χρήσης κωδικού πρόσβασης” (password sharing) του Netflix που αφορά έως και 46 εκατομμύρια ανθρώπους, σύμφωνα με μια μελέτη του 2020.

TorrentFreak he says:

Adobe believes that since every user is different, any actions taken from an account should be part of a data-driven strategy designed to “measure, manage and monetize” password sharing.

The company's vision is for platforms like Netflix to deploy machine learning models to extract patterns of behavior associated with an account. They will then be able to determine how the account is used.

This information will be able to determine what action should be taken against an account and how success or failure can be determined by monitoring an account over the coming weeks or months.

adobe netflix

Ignoring the obviously creepy factors for a moment, Adobe's approach is much more complex, even if the accompanying transparency gives a sense of "graded response" to file sharing. The question is how much customer information Adobe would need to ensure that Netflix is ​​targeting the right accounts, with the right actions, at the right time.

Το Adobe’s Account IQ τροφοδοτείται από το Adobe Sensei, το οποίο με τη σειρά του λειτουργεί σαν ένα επίπεδο νοημοσύνης για την πλατφόρμα του Adobe Experience. Θεωρητικά, η Adobe θα γνωρίζει περισσότερα για έναν streaming λογαριασμό από αυτούς που τον χρησιμοποιούν, επομένως η εταιρεία θα πρέπει να μπορεί να προβλέψει την πιο αποτελεσματική πορεία για τη μείωση της κοινής χρήσης του κωδικού πρόσβασης ή/και τη δημιουργία εσόδων από αυτόν, χωρίς να ενοχλεί τον κάτοχο του λογαριασμού.

But if it monitors customer accounts in such great detail, gathering all available information is the obvious next step.

Adobe envisions collecting all the data, such as how many devices are being used, how many people are active, in which geographic locations, device IDs, and much more.

This will then lead to a “likelihood of sharing” conclusion, along with a classification of usage patterns that should identify travelers, commuters, close family and friends, or even a second home.

After collecting all the necessary data, legal services will be able to identify the offending accounts and start preparing their "tiered response" to change behavior. After monetizing those who want to pay, those who refuse to pay can be identified and rejected. Or as Adobe puts it:

“Bring free-loaders back to the available market.”

Finally, Adobe also suggests that its system can be used to identify customers who demonstrate good behavior. These users will be able to be rewarded by eliminating authentication requirements, simultaneous streaming limits and device registrations. The Best Technology Site in Greece
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Written by giorgos

George still wonders what he's doing here ...

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