Machine learning models, which use data to help computers learn for themselves, are vulnerable to privacy leaks and malicious attacks, Cornell Tech researchers have found.
Source: Artificial intelligence may put private data at risk | Cornell Chronicle
Some of the apps in question included Disney’s “Where’s My Water?” Gameloft’s “Minion Rush” and Duolingo, the language learning app.
Βαριά πρόστιμα, σχεδόν εξοντωτικά, ειδικά για τις μεγάλες επιχειρήσεις, φέρνει ο νέος ευρωπαϊκός κανονισμός, που θα ισχύσει αυτόματα και στη χώρα μας από τον προσεχή Μάιο και αφορά το νέο θεσμικό πλαίσιο για την προστασία των προσωπικών δεδομένων.
Source: Βαριά πρόστιμα για τα προσωπικά δεδομένα | Επιχειρήσεις | Η ΚΑΘΗΜΕΡΙΝΗ
Demonstrating a potential privacy breach, a team of Princeton University engineers has developed an app that can locate and track people through their smartphones even when access to the Global Positioning System, or GPS, data on their devices is turned off.
Source: Phones vulnerable to location tracking even when GPS services off
Privacy concerns have long swirled around how much information online advertising networks collect about people’s browsing, buying and social media habits — typically to sell you something.
But could someone use mobile advertising to learn where you go for coffee? Could a burglar establish a sham company and send ads to your phone to learn when you leave the house? Could a suspicious employer see if you’re using shopping apps on work time?
The answer is yes, at least in theory. New University of Washington research, to be presented in a paper Oct. 30 at the Association for Computing Machinery’s Workshop on Privacy in the Electronic Society, suggests that for roughly $1,000, someone with devious intent can purchase and target online advertising in ways that allow them to track the location of other individuals and learn what apps they are using.
Source: For $1000, anyone can purchase online ads to track your location and app use | UW News
When one creates an account to get access to an online service, the service provider requires certain details to identify users who want to access their accounts. There are existing methods that can be built into such services to protect users and their privacy under certain circumstances. However, many service providers choose to use other methods to collect as much information about us as possible, and so frequently threaten online user privacy.
Source: Digital services collect unnecessary personal information | Karlstad University
PrivacyStreams Helps Developers Create Privacy Friendly Apps
Decision To Share Personal Data Need Not Be All or Nothing
A smartphone app that uses the raw feed from a device’s microphone or accesses its contact list can raise red flags for a user concerned about privacy. In many cases, however, the app doesn’t need all the details that users find most sensitive.
Researchers at Carnegie Mellon and Peking universities have addressed this dilemma by creating a service, PrivacyStreams, that enables app developers to access the smartphone data they need for app functionality while assuring users that their private information isn’t being sold to an online marketer or otherwise revealed.
A sleep-monitoring app, for instance, might need to access the smartphone’s microphone, but only to register loudness, not to monitor conversations. An app developer could simply sample the microphone feed every minute or so, use software in the PrivacyStreams library to transform the raw data to loudness and then send just the loudness data back to the smartphone for use by the app.
