A computer vision system using low-resolution image sensors can provide intelligent services (e.g., activity recognition) but preserve unnecessary visual privacy information from the hardware level. However, preserving visual privacy and enabling accurate machine recognition have adversarial needs on image resolution. Modeling the trade-off of privacy preservation and machine recognition performance can guide future privacy-preserving computer vision systems using low-resolution image sensors. In this paper, using the at-home activity of daily livings (ADLs) as the scenario, we first obtained the most important visual privacy features through a user survey. Then we quantified and analyzed the effects of image resolution on human and machine recognition performance in activity recognition and privacy awareness tasks. We also investigated how modern image super-resolution techniques influence these effects. Based on the results, we proposed a method for modeling the trade-off of privacy preservation and activity recognition on low-resolution images.

The white papers are similar to a security guide that Apple publishes for the iOS operating system that powers iPhones. They cover Apple's photo app, its Safari web browser, the location-based services on its mobile devices and a new service for signing into third-party apps introduced this year that competes with similar services from Facebook Inc (FB.O) and Alphabet Inc's (GOOGL.O) Google. Apple does not make public the code for its operating systems or software, so privacy and security researchers use the descriptions it publishes to understand how those systems work. In the papers, Apple outlines how its new sign-in system tries to prevent the creation of fake accounts in apps, a problem for nearly all app developers that has taken on new importance with the advent of bots on social networks. The company uses machine-learning technology that analyzes whether the device user engages in "ordinary, everyday behavior such as moving from place to place, sending messages, receiving emails, or taking photos," Apple said.

Inc. defended the privacy features of its Alexa digital assistant -- and introduced some new tools to reassure users – following months of debate about the practices of the technology giant and its largest competitors. The company plans to roll out a feature that lets users of the Alexa voice-based assistant automatically delete their verbal recordings regularly, on a rolling three-month and 18-month basis. Previously, Alexa users had to manually delete their stored voice recordings on a companion website. "We care about this," Dave Limp, the leader of Amazon's devices and services business, said of privacy during a press event at the company's headquarters in Seattle. "Privacy is absolutely foundational to everything that we do in and around Alexa."

Apple says its Safari browser will try to guard your privacy by identifying and blocking data files that track you as you move from website to website. It's turning to machine learning, a form of artificial intelligence, to make that happen. That's a new focus for Apple as it competes with Google and Amazon. Later Monday, it's expected to announce an internet-connected smart speaker to compete with Amazon's Echo and Google's Home. Other features coming to the Mac include the ability to stop video from automatically playing on websites when using Safari.