Mahadev Satyanarayanan, Carnegie Mellon University: "Using Edge Computing for Privacy in Real-Time Video Analytics"

2018-09-24 15:00:00 2018-09-24 16:00:00 Europe/Helsinki Mahadev Satyanarayanan, Carnegie Mellon University: "Using Edge Computing for Privacy in Real-Time Video Analytics" This lecture is part of the Helsinki Distinguished Lecture Series on Future Information Technology http://cs.aalto.fi/en/midcom-permalink-1e8b0ea9aad754eb0ea11e8a935abc20583420c420c Otakaari 2, 02150, Espoo

This lecture is part of the Helsinki Distinguished Lecture Series on Future Information Technology

24.09.2018 / 15:00 - 16:00

The Helsinki Distinguished Lecture Series on Future Information Technology is organized by HIIT, a joint research institute between University of Helsinki and Aalto University. The series was launched in 2012.

The focus of the seminar series is to highlight the research challenges and solutions faced by current and future information technology, as seen by the internationally leading experts in the field.

Venues alternate between University of Helsinki and Aalto University, the two host universities of HIIT.

The next lecture in the Helsinki Distinguished Lecture Series on Future Information Technology will be given by Professor Mahadev Satyanarayanan from Carnegie Mellon University.

The lecture is free of charge and open to everyone interested in the latest research in information technology. The lecture will be followed by an informal cocktail event.

Please register here.

Using Edge Computing for Privacy in Real-Time Video Analytics

Place: Small Hall, Main Building, University of Helsinki, Fabianinkatu 33, Helsinki

Web page: Helsinki Distinguished Lecture Series on Future IT

Abstract:

Live video offers several advantages relative to other sensing modalities. It is flexible and open-ended: new image and video processing algorithms can extract new information from existing video streams. It offers high resolution, wide coverage, and low cost relative to other sensing modalities. Its passive nature means that a participant does not have to wear a special device, install an app, or do anything special. He or she merely has to be visible to a camera. Privacy is clearly a major concern with video in public spaces. In this talk, I will describe how Edge Computing can be used to denature live video thereby making it “safe” from a privacy point of view. Using OpenFace, our new open-source face recognition system that approaches state-of-the-art accuracy, we are able to selectively obscure faces according to user-specified policies at full frame rate. This enables privacy management for live video analytics while providing a secure approach for handling retrospective policy exceptions.

Bio:

Satya’s multi-decade research career has focused on the challenges of performance, scalability, availability and trust in information systems that reach from the cloud to the mobile edge of the Internet. In the course of this work, he has pioneered many advances in distributed systems, mobile computing, pervasive computing, and the Internet of Things (IoT). Most recently, his seminal 2009 publication “The Case for VM-based Cloudlets in Mobile Computing” and the ensuring research has led to the emergence of Edge Computing (also known as “Fog Computing”). Satya is the Carnegie Group Professor of Computer Science at Carnegie Mellon University. He received the PhD in Computer Science from Carnegie Mellon, after Bachelor’s and Master’s degrees from the Indian Institute of Technology, Madras. He is a Fellow of the ACM and the IEEE. “For a more detailed bio, see Satya’s Wikipedia entry.