City
Epaper

Indian-origin scientists develop AI system to curb 'deepfake' videos

By IANS | Updated: July 20, 2019 15:00 IST

At a time when "deepfake" videos become a new threat to users' privacy, a team of Indian-origin researchers has developed Artificial Intelligence (AI)-driven deep neural network that can identify manipulated images at the pixel level with high precision.

Open in App

Realistic videos that map the facial expressions of one person onto those of another known as "deepfakes", present a formidable political weapon in the hands of nation-state bad actors.

Led by Amit Roy-Chowdhury, professor of electrical and computer engineering at the University of California, Riverside, the team is currently working on still images but this can help them detect "deepfake" videos.

"We trained the system to distinguish between manipulated and nonmanipulated images and now if you give it a new image, it is able to provide a probability that that image is manipulated or not, and to localize the region of the image where the manipulation occurred," said Roy-Chowdhury.

A deep neural network is what AI researchers call computer systems that have been trained to do specific tasks, in this case, recognize altered images.

These networks are organized in connected layers; "architecture" refers to the number of layers and structure of the connections between them.

While this might fool the naked eye, when examined pixel by pixel, the boundaries of the inserted object are different.

For example, they are often smoother than the natural objects.

By detecting boundaries of inserted and removed objects, a computer should be able to identify altered images.

The researchers tested the neural network with a set of images it had never seen before, and it detected the altered ones most of the time. It even spotted the manipulated region.

"If you can understand the characteristics in a still image, in a video it's basically just putting still images together one after another," explained Roy-Chowdhury in a paper published in the journal IEEE Transactions on Image Processing.

"The more fundamental challenge is probably figuring out whether a frame in a video is manipulated or not".

Even a single manipulated frame would raise a red flag.

Roy-Chowdhury, however, thinks we still have a long way to go before automated tools can detect "deepfake" videos in the wild.

"This is kind of a cat and mouse game. This whole area of cybersecurity is in some ways trying to find better defense mechanisms, but then the attacker also finds better mechanisms."

( With inputs from IANS )

Open in App

Related Stories

TechnologyS. Korea aims to generate 20 pc of power through renewable energy by 2030

BusinessS. Korea aims to generate 20 pc of power through renewable energy by 2030

NationalTamil Nadu polls: TVK chief Vijay cancels election campaign in Chennai, citing time constraints

PuneBaramati By-Election 2026: Maharashtra DCM Sunetra Pawar To File Nomination Papers Today

MumbaiDelhi–Maharashtra ATS Joint Operation: Two Suspects with Terror Links Detained

टेकमेनिया Realted Stories

TechnologySeoul shares up ahead of Samsung's Q1 guidance, currency slides

TechnologyScientists trap light in layer 1,000x thinner than hair: Study

TechnologyOPEC+ nations to ramp up oil output in May amid global energy crisis

TechnologyPakistan brazenly violating EU terms for tariff-free garment exports

TechnologyGovt launches programme to train scientists in Governance under Mission Karmayogi