Ever since the lockdown had started last year and meetings and classes shifted to video calls, there have been innumerable complaints of imposters entering the meeting room and causing disruptions. Not any more. Researchers at the Indian Institute of Technology (IIT), Ropar and Monash University, Australia have developed a unique detector to identify imposters attending a virtual conference without anybody's knowledge.
According to the team, the detector named "FakeBuster" can also find out faces manipulated on social media to defame or make a joke of someone. "In the present pandemic scenario when most of the official meetings and work is being done online, this standalone solution enables a user (organiser) to detect if another person's video is manipulated or spoofed during a video conferencing. That means the technique will find out if some imposter is attending a webinar or virtual meeting on behalf of one of your colleagues by morphing his image with his own, said Ramanathan Subramanian, Associate Professor, IIT Ropar.
This software platform is independent of video conferencing solutions and has been tested with Zoom and Skype applications. It works in both online and offline modes. Since the device can presently be attached with laptops and desktops only, we are aiming to make the network smaller and lighter to enable it to run on mobile phones or devices as well, he said The team is now working on using the device to detect fake audios also.
Usage of manipulated media content in spreading fake news, pornography and other such online content has been widely observed with major repercussions. He said such manipulations have recently found their way into video-calling platforms through spoofing tools based on transfer of facial expressions. These fake facial expressions are often convincing to human eye and can have serious implications, said Abhinav Dhall, part of the four-member team that developed the detector.
These real-time mimicked visuals (videos) known as Deepfakes' can even be used during online examinations and job interviews. The tool has achieved over 90 per cent accuracy, The other two members of the developing team are IIT students Vineet Mehta and Parul Gupta.
