Spotting Deep Fakes

Posted by mctracy On September 6, 2022

Deepfakes are edited videos of people to make them appear to be someone else. A different person’s face is placed onto their face, usually with the intention to incriminate or embarrass someone.

“’DeepFaceLive is a live-streaming version of the popular DeepFaceLab software, and is capable of creating alternate video identities in real-time. From more or less face-on viewpoints, most of the celebrity recreations are quite effective, and some are very convincing even at fairly acute angles – until the facial angle hits a full 90°.ry good at recreating profile views.’ MARTIN ANDERSON, “TO UNCOVER A DEEPFAKE VIDEO CALL, ASK THE CALLER TO TURN SIDEWAYS” AT METAPHYSIC (AUGUST 8, 2022).” (Mind Matters).

This technology poses a serious threat to cyber security. Security professionals have offered some advice in how to spot these false identity video edits.

“With criminals beginning to use deepfake video technology to spoof an identity in live online job interviews, security researchers have highlighted one simple way to spot a deepfake: just ask the person to turn their face sideways on. The reason for this as a potential handy authentication check is that deepfake AI models, while good at recreating front-on views of a person's face, aren't good at doing side-on or profile views like the ones you might see in a mug shot.”

There are also detectors for deepfake software, however with the nature of evolving techniques in cybercrime, criminals find ways around these types of programs.

“Generally, it’s getting harder to detect deepfakes, which impacts to science research as well as consumer safety. One reason for that should be quite familiar. Political scientist Nina Schick, author of Deep Fakes (2020), admits, ‘This is always going to be a game of cat and mouse,’ Schick said. ‘Because just as soon as you build a detection model that can detect one kind of deepfake, there will be a generator that will be able to beat that detector.’” (Mind Matters).

According to Sensity, 90% of biometric verification systems used in live scenarios such as online job interviews were vulnerable to attack.

“Sensity, a maker of liveness detection and deepfake detection software, in May reported that it found nine out of the 10 widely adopted biometric verification systems used in financial services for Know Your Customer (KYC) compliance were severely vulnerable to deepfake 'face swap' attacks.” (ZD Net).

Still, there are additional measures companies can take to prevent these kinds of cyber attacks.

“Meanwhile, MIT’s Media Lab offers eight tips for detecting deepfakes on our own. Here are three:

‘1. Pay attention to the cheeks and forehead. Does the skin appear too smooth or too wrinkly? Is the agedness of the skin similar to the agedness of the hair and eyes? DeepFakes are often incongruent on some dimensions.

Pay attention to the eyes and eyebrows. Do shadows appear in places that you would expect? DeepFakes often fail to fully represent the natural physics of a scene.
Pay attention to the glasses. Is there any glare? Is there too much glare? Does the angle of the glare change when the person moves? Once again, DeepFakes often fail to fully represent the natural physics of lighting.’” (Mind Matters).

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