Cyber Safety Cyber security Quick Tips

What is Deepfake Technology and How can you spot them?

Deepfake technology, much like face morphing, is a product of Artificial Intelligence technology that is frequently used to create and disseminate fake video content and generate fake news. Hackers use this to often alter pornographic video content by placing celebrities’ faces on them.


It is a combination of two clashing AI technologies: the generator and the discriminator. The generator is the creator of the fake content, whereas the discriminator is the filter that decides if the content is fake or authentic. These technologies are adaptive and self-learning since they learn from their experiences. The discriminator provides insight into the unauthentic characteristics, while the generator uses these learnings to take a different approach. The combination of these two systems makes up the generative adversarial network (GAN).


There are always pros and cons to new technologies. Deepfakes can be used to create both positive and negative effects. It has helped ALS patients or people with speech impairments to communicate effectively. It can result in major cost savings by creating efficiencies in the film, medical and non-profit industries. However, there are several cons as well.


Due to Deepfakes, the authenticity of audio and video has been challenged, and people aren’t aware of the possibilities of its tampering or ramifications. World leaders, corporate heads, and celebrities can now easily be framed saying things that were never said leading to harsh consequences. Even though it was first noticed in 2017, since then not much has been done from a legal viewpoint to monitor the creation or distribution of such content.

Damage to Company:

One of the greatest reputation damage to enterprises is misrepresentation in the form of fake comments made by the company. That is the true purpose of Deepfake technology. Cybercriminals now use deepfake technology to launch unidentifiable phishing attacks, where it becomes difficult to differentiate between the real and fake entity.
Fake content can arise from the internal organization, for instance, in the form of fake reviews to meet Key Performance Indicators. These practices must be governed by cybersecurity policies dictating the use of company IT assets.

How to spot Deepfakes:

As the technology keeps improving, it’s getting harder to identify original content and deepfakes. But here’s how you can spot them:

1) Deepfake faces don’t blink normally. The majority of images show people with their eyes open, so the algorithms never really learn about blinking. But as soon as this weakness was revealed, deepfakes started appearing with blinking.

2) Poor-quality deepfakes are easier to spot. The lip-synching might be bad, or the skin tone patchy. There can be flickering around the edges of transposed faces. And fine details, such as hair, are particularly hard for deepfakes to render well, especially where strands are visible on the fringe. DeepFakes often fail to fully represent the natural physics of a scene.

3) Badly rendered jewellery and teeth can also be a giveaway, as can strange lighting effects, such as inconsistent illumination and reflections on the iris.

Prevent yourself from Deepfakes:


A block-chain can prove to be an effective way to counter the tampering of videos. A block-chain is a digital ledger that documents any alterations made to an original video so that the creator can track changes.

Hashing is another technique that is basically a digital watermark that provides each video with a combination of numbers that is unique to the video and is lost if the video is altered.

Companies need prevention measures to monitor mentions of the company and its employees over the internet. They can work in coordination with content delivery networks to manage or monitor this information. The most effective way to prevent misrepresentation of an enterprise is to secure your identity.

Secure your Identity:

Organizations must realize the need to implement strong identity protection measures. Apart from just capturing employee biometrics, these measures can also determine how to best safeguard the information to prevent the creation of potential fakes.


The world of technology is evolving, and we must adapt to it. There will be a time when it will be impossible to distinguish real content from fake ones, and at that stage, our credibility as an individual, enterprise, and nation must be intact. The reason being people will only judge the source and context of the content and not the quality. This eventually means that the best practices we exercise today to guard our identity will go a long way in developing and sustaining our credibility at present and in the future.


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