What is Deepfake Technology
Deepfake technology is a way to use powerful machines and deep learning to manipulate photos, movies, and audio.
Among other sins, it is used for creating news and committing financial fraud.
Cybercriminals use artificial intelligence technologies to overlay a digital composite over an existing photo, audio file, or video.
In 2017, a person on Reddit who went by the handle “Deepfakes” went by the phrase “deepfake.”
This person created and uploaded pornographic videos by using Google’s deep-learning, open-source technology.
What is Deepfake Technology
Deepfake learnig
Deepfake technology is now being used for evil things like financial crime, identitytheft, automated misinformation attacks, social engineering, celebrity pornography, fraud, and hoaxes, among other things. Prominent figures like previous US Presidents Barack Obama and Donald Trump, Indian Prime Minister Narendra Modi, etc., have been imitated using deepfake technology.
How are Deepfakes Used?
Two machine learning models are used for creating convincing deep fake movies: one analyzes whether a video is real or fake, while the other creates false videos using a collection of sample videos.
Generative Adversarial Networks (GANs), another kind of machine learning, are frequently used to improve deepfakes. These two models are trained to compete with one another using the GAN technique until the second model loses its ability to discern between authentic and fraudulent films. The result is a deep fake that looks authentic to viewers who are not humans.
Realistic deepfakes may be produced using GAN most effectively when a large dataset is available for it to learn from.
For this reason, deepfakes frequently target politicians and celebrities. This is because they are well-known in the public and offer a wealth of content that AI can use.
One of the foremost authorities in this area, Chris Ume, for example, has produced very lifelike deepfakes of Tom Cruise on TikTok that have gained a lot of traction. Ume claims that producing complex deepfakes needs a lot of data, which has to be carefully cleaned to make sure that only the best data is used.
The following are a few of the more striking instances of deepfakes that highlight the technology’s frightening potential as well as its creative opportunities
Risks and Dangers of Deepfake
Deepfake technology’s ascent has significantly increased the risks and perils in our digital environment. Using deepfakes, one can:
- Spread disinformation and propaganda
- Manipulate political discourse
- Damage reputations
Furthermore, deepfakes can be employed for nefarious activities like fraud and extortion. A deepfake video, for example, can be used to pose as someone else and demand money or private information.
Deepfakes pose a threat to privacy and security as well. In particular, deepfake-based assaults can easily target face liveness verification, an aspect of facial recognition technology that depends on computer vision to confirm the presence of a real user.
Such attacks have the potential to seriously jeopardize user data security and raise serious security issues for both users and applications.
Political Implications of Deepfakes
Deepfakes can undermine democratic processes, alter government regulations, and cause division among the populace.
The capacity to produce successfully phony recordings of political figures can cause confusion, deception, and a decline in confidence in government agencies. Furthermore, information of this kind has the ability to influence and warp the complex media landscape.
Social Implications of Deepfakes
Because social media platforms now dominate our online lives, there is always a risk of deepfake information spreading unchecked.
Regrettably, many who have created deepfakes have abused this technology by taking advantage of and damaging individuals. For instance, deepfakes are used by cybercriminals to perpetrate identity theft and online fraud, while deepfakes themselves are the target of scams that deceive people.
Economic Implications of Deepfakes
Deepfakes have the potential to seriously harm economies and enterprises in the information-based economy of today.
The possibility of market manipulation is one of the biggest effects on the economy. A firm’s stock price may fluctuate, and actions that favor the people who created the deepfakes may result from the creation of incorrect or misleading information about the company.
How to Spot a Deepfake
Though it can be difficult to spot a deepfake, there are a few techniques people can employ to recognize phony media.
Here are a few of the best techniques for spotting a deep fake:
Keep an eye out for irregularities: Deepfakes frequently feature irregularities in the lighting, shadows, and reflections that are absent from authentic media.
Examine the audio: Pay close attention to the video’s audio. Audio quality in deepfakes can be artificial or erratic, with changes in vocal pitch or background noise, for example.
Employ tools for detecting deepfakes: A number of tools have been created to assist in identifying deepfakes. These instruments examine different facets of the media, including skin textures, eye movements, and facial expressions, in order to identify instances of media manipulation.
Microsoft’s Video Authenticator, for instance, can identify grayscale parts and blending boundaries that are imperceptible to the human eye, and Facebook’s Reverse Engineering can identify fingerprints left behind by an AI model.
Look out for artificial motions: Deepfakes may have movements that are not characteristic of actual humans. In the video, look for any distortions or glitches that deviate from the normal patterns of movement.
