Although there have been remarkable advancements in artificial intelligence, they have also led to the innovation of deepfake technology. Nevertheless, this can help people to do various tasks that require the same human being in many places. For example, some celebrities mentioned that Deepfake helps people attend press conferences online, which is hectic to handle physically. However, no technology is secure from criminals, and they utilize every innovation for their illegitimate activities. Similarly, fraudsters now utilize deepfakes to bypass securities, particularly the biometric system. Many competitor firms involve deepfake technology for various immoral activities.
This blog post will describe the nature, types, and examples of deepfakes. Additionally, it will provide a solution for organizational security from advanced criminal strategies such as deepfakes and spoofing attacks.
What are Deepfakes?
A deepfake is a specific kind of synthetic media, including videos, voices, and images. This media involves the swapping of various biological traits with another person’s likeness. It can be true that deepfakes are used as an open source for face swapping. Other than people who are alive, nowadays, there can be the emergence of deepfakes of those who do not actually exist or are dead. This technology involves the generative adversarial networks (GANs). A GAN can be thought of as a dual AI system where, in one place, it works as a rebellion and in another as a savior. Criminals utilize GAN to generate deepfakes, which they use in the execution of their illicit plans. On the other hand, deepfake detection technology involves the GAN algorithms to differentiate between fake and real data.
How Deepfakes Are Created?
Deeofake creation is not as simple as it appears. It is not simply about the application of filters or swapping techniques. However, it is a complex process that involves a vast amount of relevant data and computing services. A large number of data sets are required to go with mimicry or replication. This data involves images, videos, and audio of an entity that has to be replicated. Then, using the GANs, artificial intelligence algorithms are trained to replicate the same physical features in deepfake videos, audio, or images. It works for the replication of sound patterns, facial data, and other physiological appearances. However, it is not easy to replicate all biological patterns and traits, and this leaves room for deepfake detection through advanced technology.
Common Types of Deepfakes
Deepfakes are not only videos or images but also audio. Video deepfakes involve the alternation of a person’s facial data as well as voice and micro-expressions. Audio deepfakes involve only voice, which is often used to spread misinformation. It is mainly used in celebrity fake voice clips and political misinformation. Both audio and video deepfakes have their use cases. It involves both playful and criminal usage as per the purpose. Many criminals utilize deepfakes to bypass securities for their illicit activities. It makes organizations victims of various legal complications and financial loss. The financial sector, which provides online services, is currently facing threats from money laundering activities. It is necessary to utilize deepfake detection technology for organizational security from criminal tactics.
Some Real Life Examples of Deepfakes
One of the deepfake cases occurred in 2019. when the CEO of a U.K.-based energy firm listened to his boss’s order to transfer €220,000 to a supplier in Hungary, his boss was a leader of the firm’s German parent company. Afterward, it was determined that the CEO recognized the voice call as his boss, but actually, it was a deepfake. The caller tried several other times to get money, but the U.K. executive had identified the suspiciousness and did not transfer money anymore.
Another example is Barack Obama’s deepfake, in which he was giving a public service announcement regarding the warning against fake news. But it was identifies that it was not actually Obama’s video but a deepfake who was produced by Jordan Peele in collaboration with Jonah Peretti, a BuzzFeed CEO.
Two years before, a series of deepfakes, Tom Cruise, went viral on TikTok. These deepfake videos presented a collaborative effort between a Tom Cruise impersonator named Miles Fisher and Chris Umé, who was a visual effects specialist.
The number of deepfake attacks comes in front every day, and effective measures are required for detection and real-time organizational security. Deepfake detection technology is the most reliable and best solution for its auto-check service and accuracy of results.
Final Words
Deepfake technology has brought various complications to many industries. Criminals utilize deepfake videos to bypass securities. It is necessary to utilize deepfake detection solutions within the actors to prevent criminal activities. Financial sectors now provide digital services and use biometric security systems. Hence, they require deepfake detectors to secure their landscape from financial terrorism and money laundering. Additionally, deepfakes in the form of audio and videos are making various entities victims of many complications.
