Originally developed for use in visual effects and media creation, deepfake technology is currently being used maliciously. Although there are undoubtedly a lot of beneficial applications for the technology, the race has been heavily dominated by the negative ones.
- When the foundation for the creation of the “Video Rewrite Program” was established in 1997, the idea of deepfake was established. This ground-breaking software could change audio and video data using neural networks and could generate facial motions from auditory inputs. Additionally, deepfakes in the early 2000s were made possible by the creation of this program.
- Later, a new algorithm called the “Active Appearance Model” was released, and because of its effectiveness and capabilities, it quickly gained popularity. Convolutional neural networks (CNNs) were the mainstay of the algorithms, which meticulously examined the targeted person’s facial traits to recreate incredibly realistic photos or movies.
- In 2017, when a Reddit community saw a spike in deepfake photos and videos, causing alarms and upsetting worries, deepfake technology gained more attention.
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How These are Created?
Deepfake generation is becoming easier with sophisticated AI algorithms and deep learning models. The abusers can easily obtain the targeted people’s biometric information and use it to create identities that are impossible to refuse. To the extent that it becomes difficult to distinguish between a real person and a phony identity, the deepfake photos or videos seem incredibly lifelike and convincing.
Deepfake production makes considerable use of autoencoders and GANs. Deepfake videos are produced using encoders and decoders that are implemented inside the framework of GANs. After receiving the facial data, the encoder examines the characteristics and extracts the necessary facial properties. The decoder receives the separated facial attributes and uses the information to assemble the face, repeating the process until the desired results are obtained.
How Deepfakes Can be Detected Using Software?
Several software that are designed to detect the spoof. These help one to take an action against such frauds and detect the fraud timely. By doing so, such crimes and malicious activities can be mitigated timely.
Moreover, all the advanced software that is designed for the detection of deepfakes works with the same technique. A sophisticated security method used in face recognition technology to verify the claimed identity’s liveness is called “liveness detection.” Biometric liveness detection can quickly identify deepfakes by identifying spoofs or fake identities by examining little movements or microexpressions. Through offsite liveness detection, this technology may verify the legitimacy of previously posted photos or videos on social media.
Facial recognition algorithms that incorporate texture analysis can successfully differentiate between a real person and a mask or fake identity. The method closely examines the skin’s texture, including pores, wrinkles, blemishes, and color, making it difficult for spoof identities to imitate or reproduce. The detection of deepfake attempts is aided by these small facts. In this, the use of deepfake detection technology is highly encouraged along with educating the audience.
How Financial Fraud Can be Done Using Deepfakes?
AI is becoming a very powerful tool for financial fraud through the use of deepfakes. Deepfake fraud includes posing as bank employees or clients, deceiving organizations into approving transactions opening new accounts, etc. As you might expect, scammers employed deepfakes of speech to impersonate business bosses, who then gave staff orders to transfer substantial amounts of money. Most of the time, the scam is not discovered until it is too late. Deepfake fraud is one of the most pressing issues facing financial institutions today since deepfakes can be used to propagate misleading information, influence markets, or fabricate identities for money laundering.
How Deepfakes Can Be Utilized By the Fraudsters?
Deepfakes are a key tool used by scammers in their operations. When they fall into the hands of scammers, many businesses experience significant financial losses. These days, companies collaborate with organizations through digital offerings and employ remote dealing techniques. They use digital communication channels to conduct all required business-related conversations and hold remote meetings. Many businesses lose money because they are unable to detect deepfakes and send large sums of money to the accounts of scammers. Secure business operations and work require the use of AI deepfake detection software. Having strong systems in place to detect deepfakes online is essential.
Conclusion
Deepfake software provides an opportunity for many people to use it for various purposes. Deepfakes are highly effective in boosting creativity in the fields of art, media, film, and other fields where needed. Many professionals can make a productive use of this technology for a positive contribution. Online deepfake detection can be extremely beneficial to detect the spoof timely.
