AI and Frauds: How to Protect Yourself from Deep Fake Videos

Deepfake videos and AI frauds are increasingly becoming rampant, spreading misinformation and defaming reputations. These videos not only defame the reputation of innocent people but also rob them of hard-earned funds through fake investment opportunities.

However, in this article, we dive deep into key signs you can use to tell a deepfake video and the tools that can help identify these videos before the situation worsens.

What Are AI Deep Fake Videos?

Deepfake is an artificial video created from deep learning, an aspect of machine learning and a branch of AI that programs computers to carry out tasks through experiences. The main aim of deepfake is to influence people to think something happened when it didn’t. Anyone who can create deepfakes can spread misinformation and cause people to behave in a way that will propagate their agenda in some way.
 

Deepfakes have been used for humour and other entertainment purposes, but they can also be used for many AI-generated video scams like reputation smearing, hoaxes, celebrity pornography, social engineering, election manipulation, and other fraudulent purposes.

Typical ways you can spot a deep fake videos include unnatural eye movements, awkward facial positioning, lack of emotion, hair that doesn’t look real and many other tell-tale signs.

Related: AI and Fraud: Opportunities and Challenges

What are the Common Types of AI Video Frauds?

1. Automated social media manipulation

AI has been used to manage fake social media accounts while influencing the public and promoting fraudulent schemes. These AI scam bots can mimic human interactions, making them hard to detect. A deep fake video security tip would be that   social media platforms improve their fraud detection algorithms and users should also verify information through verified sources before going ahead with discussions, especially sensitive ones.

2. Synthetic voice scams

Scammers use AI to create or mimic real voices to impersonate specific individuals to create personas for a scam call. An alarming case was that of a director of a large corporation telling his employee to transfer funds. To curb this AI scam, implement a verbal password into your system and train staff to recognize potential AI voice scams. AI and fraud awareness are necessary if you want to curb the menace of deep fake and scams perpetrated on the internet.

3. Virtual reality scams 

With virtual reality, AI has been a pivotal tool in creating immersive yet fake experiences like fake virtual real estate and other investment opportunities. These scams are quite elaborate and exploit the new and unregulated virtual reality space. An example of such a scam was the sale of non-existent virtual reality which cost investors millions. An AI deep fake prevention method would be for investors to always conduct thorough due diligence and seek legal counsel before investing in virtual assets.

Key Signs of Deep Fake Videos

Scammers typically trick their victims into cooperating with their demands before they know they are being deceived. Scammers build on traditional means with AI technology. However, spotting AI-generated scams is possible. Here are some red flags to help you find out when something is wrong:

1. Links to chatbot

If you find yourself talking to a chatbot after clicking a link on a text or email, you are likely in the middle of an AI scam. 

2. Asking for personal information

An AI scam will ask for your personal information that is not relevant to the exchange or discussion. This is so they can gain access to your accounts from different loopholes in the financial system.

3. Odd images

Some scams use AI images for adverts to get viewers to buy a fake product or purchase a service that does not exist. If you look closely at AI images, you will find that they are usually not perfect and that typically gives them away.

Tools to Identify AI Manipulated Videos

If you are wondering how to detect deep fake videos, these tools have been pivotal in identifying manipulated videos and images:

1. Open AI Deep Fake detector

Open AI has launched a fake video detection tool that can identify AI images with accuracy. It can identify images created by OpenAI's DALL-E 3 with a success rate of 98.3%. However, it is less effective when analyzing images from other AI systems and flags only 5-10% of them. While it has not yet been publicly released, it works based on a binary system and uses tamper-resistant metadata to improve content traceability.

2. Hive’s AI deep fake detector

Hive AI came up with a powerful detection API that identifies content images and videos. It is typically used for content moderation which helps digital platforms detect and remove deep fake media. Such media includes non-consensual deep fake pornography and misinformation. This model works by first detecting faces in an image or video then labelling them as deep fake or not.

Because of its accuracy, the US Department of Defense has invested up to $2.4 million in Hive's AI detection tool. It was selected from 36 firms to help the defense unit counter misinformation and synthetic data.

3. Intel's FakeCatcher

Intel’s FakeCatcher is the world's first real-time deepfake detector that uses biological signals to authenticate a video. Traditional AI detectors rely on inconsistencies in facial or pixel movements, FakeCatcher uses photoplethysmography (PPG). This is a method that uses subtle changes in blood flow in video pixels. This approach is effective in determining between real and AI-generated videos in seconds.

This program runs on 3rd Gen Intel Xeon Scalable processors which can process up to 72 real-time deep fake streams. This model has a success rate of 96% and 91% when tested on extreme deep fake videos. Intel’s FakeCatcher can be used in media and broadcasting, content creation, social media and other public domains.

Future Trends in Deep Fake Detection

Deepfake detection methods are likely to have more advanced AI algorithms including machine learning, real-time analysis, and blockchain integration. However, here are some future trends you can expect from deepfake detection:

1. Multimodal analysis

This involves bot just visual signals but audio inconsistencies, lip synchronization and even speaker identification to handle audio manipulation.

2. Biometric integration

This combines deepfake detection with biometric verification systems to cross-examine identities and detect manipulated content. Since biometrics cannot be manipulated, this provides an added layer of security to the detection process.

3. Blockchain verification

Blockchain verification creates tamper-proof records of media content. This allows you to trace the source and history of the media file. This can help you to identify discrepancies easily.

4. Quantum computing potential

Quantum computing performs complex calculations on data sets to improve the deepfake detection process. With quantum computing, algorithms can easily track down deep fake media and improve the process.

Conclusion

Deepfakes are an unfortunate partner to the advent of AI and machine learning. While AI can be a good addition to everyday work tools, deepfake poses a threat to digital security. However, it is still possible to protect oneself against these manipulations. 
 

Youverify supplies a biometric verification kit that when combined with deep fake detection, can be a significant advantage to spoting and preventing further deepfake videos and AI frauds. With Youverify’s host of resources, you can equally learn more about deepfake and other methods to safeguard your media against manipulation.