Deepfake Detection: What Are Deepfakes?

When technology starts becoming damaging instead of making life easier, it is important to understand it well and take preventative measures. One such thing with the increasing use of AI is deepfakes. The market size of deepfake AI will reach $19,824.7 million by 2033, with a growth rate of 44.3%. And there are serious consequences of this form of cybercrime, where fabricated media of a person saying or doing something they never did is circulating. 

In this blog, you will understand how deepfakes are made, their types, ways to spot them, and what can be done to stay safe. 

Before getting deep into what it actually is, let me first take you to some real-life case studies/examples involving deepfakes that led to harmful consequences. This will help you understand better why you exactly need to get in-depth information on deepfakes. 

Fake Video of Bombay Stock Exchange (BSE) MD & CEO

Recently, a fake video of the Chief Executive of the Bombay Stock Exchange, Sundararaman Ramamurthy, was all over social media sites, especially in India. The video shows him advising about which stocks to buy. And viewers were lured by lucrative returns if they followed the advice. 

Ramamurthy said, We don’t know the number of people who have seen this deepfake video, and it is difficult to find out, so we can’t judge if the impact was big or not. We want it to be non-impactful, as no one should suffer losses believing something untrue. 

“The latest data shows that over the past two years or so, we’ve seen an increase of almost 3,000% in the number of deepfakes being utilized,” says Karim Toubba, the chief executive of US-based password security company LastPass.

$46 Million Scam by Deepfake Romance Gang

A gang of cybercriminals used deepfake technology to create entirely fictional female profiles and lured several men in India, Taiwan, and Singapore. The scam network faded away in Asia. They developed a virtual romantic relationship with the victims, exploiting their emotions and persuading them to invest fraud crypto platforms. They successfully extorted a sum of 46 million USD from the victims. 

Celebrity Deepfakes

The list of cases in this category of deepfake scams can go on for miles; there have been several deepfake creations of actors, politicians, and public figures showcasing them saying, doing, or promoting stuff that they never actually did. And these have happened worldwide; one of the most talked-about examples is deepfakes of the US president, Donald Trump. There have been several claims that he uses such kinds of videos to glorify himself. Though there have also been several meme-type and funny deepfakes of the President. 

Another well-known case is of a woman who believed for two years that she was dating the actor Martin Henderson (famous for his roles in Virgin River and Grey’s Anatomy). The fakester used visual and audio deepfakes (voice messages) to lure the lady and convince her to build a life together. She was scammed out of $375,000 by sending him this money. 

How Are Deepfakes Made?

It requires a significant amount of effort, technical expertise, and steps to create deepfakes. Here are the steps:

Data Collection 

You need extensive and exorbitant data to generate a high-quality deepfake. You need photos, videos, and audio/voice recordings of the person you are targeting. Social media or publicly shared information by the individual are the main sources of information.

Data Processing

Now the information is cleaned and organized to extract faces from videos, tiny details and features, isolate voice samples, and prepare data for training. 

Model training

Using deep learning techniques, specifically GANs (generative adversarial networks) and autoencoders, to make Deepfakes. They learn patterns from the data. To train neural networks, people use many other similar AI frameworks. 

Generation

Now the model runs to create the new synthetic content and refine parameters to make them look real and believable. 

Post-processing

Using editing software to remove any errors or obvious artifacts to improve the overall quality.

How to Spot a Deepfake?

Deepfakes often show some signs that help you understand if the content is fake. Though extremely high-quality deepfakes are tricky to identify, you can still consider these signs. 

• You can identify deepfake videos by clear boundaries or borders where you can see image overlay.
• Graphical issues in head moments, as these fake videos are often best for slow, calm, and forward-facing expressions. 
• Irregular image colors, lighting, or quality. 
• Errors in facial expressions or lip syncs.
• Eye rendering issues and abnormalities in movements.
• Some natural permanent facial features may not be present, like birthmarks or moles, etc.
• Sometimes, you may notice that the original image or its elements may appear over the fake one. 
• Pixelation, flickering, and blurring can be signals too. 
• Also, these fakes are hyper-realistic; this is also a sign of fake content.

Best Deepfake Tools & Softwares 

Here is information about software that people use to generate deepfakes: 

Best Deepfake Detection Tools

Now that you know there are tools to make deepfakes, but not to worry, there are also counterattack tools and application which help you uncover synthetic content. 

Sensity AI

It is the best option for visual threat intelligence; it focuses on deception instead of just general editing. Its forensic signals help you spot manipulated footage. Whereas the mapping features find origin points and repost networks circulating the fake. The traceability feature is its strength. 

Microsoft Video Authenticator 

It helps verification teams that need practical manipulation scores for authenticity checks of video content. For heavily edited clips, frame-centric analysis is best for identifying common visual anomalies. Newsrooms and platform reviews can use it to detect fake content faster by looking at flagged spans instead of rewatching the entire content. The main advantage is review-ready scores for lined-up operations and rapid escalation. 

Sentinel AI

A best choice if you are looking to identify spoofed and fabricated personas during user verification. It will flag dubious onboarding and account recovery attempts, which prompt strong security and identity checks. The blend of fraud signals with behavioral information can prevent impersonation before a major incident occurs.

Pindrop Pulse

It is an audio deepfake detection tools which helps in the detection of heavily fraud-prone phone channels like support and finance. It offers voice authenticity scores and acoustic signals that can spot synthetic audio in real-time. Call centers can use it to stay safe from such impersonation fraud during calls before taking any harmful action. 

Conclusion

Deepfakes are something that can cause serious harm if not taken seriously; using them, a person can imitate anyone and make them do or say things they never actually did. These are mostly pictures or videos, but can also include voice fakes. They are made using advanced deep learning algorithms. High-quality deepfakes are sometimes hard to detect, but I have listed some of the best tools that can be of great help to you. There have been several cases of deepfakes that have caused serious damage to people’s reputations. So learn them and use the mentioned preventive measures.

Also Read: Data Privacy in AI Systems: You Are Being Watched