The goal of technology is to make life easier. However, innovations are amoral. In other words, they lack a moral sense. Technology is neither good nor bad. Ultimately, it depends on how humans utilize it.
Deepfake is one such mechanism. On the upside, the tech offers tremendous benefits in education and healthcare. People use it to create realistic simulations, facilitate communication, and personalize experiences.
Sadly, criminals also leverage deepfakes to cause harm, so much so that they raise concerns about identity theft, misinformation, and erosion of public trust in the media. In this article, we’ll examine how much risk deepfakes pose for online security.
Source: Freepik
What Are Deepfakes
Deepfake is a form of artificial intelligence that can be used to create convincing sounds, videos, and images that mimic an original. The creators use machine learning algorithms and Generative Adversarial Networks (GANs). These algorithms analyze and replicate human likeness. Then, they use them to design realistic but fake videos, images, and audio.
In late 2017, a pornographic video of Gal Gadot started making rounds on the internet. However, it wasn’t her. Instead, the creator attached the actress’s face to an existing video. Despite being fake, the video quality was exceptional, enough to convince casual viewers.
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In 2020, Dave Gershgorn released new music using tracks from living and dead artists. Examples include Frank Sinatra, Elvis, and many more. The tracks were removed after Roc Nation LLC sued YouTube. A year prior, fraudsters tricked the CEO of British Energy into sending $240,000. A jealous mother also forged explicit images of her daughter’s cheerleading rival.
In 2021, someone uploaded a deepfake video of Tom Cruise sucking a lollipop and performing a magic trick on TikTok. Worse still, all types of deepfake media (images, text, audio, and video) can be used to simulate or represent an individual.
How Deepfake Technology Works
Deepfake technology uses AI-driven machine learning models. These tools leverage vast amounts of data. GANs use two neural networks. One generates fake content, while the other evaluates its authenticity. Over time, the generator improves its result until it becomes convincing enough. It mimics voice tones, body movements, and facial expressions.
Due to technological advancements, it is becoming more difficult to distinguish real footage from deepfakes. Understandably, you must know how deepfakes work to stand a chance. Manual methods like detecting language patterns, reverse image search, and AI detection tools help you identify fake content. Still, not everyone can detect deepfakes before harm.
As deepfake technology improves, it becomes even more important to have ways to detect fake content. Better detection tools and increased awareness are necessary to prevent the spread of false information. Staying informed and knowing how to verify content is crucial for everyone.
Common Uses of Deepfakes in Online Scams
The most popular use of deepfake is in perpetuating online scams. The common ones are:
Deepfake Identity Theft and Fraud
Fraudsters create fake images or videos to bypass identity verification systems. Like in the case of Tom Cruise, they replicate the victim’s face and voice. With this, they apply for loans, open fraudulent bank accounts, and gain authorization to secure systems.
Deepfakes in Phishing and Social Engineering Attacks
Traditional phishing scams happen via emails and fake websites. However, deepfakes now allow individuals to use voice or video recordings to impersonal executives. They trick employees into sharing confidential information or transferring funds.
Financial Scams
Criminals use deepfakes to create fake news. These news articles feature government officials or well-known CEOs. For example, an executive may announce false company earnings to manipulate the financial markets. Likewise, a politician may give a speech that is enough to impact public trust.
Nonconsensual Pornography
Another major threat of deepfakes is pornography. Surprisingly, this accounts for 96% of deepfakes on the internet. Criminals often target celebrities, creating revenge porn.
Disinformation
One time, a fake video of Mark Zuckerberg claimed to have complete control over the data of billions of people. Deepfake videos of Donald Trump are also widespread online, raising concerns about manipulation among the public.
Challenges in Detecting and Preventing Deepfakes
AI-based detection systems analyze inconsistencies in video and audio. However, technology improves daily. As a result, deepfakes are advancing faster than countermeasures. Typically, people look for audio mismatches, unnatural facial expressions, and blinking patterns to reveal a deepfake.
But as AI improves, the signs become harder to spot. Many researchers and tech companies are developing AI-powered tools to identify deepfakes. However, most of these solutions are in their development stages.
Source: Freepik
How to Protect Yourself From Deepfake Scams
Deepfake videos, texts, and audio can affect anybody. Here are some tips to protect yourself:
- Always verify the source of information before sharing or believing it.
- Use tools like Google Reverse Image Search to check the authenticity of any media you receive.
- Look for inconsistencies in the face, lip, and eye.
- Implement multi-factor authentication to prevent unauthorized access to your online accounts.
- Use AI-based verification tools to analyze and identify potential deepfakes. Examples include Copyleaks or Original AI (texts), Reality Defender or Microsoft Video Authenticator (audio & video), and Hive Moderation or AI Image Detector (images).
- Train employees on how to detect and respond to deepfake threats.
Are Deepfakes Bad?
The use of deepfakes determines whether they are good or bad. With proper disclosure, many consider deepfakes to be fair.
In other words, the audio, video, or text must not violate someone’s intellectual property rights or privacy. If the content is misleading, then it is bad. Use the table below for more information on the acceptable uses of deepfakes.
| Features | Acceptable Uses |
| Parodies | Satire in entertainment or political speeches and meme culture |
| Film industry | De-aging actors, posthumous performances, voice cloning for dubbing |
| Education | Historical reenactments, personalized learning, medical training |
| Assistive technologies | Sign language avatars and speech restoration |
| Gaming | Player avatars in extended realities and realistic Non-Player Characters (NPCs) |
| Law enforcement | Crime reconstruction & facial recognition training |
Conclusion
Concerns about the harmful effects of deepfakes are growing. The system is becoming more sophisticated, posing serious threats to businesses and individuals. Cybersecurity efforts must focus on raising awareness, developing AI countermeasures, and implementing security features.
To use deepfakes, request consent before adoption. Likewise, label them to avoid deception. Finally, avoid using your content for harassment, misinformation, or illegal activities.
