What Is Deepfake? Meaning, Types of Frauds, Examples, and Prevention Best Practices for 2022

A deepfake is an artificial intelligence-powered form of media that depicts a person saying something they did not say, appearing in a manner different from authentic visuals, or diverging from reality somehow. Its purpose is to fool the media viewer or a technology system. This article explains how deepfakes work, the fraudulent activities they enable, and how to protect against them.

What Is Deepfake and How Does it Work? 

A deepfake is defined as an artificial intelligence-powered form of media that depicts a person saying something they did not say, appearing in a manner different from authentic visuals, or diverging from reality somehow, with the purpose of fooling the media viewer or a technology system. 

A deepfake is a human impersonation created with advanced technologies, including artificial intelligence (AI) and deep learning. It can be a fake picture or clip of a person’s expression, an audible file or filter that imitates their speech, or anything else that resembles a person using machine learning (ML). 

Visual and audio alteration has been practiced for many years. For instance, graphic editing techniques were used in films to smooth over movie flaws, and individuals have been using image editing software to generate memes since the dawn of the internet. Deepfakes are an AI-enabled extension of this, which can be used to mislead users. 

They may also use newly emerging technology such as autoencoders and synthetic adversarial systems. Threat actors can use deep learning algorithms to target specific features of a person’s likeness, such as their face structure or body language. It provides incredibly convincing impersonations that hackers are trying to take advantage of.

The rising reliance of enterprises on video-based interactions is expected to encourage attackers to engage in deepfake assaults. According to Darren ThomsonOpens a new window , CyberCube’s Head of Cybersecurity Strategy, as sensitive data becomes more widely available online, fraudsters drive innovation to take advantage of this phenomenon. He has mentioned that new and developing social engineering approaches like deepfake audio and video have become technically and commercially viable for criminal organizations worldwide.

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How does deepfake work?

Machine learning is a crucial component in the development of a deepfake. Convolutional neural networks are artificial Intelligent computer systems built partly on the human mind, meant to spot trends in information. Deepfakes depend on artificial neural networks. The process of making a deepfake starts here.

To make a deepfake video, the developer first feeds countless hours of actual video footage to a deep neural network, which is then “trained” to recognize detailed rhythms and traits of a person. This is performed to provide the algorithm with a realistic representation of how that individual appears from various perspectives. 

The next move is to combine the trained learning algorithm with computer graphics technologies to overlay real-time video of a person with AI-generated facial and vocal patterns obtained from neural network input. Although many people believe that constructing a deepfake needs complicated tools and specialist knowledge, this is not the case — they can also be created with only basic graphic design knowledge. 

While sophisticated approaches are required for hyperrealistic deepfakes, all a hacker need is access to somebody’s video or audio material. Given the vast amount of content currently available, this is particularly feasible, as original material is available in abundance to fuel the algorithm and build a convincing deepfake.

While the capacity to constantly swap faces to create genuine and realistic-looking artificial video has some intriguing innocuous applications (such as in movies and gaming), it is a powerful weapon with some worrying implications. Creating synthetic pornographic material was one of the earliest practical uses for deepfakes. 

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Types of Deepfake Frauds

Now that we have established what a deepfake is, let us consider its various types: 

1. Textual deepfakes

Earlier, it was thought that a machine could not do a creative project like drawing or writing in the early stages of machine learning and natural language processing (NLP). Fast forward through 2021, when top-rated AI-generated writing can now compose human-looking pith and clarity, thanks to the robust language models and libraries developed over decades by the incremental labor of scholars and data science specialists.

2. Deepfake video

Deepfake criminals’ primary weapon is the creation of fake photographs and videos. Given that we live in the omnipresent social media world, where videos and photos elucidate incidents and stories better than the text format, it is the most widely used type of deepfake. 

Modern video-generating artificial intelligence is more competent than natural language AI and may be more hazardous. Hyperconnect, a Seoul-based software firm, released MarioNETte in 2020, a program that can create deepfake movies of historical people, celebrities, and leaders. This is accomplished by having another individual reenact the desired personality’s facial gestures, which are then placed on the intended personality’s deepfake.

3. Deepfake audio

Text, photos, and video are not the only things that neural networks and artificial intelligence can do. They also can clone a human voice. All that’s needed is a data repository containing an audiotape of a person whose voice must be imitated. Deepfake algorithms will be able to learn from this data collection and replicate the prosody of a specific person’s voice.

Commercial software such as Lyrebird and Deep Voice has been introduced. Still, you only have to say a few phrases before artificial intelligence becomes acclimated to your voice and accent. This program becomes strong enough to copy your voice as you send in more recordings of yourself. You may simply deliver a phrase or a sentence after loading in a collection of your voice recordings, and this deepfake program will describe the text in your tone.

4. Deepfakes on social media

One can use deepfake innovation in conjunction with creating stories or blogs to build a fake internet profile that would be difficult for a regular user to detect. A deepfake with the identity Maisy Kinsley on social media sites like LinkedIn and Twitter, for instance, was convincingly a (non-existent) Bloomberg reporter. Her profile photo was unusual as if it had been made by software. Maisy Kinsley’s public profile regularly attempted to connect with Tesla stock short-sellers, indicating that the profile was most likely fabricated for financial gain.

5. Real-time or live deepfakes

Deepfake technology is astonishingly advanced, allowing firms to generate advertising clones, governments to imitate political adversaries, and hackers to recreate user voices to pass voice-based authentication. 

Youtubers are already changing their faces in real-time using a novel deepfake program. For example, DeepFaceLive is an open-source artificial intelligence software that can convert your visage into someone else’s via videoconference and streaming networks. Streamers already have started utilizing the feature on platforms like Twitch, and both broadcasters and developers of any other media output can use this program.

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Deepfake Fraud Examples

Recent examples of fraudulent activities carried out using deepfakes include:

1. The Mandalorian Luke Skywalker deepfake

Star Wars fans were ecstatic when Luke Skywalker appeared in The Mandalorian’s season 2 finale. However, once the space dust had cleared, viewers were keen to point out problems in the digital reconstruction of a youthful Mark Hamill. YouTuber Shamook tried his hand at deepfaking a Luke Skywalker from the Return of the Jedi age, with stunning results.

Shamook had been recruited by no one other than Industrial Light and Magic, the renowned visual effects company responsible for bringing the Star Wars universe to life. We’re interested in watching how deepfake technology shapes the universe far, far away.

2. The Nancy Pelosi slowed-down video

It was not a deepfake in the traditional sense; instead, it illustrated why its possible misuse has become so dreaded in geopolitics. The 2019 clip was slowed down by 25% and video changed the pitch to make it appear as though Nancy Pelosi, the United States House of Representatives speaker, was gurning her words. 

The tape was shared worldwide, and after the video was fact-checked and found to be fraudulent, Facebook declined to remove it, saying it had decreased its circulation. The post was later taken down, although it’s unclear who was responsible and who took it down.

3. Obama’s message to the public

Most of the more convincing deepfakes have used imposters to impersonate the source’s speech and mannerisms, such as this video developed by BuzzFeed and actor Jordan Peele combining After Effects CC and FakeApp. Peele’s jaw was superimposed over Obama’s, with a jawline that matched Peele’s mouth motions replacing Obama’s. After that, FakeApp was used to improve the footage with almost 50 hours of automated processing.

4. Yang Mi travels in time

A video featuring Yang Mi, one of China’s renowned current performers, pasted into the 1983 Hong Kong tv series The Legend Of The Condor Heroes went viral a few years ago, clocking up 240 million views before being taken off by Chinese authorities. Its maker, a Yang Mi admirer, apologized on Weibo, saying he made the film as a caution to promote awareness of the innovation. 

While the film and television industries are likely to react negatively to deepfakes at first, it is also feasible to see how the sector could ultimately accept the innovation and profit from it by enabling viewers to perform director on home updates by tricking dialogue, inserting alternate scenes, or even playing characters themselves. There will also be a slew of celebrity cameos in video games.

5. Zuckerberg deepfake where he speaks frankly 

Artist Bill Posters uploaded this on Facebook-owned Instagram in June in reaction to Facebook’s failure to remove the clip of Nancy Pelosi, displaying Mark Zuckerberg bragging about how the site “owns” its followers. The video was created as part of Posters and Daniel Howe’s Spectre project, which was produced for Sheffield Doc Fest to highlight how one may use social media to deceive people. It was created using the VDR (video conversation substitution) software from Israeli `Firm Canny AI, which is being pushed with a deepfake singalong with several international leaders.

The posters used the hashtag #deepfake to call attention to it. While the video seems convincing in silent mode, the voice gives it away, demonstrating that a competent actor is still required to create realistic deepfake instances. However, with Lyrebird and Adobe VoCo proposing AI voice generation, it may not be much until one can simply add passable sounds to deepfakes.

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Deepfake Fraud Prevention Best Practices for 2022

Given the sophistication of the danger, businesses would be wise to take some basic and preventive steps to reduce the chance of falling prey to deepfake-based frauds. These are a few examples:

1. Use anti-fake technology

Finding a reliable means to identify deepfake attacks, especially using automated technologies, is one way for businesses to guard themselves against them. Such an opportunity is AI-powered detecting software. One may also use the same deep learning techniques to make deepfakes to detect evidence that a picture or video has been tampered with.

Deepfakes can be detected in a variety of ways, and this is only one of them. Watermarking information to detect manipulation is another technology-based technique. Amber Authenticate, for instance, is a cryptographic device that can produce hashes at predetermined intervals throughout a movie. If the video is changed, the hashes will shift, alerting the user that the material has been changed.

2. Espouse training and awareness

The uniqueness of the threat is among the grounds why deepfakes are dangerous to businesses. Most businesses still have no idea what deepfakes are or how damaging they can be. On the other hand, companies can lower their chances of falling victim to a deepfake assault by informing employees, management, and shareholders about the danger.

Enterprises can build an additional layer of defense with enough training and increased awareness. Employees should be able to identify deepfake-based social engineering efforts through training that emphasizes how technology is utilized in hostile actions and how to spot it. Businesses must take a systematic approach to developing a security-conscious workplace culture. Employees will be better at recognizing deepfakes if they are educated about security threats and preventative strategies.

3. Enforce robust security protocols

Technology may not be the only way to avoid deepfake videos. Rebutting deepfake with good fundamental security practices is surprisingly effective. Automatic checks implemented into any procedure for disbursing payments, for example, might have prevented numerous deepfake and related frauds.

• Inform employees and family members about how deepfaking operates and the difficulties it can cause.
• Teach yourself and others how to recognize a deepfake.
• Ensure that you are media savvy and use high-quality news sources.
• Have excellent fundamental procedures in place — “trust but verify.” A suspicious attitude about voicemail and videos will not protect you from being duped, but it will help you avoid many pitfalls.

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4. Explore the use of blockchain

Using blockchain as a solution could be a viable option. A decentralized system, or blockchain, allows users to store information online without the use of centralized servers. Furthermore, blockchains are resistant to a wide range of security vulnerabilities that centralized data storage is susceptible to. Although distributed ledgers are not currently capable of storing large amounts of data, they are suitable for storing hashes and electronic signatures.

Individuals may, for instance, use blockchain to authenticate and verify the validity of a video or audio document that is personal to them. The more people that sign film with their electronic signatures, the more likely it is to be deemed an authentic record. This is not the best option. It will be necessary to take additional measures to assess and factor in the competence of those who vote on a file.

5. Adopt a zero-trust approach to online content

Just as anyone can steal images and create phony profiles on the internet, scammers can go one step further using deepfake software. Before you trust anything you see on the internet, adopt a zero-trust approach and use caution. This advice applies to all new stories, images, and videos. You can learn to recognize bogus information by using web tools.

6. Prepare a response strategy

Make sure you are prepared to react to a deepfake in the right way. Prepare a strategy that you can implement if a deepfake is discovered. In this technique, you must outline individual responsibilities and required activities.

Identity checks like validation, device ID and analytics, behavioral analytics, and document verification are all critical parts of a multi-layered protection plan, especially when it comes to how scammers may try to spread or use these deepfakes. It may seem self-evident, but the first layer of defense is crucial: ensuring that only the proper people (and only the right people) have access to all potential areas of vulnerability. 

7. Develop new security standards

Another method of preventing deepfakes is implementing new security standards within your company. A deepfake’s ability to persuade a person is great, but its ability to persuade others drops rapidly when more individuals are involved. A corporation can detect a deepfake assault before it causes damage by adding numerous inspections to instances where deepfakes may be implicated.

Hackers use deepfakes to create phone and video calls while impersonating firm employees. As a result, firms can build security standards that outline an inspection routine that staff should take when answering such calls to detect deepfakes.

8. Keep user data private

Consider restricting the reach of your postings if you still want to be active on social media. Making your profile private is a wise approach to keeping your photos between a recognized network, even if it is not a failsafe solution to protect your pictures. Do not add strangers or connect with them if you do not know them. This is a general principle to follow if you do not want to fall victim to a trolling or phishing scam.

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Takeaways 

Today, governments and enterprises across the globe are concerned about the pernicious impacts of a deepfake attack. It could lead to several extremely disparaging and damaging outcomes for institutions and individuals alike, so a foolproof and robust security mechanism is strongly recommended. 

By adhering to deepfake fraud prevention best practices and maintaining a strong digital hygiene policy, companies can genuinely fight back against the many threat actors out there. Finally, it is also important to educate individuals (or your employees) on the insidious impacts of a deepfake attack and the most prudent ways to safeguard oneself from such an occurrence. By building this calibrated and well-articulated defense mechanism, deepfakes, and their creators can be held at bay. 

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