We are in an era of Generative AI, where artificial intelligence programs can write human-like prose, mimic voices, generate new images, etc. Deep Fake is a part of this latest creation. Again, enterprises are dwelling in an unending cat-and-mouse game of cybersecurity and hacking. With the rise of AI and ML techniques, the proliferation of Deep Fake technology poses a considerable hazard to the cyber world.
With time, AI tools and tactics are getting more creative and capable because of more data fed to them. Deep Fakes pose a significant threat to cybersecurity by introducing new forms of cyber crimes in the digital ecosystem. This article is a comprehensive guide on deepfakes and how security experts should take preventive measures against them.
What is Deepfake?
Deepfake is a technology that uses AI to generate videos, images, voices, or text to mimic that of a human. Here, the term “deep” comes from “Deep Learning.” It is a sub-field of machine learning and AI. It uses data to generate multi-layer neural networks. The term “fake” determines that the video, image, or voice generated by AI is a pseudo media. But, it becomes difficult to distinguish such digital content from human-generated media.
Deepfake technology often involves synthetic media and content like face swapping, fake voice generation, gesture and body manipulation, etc. Research and developments are going on to detect and countermeasure deepfakes through deepfakes detection techniques and tools. Various media firms and companies have been using deepfakes in movie scenes and museums to generate sets of multiple incidents and activities.
Involvement of Deepfakes in Cybercrime
Although deepfakes have numerous advantages across various industries like media, films, museums, animation, and games, cybercriminals can use them to generate miscommunication. Cybercriminals often use high-end machines for cybercrime. They replicate someone’s identity using multiple AI tools and ML techniques to circulate deceitful information.
Cybercriminals increasingly use deepfakes to generate convincing hoax images, sounds, and videos. Through such content, cybercriminals try to impersonate individuals, often superimposing their criminal wants and thoughts onto another person. Cybercriminals also take sample voices and manipulate those voices to say or do things the original person never intended to say or do.
According to Reuters report, Deep Media estimated that 500,000 voice and video deepfakes will be posted on social media websites in 2023. Deep Media also disclosed the reality that cloning a voice needs a $10,000 server cost. It also required powerful machines for AI training until late last year. But now, many startups have started offering such services for a few dollars.
Deepfake technologies have evolved as the highest form of social engineering attack. With deep-seated instincts and gaining trust by tricking into believing masses that something is real, cybercriminals earn millions. Some deepfake videos and voice help defame organizations or a person who is the face of a brand. Here is an example of the most infamous deepfake video that surfaced when the Facebook privacy debacle hit.
Various Use Cases of Deepfakes in Cybercrime
There are numerous appalling and malicious purposes where cybercriminals find deepfakes effective. These are:
- Election manipulation: Cybercriminals create fake videos of world leaders and politicians. They manipulate the voice and video of the person with an agenda not intended by the original person. That raises an alarming concern, which ultimately affects and exploits elections. Barack Obama and Donald Trump‘s videos are some examples of how deepfakes are provoking. Analysts are worried that the upcoming elections across various countries will be impacted because of deepfakes.
- Celebrity Pornography: Another looming threat that is surfacing online is the fake pornographic videos of celebrities. Cybercriminals take the video footage of celebrities from movie scenes and ads. Because of excessive video data shot from different angles, it becomes easy for adversaries to create nonconsensual pornographic videos. Such videos account for up to 96% of deepfakes o on the internet. These video clips generally target celebrities. Deepfake technology also helps cybercriminals create fraud and fake instances of revenge porn.
- Automated Disinformation Attacks: Another way deepfakes impact organizations and individuals is by spreading disinformation. Disinformation attacks include conspiracy theories, incorrect opinions, fake political views, delivering unnecessary agendas, etc. Deepfake videos often create hoaxes and convincing video footage that compel individuals to believe in them. Such disinformation attacks distort the harmony of social media and other online portals.
- Social Engineering: Various social engineering scams and attacks – like calling someone with a fake voice, sending a counterfeit video clip of a trusted agent, etc., have accelerated with the advent of AI-based deepfakes. For example, a deepfake video tricked the CEO of a U.K. energy firm into believing that he was talking to one of the top executives of the firm’s parent company. Such deepfake videos can help cybercriminals extract sensitive information about any victim company or individual.
Other advanced threats like biometric authentication With voice recognition systems can get compromised with high-quality deepfake audio. Cybercriminal groups using ransomware can perform deepfake-based extortion to get the ransom.
Preventive Measures and Spotting Deepfakes
In this era of generative AI, preventing someone’s or an organization’s reputation is crucial. Here are some preventive measures and spotting techniques enterprises and individuals can carry out to identify and control deepfake crimes.
Identification techniques:
- In deepfake videos, you can notice unnatural eye movements.
- Today’s deepfake videos also have fewer blinking of the eye. Regular blinking of eyes is still a challenge with generative deepfake AI videos.
- Unnatural body shapes and facial expressions also give you a sign of the fact that the video is a fake AI-generative one.
- Abnormal skin colour and inconsistent facial positions are some red flags or indicators that the video is deepfaked.
Preventive measures:
- Advanced AI-detection tools can help automate the detection and monitoring of deepfake videos.
- To combat deepfakes, especially those that surface on social media – social media apps can enforce an immediate ban on accounts that release deepfakes.
- Enterprises can train, provide awareness, and prepare employees to identify deepfake video footage.
- Every enterprise with generative AI for video creation must initiate guardrails. It will define which groups within the organization can use generative AI and deepfake technologies and for what purposes.
Conclusion
We hope this article has given a crisp idea of deepfake videos and how cybercriminals can use them in cybercrimes. To tackle such cybercrimes, researchers are developing AI-powered deepfake detection technologies. But their development speed is not as fast as fraudsters forging them with devious uses. Therefore, individuals and enterprises should keep themselves aware and knowledgeable. It will help prevent them from becoming the victim and identify such threats.
In the ongoing battle against deepfake-related cybercrimes, VE3’s innovative cybersecurity solutions can play a pivotal role. We stand at the forefront of cybersecurity, providing cutting-edge AI-driven solutions specifically designed to detect and combat deepfake threats. By leveraging advanced algorithms and machine learning, we empower individuals and enterprises to fortify their defenses against the evolving landscape of cyber threats. To know more, explore our innovative digital solutions or contact us directly.
