Thought Leadership
Everyone has heard or read about them, and some people may even have fallen for them: Deepfakes are increasingly blurring the boundaries between reality and fiction and pose a significant threat to the reliability of our digital identity.
These highly sophisticated and often deceptively real-looking manipulations of image and sound material are becoming increasingly important, as they can have serious consequences on an individual, economic and social level.
The different forms of deepfakes
Deepfakes are synthetically produced media that are created with the help of (generative) artificial intelligence and can change existing images, videos or audio files or create them from scratch. The term “deepfake” is derived from the AI technology “deep learning” and the English word “fake” (forgery, deception). There are many possible applications for deepfakes. However, they are most frequently misused to spread false information or facilitate identity fraud.
1. image manipulation
One of the most prominent examples of deepfakes are manipulated images. One recent incident has made particularly big waves in the media: the deepfake scandal surrounding Taylor Swift. To create such fakes, generative AI models are used to create realistic-looking illusions that never actually happened. Websites such as “thispersondoesnotexist.com” demonstrate how easy it has become to generate fictitious faces that are almost indistinguishable from real people. In addition to faces, scenes and objects can also be altered to appear deceptively real, which has already led to serious misunderstandings in the past.
Examples of image manipulation:
- Fake images of celebrities: These are widespread and aim to damage the public image or create false narratives.
- Manipulated evidence photos: In legal and journalistic contexts, manipulated photos can be used to spread false information.
- Deception on social media: Deepfakes can be used to create fake profiles or posts that are often difficult to distinguish from the real thing.
2. sound manipulation
In addition to the visual aspects, deepfakes in the audio sector also pose a significant threat. With the help of AI technologies, voices can be imitated so perfectly that they can even deceive friends and family members – a dangerous tool for fraudsters, who already use the classic grandchild trick or shock calls to steal money by feigning distress under time pressure. This AI-supported form of manipulation takes the familiar scams to a new level.
Examples of sound manipulation:
- Text-to-speech with voice copying: Modern AI models can generate authentic-sounding voice recordings that are indistinguishable from real ones. In most cases, only short original recordings (just a few seconds are enough!) are needed to imitate any target voice.
- Speech-to-speech (voice cloning): This technology makes it possible to clone a person’s voice and use it in any context – particularly dangerous in CEO fraud, where fraudsters use fake instructions from supposed executives to initiate urgent bank transfers.
- Fake voicemail: Criminals use fake voicemails to deceive company employees and obtain confidential information or manipulate financial transactions.
3. fake documents and fraud-as-a-service
In addition to the manipulation of image and audio material, forged documents and “fraud-as-a-service” models are also gaining in importance. These techniques aim to forge digital identities and thus gain unauthorized access to sensitive systems.
Forged documents – the tools for this are usually available on the darknet
Thanks to advanced AI technologies, official documents such as driving licenses, passports and identity cards can now be made to look deceptively real. These forgeries are so professionally produced that they can be used to circumvent KYC (Know Your Customer) procedures or otherwise gain unauthorized access. In most cases, cyber criminals make use of the wide range of services available on the darknet to acquire the necessary tools for their fraud campaign as a “fraud-as-a-service” service.
Fraud-as-a-Service is an increasingly persistent trend in the world of cybercrime. This type of service allows criminals to purchase forged documents for a fee, which can be used to circumvent security protocols in various areas. The possible uses of such forged documents are diverse: for example, they can be used in cryptocurrency exchanges to bypass KYC verification. They are also used in banking systems and online stores to facilitate fraudulent activities.
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The entry point: digital identity
Digital identity is often the first point of contact and the biggest obstacle for attackers trying to penetrate an IT ecosystem. Deepfakes make this step much easier by enabling the careful curation of credible identities that can be used to easily bypass security measures. Once a company or individual’s digital identity is compromised, attackers then have free access to sensitive data and systems.
Examples of the misuse of digital identities:
- Social engineering: Attackers use deepfakes to imitate trustworthy sources and deceive employees or customers.
- Access to protected systems: Attackers can gain access to internal systems and networks using forged proof of identity.
- Spreading disinformation: Deepfakes can be used to spread false information in order to influence public opinion or market movements.
Protective measures against deepfakes
With the growing threat of deepfakes, it is crucial to protect yourself effectively. Here are some approaches that can help to effectively protect against these threats:
Education and awareness-raising
To raise awareness of the risks of deepfakes, regular training for employees is essential. These trainings help to better understand the dangers of deepfakes and offer practical instructions on how to recognize these manipulations and react correctly. In addition to internal training, public information campaigns should also be carried out. These campaigns should inform the general public about the potential dangers of deepfakes and what detection features can be used to identify AI counterfeits.
Technological solutions
Deepfake detection software is one of the most effective weapons in the fight against AI-generated deception attempts. These advanced software solutions are based on algorithms that can detect specific AI recognition features in images and sound and thus help to reliably identify fake content. In addition, stronger authentication procedures should be implemented to protect access to sensitive data. Methods such as two-factor authentication (2FA) and biometric security measures create additional security levels and significantly increase protection against unauthorized access.
Procedures and guidelines
Process adjustments are necessary to increase the effectiveness of security measures. The introduction of verification procedures, such as interactive challenges or code words, can be a major obstacle to the use of deepfakes. In addition, security policies and procedures should be regularly reviewed to ensure that they address current threats and that appropriate adjustments are made to address emerging vulnerabilities (so-called zero-day vulnerabilities). Continuous reviews are crucial to keep security systems up to date and ensure protection against potential attacks.
Only those who have deepfakes on their radar can react to them correctly
Today, no one can doubt that deepfakes pose a significant threat to the global digital ecosystem and can undermine trust in media, communication and even the credibility of identities. Companies and individuals need to be aware of the potential risks in order to prepare appropriately and respond immediately. Modern fraud detection solutions are a powerful tool, as they themselves use artificial intelligence and machine learning to detect suspicious activity and anomalies that could indicate deepfakes. These systems provide a valuable and reliable line of defense by continuously learning and adapting to new attack patterns, perfecting their effectiveness in the fight against the ever-evolving deepfake threat landscape.
The fight against deepfakes is a technological arms race: while counterfeits are becoming ever more perfect, detection systems have to keep up. But technical solutions alone are not enough. The key lies in a holistic approach: advanced AI detection, trained employees and a deep understanding of attacker patterns. The challenge is complex, but the solution is tangible – through close cooperation between fraud experts, security authorities and educated users. Only together can we preserve digital authenticity, even in times of AI-supported deepfakes.
