Artificial IntelligenceCybersecurityData PrivacyDigitalRisk ManagementTechnology

Deepfake Impersonations: Beware the Sound of Fraud!

People are falling for spoofed voice hackers

For example, in March 2019, criminals used artificial intelligence-based software to impersonate a chief executive’s voice and demand a fraudulent transfer of €220,000 ($243,000).

This scam is sometimes referred to as “vishing,” or voice phishing.

In another case, cybercriminals cloned the voice of a company director in the U.A.E. to steal as much as $35 million in a huge and complex bank fraud.

This video lays out how vishing could be used to steal personal information and extort money from unsuspecting victims:

Deepfake scamming, however, is not limited to voice only.

Deepfake Video Fraud

Also around the same period, deepfake videos were beginning to be used in blackmail and extortion attempts.

In these cases, criminals would create a video that appeared to show an individual (often a public figure or corporate executive) behaving inappropriately or illegally, and then demand payment in exchange for not releasing the video.

These are just some examples of how criminals are using AI voice technology to scam people.

This video is an example of a video and voice generated by AI where Ex president Barack Obama warns about AI impersonation:

How can you combat these scams?

Detecting deepfakes and impersonation scams can be challenging due to the advancement of technology.

However, there are several techniques and approaches that can be used to help identify and combat such scams. Here are some commonly employed methods:

1. Facial analysis: Advanced facial recognition algorithms can be used to analyze facial features and identify anomalies in the generated image or video. This includes examining inconsistencies in facial expressions, eye movements, blinking patterns, and lip-syncing.

2. Reverse image and video search: Conducting reverse image or video searches can help determine if the content has been used elsewhere on the internet. This can unveil instances of the same person in different contexts or reveal whether the media has been manipulated.

3. Metadata analysis: Examining metadata associated with the image or video can provide valuable information. Details such as creation date, device information, and editing history can be helpful in assessing the authenticity of the media.

4. Source verification: Verifying the source of the content is crucial. Authenticating the identity of the sender, cross-checking with known sources e.g. ask for a text confirmation, or obtaining information from trusted platforms can assist in determining the legitimacy of the media.

5. Forensic analysis: Digital forensics techniques can be employed to analyze deepfake videos or images. This involves examining artifacts and inconsistencies in the manipulated content, such as pixel-level analysis, noise patterns, and edge detection.

6. Multi-modal analysis: Combining various modalities, such as audio, video, and textual information, can enhance the detection process. Analyzing inconsistencies between these modalities can help identify discrepancies and potential deepfake or impersonation attempts.

7. Machine learning algorithms: Developing and training machine learning models specifically designed to detect deepfakes is an ongoing area of research. These models learn patterns and characteristics of manipulated media to distinguish them from genuine content.

8. Human expertise: In certain cases, human expertise and judgment can play a crucial role. Experienced professionals, such as forensic analysts or content reviewers, can often identify subtle cues and anomalies that automated systems may miss.

It is important to note that the field of deepfake detection and social engineering scams are evolving, and new techniques are continually being developed.

Combating deepfake and impersonation scams requires a multi-faceted approach that combines technical solutions, collaborative efforts, and user education to stay ahead of the evolving threat landscape.

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Carsten Krause

As the CDO of The CDO TIMES I am dedicated delivering actionable insights to our readers, explore current and future trends that are relevant to leaders and organizations undertaking digital transformation efforts. Besides writing about these topics we also help organizations make sense of all of the puzzle pieces and deliver actionable roadmaps and capabilities to stay future proof leveraging technology. Contact us at: to get in touch.

One thought on “Deepfake Impersonations: Beware the Sound of Fraud!

  • #4 Source verification is really the most approachable solution until better detection tools are developed. At least when it comes to vishing. I heard a story about a grandmother getting an AI voice fake call asking her to help what sounded like her desperate grandson. He needs money wired to a foreign country immediately to avoid some kind of peril.

    The only way a grandmother could avoid this trap is to call her grandson and confirm if he actually was out of country, and/or in trouble. We need to educate everyone, confirm the source before you send money anywhere.

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