Since the time of 2015, deepfake technology has risen due to knowledge of ai tools and machine learning. The use of deepfake scams has become more frequent and more sophisticated due to the acceleration technology of AI tools. This is also giving rise to several fraudulent activities.
These new deepfake technologies are so dangerous that they allow scammers to add anyone in the video or the audio, audio can also be used to make such fake things. This is troubling for many people that scammers are using such technology to trap innocent people or even those who are influential. but if the victims have software to detect or stop the deepfake then it can be spotted. With the use of AI tools, they can pose individuals in video calls like Skype, zoom, or other apps. This can be hard to spot.
Wall Street has published an article revealing how deep fake AI audio trapped the CEO of uk UK-based energy firm in fraud of 220,000 euros. He was faked call by the scammer who used ai voice to detract the ceo.
Some deepfake software is very powerful in that it takes only 10 seconds to a minute to replicate the voice of the person who is talking; it replicates the various speech patterns, emotions, accents and the subject of the speech. This can be very hard to distinguish from the voice of the real person who is talking. It will even pause for the natural inflexion, letters and voice pitch. Which makes the perfect replica of what cannot be recognized.
The best example of this is, according to a New York Times article, a month ago caller posed and replicated as former Ukraine foreign minister Dmytro Kuleba in a video conference call with Senator Benjamin L. Cardin, the chairman of the foreign relations committee.
Although there was no evidence of any fraudulence activity, it is proved that some actors also manipulate key political leaders to influence certain outcomes of political elections or high-stakes foreign policy.
While digital arrest incidents have occurred globally, scams involving deepfakes are particularly widespread in India, according to Subrahmanian, a professor at Northwestern University. This is largely due to a lack of awareness about deepfake technology in the country. Subrahmanian also noted that a large portion of India’s population relies heavily on mobile phones, often trusting them as a source of reliable information. “When they receive a call like this, they don’t immediately question its authenticity,” he explained.
He further pointed out that India’s telecommunications sector has not prioritized cybersecurity adequately.
How can this be prevented?
Most deepfake software is created using AI models known as generative adversarial networks (GANs), which often leave behind distinct “artifacts” in the manipulated content. Deepfake detection systems can identify these artifacts, particularly in audio, and flag the fake material. As deepfake technology advances, detection systems will need to evolve alongside it to keep pace with these innovations.
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