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28/06/24
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Bitget Report Highlights Rise in Crypto Scams Involving Deep Fakes
On June 27, Bitget Research’s report revealed that fake tricks and scams may bring about cryptocurrency losses worth more than $25bn this year, representing over two hundred percent of the losses in 2023.
According to the report, the number of deep fakes globally increased by more than 245 percent this year, based on a previous research data from Sumsub. Most deep fakes discovered in Q1 2024 were in China, Germany, Ukraine, the United States, Vietnam and the UK, while the cryptocurrency industry recorded a 217 percent increase relative to the same quarter last year.
The increase in deep fakes within the crypto industry prompted cryptocurrency losses valued at $6.3bn in Q1 2024. Bitget noted that the losses are expected to rise to $10 billion per quarter by next year.
Fraudsters employing deep fakes have been using almost the same tactics over the years. The majority of losses due to deep fakes within the crypto space happen as fake projects, phishing attacks as well as Ponzi schemes. This involves using deep fake tech to earn crypto investors’ trust.
This method was used in over 50 percent of all cryptocurrency losses related to deep fakes over the past two years. “By impersonating influential figures, these schemes create the illusion of credibility and substantial project capitalization, thereby receiving large investments from victims without thorough due diligence,” said Bitget Research.
Fraudsters using deep fakes often generate videos of MicroStrategy executive chairman Michael Saylor. Saylor’s team removes about 80 AI-generated fake videos of him every day, according to him six months ago. These fake videos often promote some kind of scam related to Bitcoin.
Bad actors also use deep fakes for other malicious schemes, and these include cyber extortion, identity and impersonation fraud, and market manipulation. According to Bitget’s prediction, the share of cryptocurrency crimes involving deep fakes may hit 70 percent in two years if there are no effective measures.
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