Imagine returning home tired after a long and hard day to a phone call from your friend or relative asking you for money. Have you ever thought if it is real or fake? There are scammers around who are using voice deepfake programs to mimic anyone and are asking out for money. Not one, but there are multiple complaints about this issue and people are actually facing problems because of it. The scammers are doing this without leaving any traces behind. Many of them are so clean in mimicking that people believe whatever they are hearing is very genuine.
What is Voice Deepfake?
A voice deepfake is an artificial audio recording specially created using advanced machine learning techniques, such as deep learning algorithms, that can mimic someone else’s voice to a high degree of accuracy. The term “deepfake” is derived from the use of deep neural networks to manipulate or create digital media, in this case, voice recordings.
Voice deepfakes can be used to impersonate individuals, making them say things they did not say or making it appear as though they said something in a different tone or context. This technology has raised alerts about its potential to be used for malicious purposes, such as spreading fake information, defaming individuals, or impersonating someone’s identity. On the positive side, voice deepfakes can also have practical applications, such as in speech synthesis for people who have lost their voice or have difficulty speaking. Overall, the technology has both positive and negative implications and it is important to be aware of its potential uses and misuse. It can be used for good and bad purposes as well. But, mainly there is the only news that evil minds are using it for fraud purposes.
There are several ways in which someone can use voice-deepfake technology to scam others. Here are a few examples:
1. Impersonation of authority figures
Scammers can use voice deepfake technology to mimic the voice of someone in a position of authority, such as a CEO, government official, or law enforcement officer. They can then use this fake voice to convince their target to take some action that benefits the scammer, such as providing personal information or transferring money.
2. Social engineering
Scammers can use voice deepfake technology for creating fake recordings of your near ones, making it sound like they are distressed or in a need of urgent help. The scammer can then use this fake recording to convince the target to transfer money or take some other action to help the person in distress.
3. Spoofing phone numbers
Scammers can use voice deepfake technology to mimic the voice of a target’s family member or friend, and then use spoofing techniques to make it look like the call is coming from that person’s phone number. The scammer can then use this fake voice to trick the target into providing personal information or sending money.
4. Business scams
Scammers might use voice deepfake technology to impersonate a company representative, such as a customer service agent or a financial advisor. They can then use this fake voice to trick customers into providing sensitive information or making fraudulent transactions.
Overall, voice deepfake technology can be used to create convincing scams that trick people into taking actions that benefit the scammer. It is important to be cautious and verify the authenticity of any requests or phone calls that seem suspicious.
How to avoid getting scammed by Voice Deepfake scammers?
Here are some tips to help you avoid getting scammed by voice deepfake scammers:
1. Be cautious of unsolicited phone calls
If you receive a phone call from an unknown number, be cautious of the information that you provide. Scammers may use voice deepfake technology to impersonate someone you know or a company representative, so it is important to verify the authenticity of the caller and their request before providing any personal information or money.
2. Verify the caller’s identity
If the caller claims to be a company representative or someone you know, ask for their name, department, and phone number, and then verify their identity with the company or person in question. Do not rely solely on the information provided by the caller.
3. Do not provide personal information
Be cautious of providing any personal information, such as your social security number, bank account details, or credit card information, to a caller you do not know or trust.
4. Hang up and call back
If you receive a suspicious phone call, hang up and call back using a phone number that you know is legitimate. This will help you verify the authenticity of the caller and their request.
5. Use two-factor authentication
Two-factor authentication is a security feature that requires you to provide two forms of identification before accessing your account. This can help protect your accounts from unauthorized access, even if a scammer has your personal information.
6. Use anti-spoofing tools
Some phone companies and mobile apps offer anti-spoofing tools that can help detect and block calls from spoofed phone numbers.
It is important to be cautious and verify the authenticity of any phone calls or requests that seem suspicious. If you are unsure, it is better to err on the side of caution and not provide any personal information or money.
The case reported of voice deepfakes is serious and also got viral
The CEO of an unnamed UK-based energy firm claims that he was on the phone with his boss, the chief executive of firm’s the German parent company when he followed the orders to immediately transfer €220,000 (approx. $243,000) to the bank account of a Hungarian supplier. In fact, the voice belonged to a scammer using AI voice technology to rob the German chief executive. Rüdiger Kirsch of Euler Hermes Group SA, the firm’s insurance company, shared the information with WSJ. He explained that the CEO recognized the subtle German accent in his boss’s voice, and moreover that it carried the man’s “melody.”
No suspects have been identified, and little is known about what software they used or how they gathered the voice data necessary to spoof the German executive—but this case reveals one of the many possible ways machine learning can be weaponized.
