In the age of technology, scams and frauds have taken a more sophisticated form with the advent of deepfake technology. Deepfake video calls and robocalls are becoming increasingly common, allowing scammers to impersonate someone else, be it a celebrity, friend, or even a trusted authority figure. The goal is to trick unsuspecting victims into handing over personal information or money. This type of scam is particularly dangerous because it's nearly impossible to detect and leaves victims feeling extremely vulnerable and confused.
Educating people and staying informed about these deceptive practices is crucial. In this article, we'll explore the rise of deepfake technology and what you need to know to protect yourself from these dangerous scams.
Deepfakes are a type of technology that allows people to manipulate video and audio, making it appear as though someone is saying or doing things they never actually did. This is achieved through artificial intelligence and machine learning algorithms that are trained to analyze and replicate a person's facial expressions, voice, and movements. The result is a highly realistic and convincing fake video that can be used for various purposes, both good and bad.
Scammers maliciously use deepfakes to fake video calls and impersonate someone else. A well-known example is the deepfake video created by Buzzfeed and Jordan Peele, in which Peele's face was superimposed onto former President Barack Obama's body, making it seem as though Obama was saying things he never actually said. See for yourself:
This highlights the potential dangers of deepfakes and how easily they can be used to manipulate and deceive people. With the proper software and knowledge, it's not hard to create fake videos of celebrities, friends, or even trusted authority figures. There's a good chance you've watched a deepfake video and not even known it. This makes deepfakes a concerning issue since phone scammers can use that same technology to create incredibly persuasive robocalls that react and respond to you. Even worse, with deepfake technology, scammers can easily replicate our speaking style and emotions from daily conversations.
Robocalls are pre-recorded phone calls that are automatically dialed to a large number of people. For years, scammers have used robocalls to impersonate government agencies, such as the IRS, to trick people into paying fake taxes or fines. While these scam robocalls have a gimmicky, robotic tone, some legitimate robocalls do, too. That's why people still fall for them every day.
Phone scammers have a history of applying clever tactics and new technology. One of the first known scams involved an impersonator and fake ransom, which managed to steal $20,000 back in 1888. Almost one hundred years later, autodialers allowed them to place calls at incredible volumes for cheap. Today, these types of scams are commonly referred to as "IRS robocalls" and continue to be a widespread problem.
Deepfake robocalls, on the other hand, take the impersonation aspect of these scams to a whole new level. With the ability to manipulate video and audio, deepfake technology allows scammers to create highly realistic fake video calls, making it even easier to impersonate someone. Unlike traditional robocalls, deepfake robocalls are more convincing but, at the same time, much harder to detect. The seriousness of this threat even increases when combined with "phone spoofing." "Spoofing" is another malicious technique in which scammers manipulate the caller ID information to make it appear as if the call is coming from a legitimate source. This makes it even harder for victims to detect the scam and increases their chances of being tricked.
This is the kind of tool phone scammers dream of. It makes it nearly impossible to discern whether a call is legitimate or a phishing scheme.
Deepfakes are manipulated videos or audio recordings that mimic someone's voice and appearance, making it appear as if they are saying or doing something they never actually did. Naturally, this technology has raised questions about whether it constitutes identity theft and when it becomes illegal.
While deepfakes are not always fraudulent, the intent behind their use determines whether they’re legal. However, the legal boundaries around deepfake technology and its use for identity theft are still largely undefined. Currently, there are few laws that explicitly address deepfakes and their impact on privacy and security. This is an evolving area of law, and as deepfake technology advances, we will likely see more legislation being introduced to address these issues.
In general, deepfakes can be considered fraudulent when they:
The specific crimes connected with deepfake technology include:
A criminal activity in which a deceased person's identity is stolen and used to gain access to financial accounts or services is called "ghost fraud." Fraudsters use deepfakes to impersonate the deceased person, making the crime more convincing. The stolen identity is then used to apply for credit cards, loans, and other financial products.
Also known as application fraud, this activity turns into a crime when criminals use stolen or fake identities to open new bank accounts. Since fraudsters can max out credit cards and take out loans that are never paid back, this crime often leads to severe financial damage.
Synthetic identity fraud is a complex form of fraud in which fraudsters use information from multiple people and fake data to create a non-existent "person." They then use the synthetic identity to apply for credit cards and loans or make large transactions.
Hiring fraud or recruitment fraud occurs when criminals offer a person a fake job through unsolicited emails, online recruitment websites, or text messages. These scams aim to gain access to personal information, conduct illegal activities, or solicit payments.
With this type of fraud, someone impersonates a deceased person or family member to claim specific benefits, such as life insurance, pension, or similar.
The "Institute for Internet & the Just Society" recommends that lawmakers and policymakers should address these challenges by creating laws and regulations that balance the potential benefits of deepfakes with the need to protect individuals and society. Some possible legal measures that could be taken include making it explicitly illegal to create and distribute deepfakes for malicious purposes, requiring deepfake creators to label their works, and setting up a system for individuals to seek redress if they have been harmed by deepfakes.
In the era of deepfakes and robocalls, it's becoming increasingly difficult to trust any phone call. Deepfakes enable scammers to impersonate someone else's voice, making it difficult to distinguish between a genuine call and a fake one. At the same time, robocalls have become a common way for scammers to reach a large number of people, using automated calls to deliver pre-recorded messages. With these technological advancements, it's not surprising that many people are feeling cautious and skeptical when it comes to answering phone calls.
As a result, educating people about how to spot and avoid these scams, such as by verifying the caller's identity, not giving out personal information, and reporting any suspicious activity to the authorities, is crucial. Additionally, technology companies and government agencies are working on developing solutions to detect deepfakes and block robocalls, but it's still an ongoing battle.
Until these solutions become more widespread, it's important to stay vigilant and approach all phone calls with caution. It may seem like a minor inconvenience, but these steps can help protect you from falling victim to phone scams.
In today's digital age, it can be difficult to tell if a video or audio recording is real or a deepfake. However, there are several ways to identify a deepfake and distinguish it from a real recording.
If you're unsure if an image or video is fake, look for these signs:
To determine if an audio file is a deepfake or not, check for the following:
Source: Homeland Security
An AI from tech company Baidu created a series of deepfakes using only a 3.7 seconds audio snippet from a real person. The ability to simulate a conversation like this was the missing piece in the phone scammer arsenal that already included neighbor spoofing. Soon, the combination of autodialers, neighbor spoofing, and deepfakes will open up a scammer's paradise.
It's now more imperative than ever that people remain vigilant and educate themselves on the latest tactics used by scammers.
Since Google and Apple dominate the smartphone market, one would hope they'd offer a solution to the increasing threat of deepfake calls. Both companies are working on specific features to fight back against spam and scam calls, but the danger coming from deepfake technology is tangible and creates a real challenge.
Google's Pixel phones have a "Call Screen" feature, which helps users determine the authenticity of incoming calls. It uses Google's artificial intelligence technology to transcribe the caller's voice in real-time, allowing the user to see a transcript of the call before answering. It does so by alerting the caller that you are using a screening service and that you'll get a copy of this conversation. The Google Assistant then asks the caller to state their name and reason for calling. If the transcription seems suspicious, the user can then flag the call as spam.
While this feature might seem convenient, especially for most spam calls and robocalls, it does have its flaws when it comes to deepfake calls. Deepfake technology, with machine learning that manufactures realistic voice responses, will still get to you (even if the initial interaction is transcribed through Google Assistant).
Oddly enough, the kind of machine learning and automation tools that power deepfakes is the same that Duplex, another of Google's AI software, uses to place human-sounding voice calls on your behalf, like booking restaurant reservations and hair appointments.
So far, iPhone users have had to fight spam calls without help from Apple. But the company has patented a system for screening spam calls using machine learning and audio analysis. This system aims to automatically identify and block calls from known spammers, and flag potential spam calls for manual review. The patent application describes how the system uses audio characteristics such as voice pitch and modulation, background noise, and the presence of a pre-recorded message to determine if a call is likely to be spam. The goal of the patent is to make it easier for users to identify and avoid unwanted and potentially dangerous calls and to help protect their privacy and security. However, it is important to note that the mere existence of a patent does not guarantee that Apple will ever implement this technology or that it will be successful in blocking all spam calls. At the same time, it doesn't state how Apple's patented system would fight the deepfake technology used in robocalls.
While both Google's Call Screening and Apple's patent aim to detect spam calls and robocalls, these solutions alone are not enough to ultimately combat deepfake technology. Deepfakes are rapidly advancing, and it may be challenging for call screening technology to keep up. In addition, deepfakes can still find their way through these screening methods if they are sophisticated enough. Therefore, it's important to remain vigilant and use multiple verification methods before accepting a call or trusting its content.
Since deepfakes are based on machine learning and automation technology, it only makes sense that detection tools use the same level of technology. In this case, it's machine learning and audio fingerprinting. "Audio fingerprinting" is a technology that could be the key to stopping deepfake robocalls. It creates a unique digital signature, called a "fingerprint," for each individual's voice. This fingerprint is created by analyzing various audio characteristics, such as spectral content, pitch, and rhythm. The fingerprint is then compared to a database of known audio recordings to determine if there's a match.
In the context of deepfake audio, audio fingerprinting can be used to determine if an audio recording has been manipulated or fabricated. This can be done by comparing the fingerprint of the deepfake audio with a reference recording of the person's original speech, such as a recording made before the deepfake was created. If the fingerprints don't match, this indicates that the audio has been altered and is likely a deepfake.
As you can see, audio fingerprinting can provide the necessary extra layer of protection against deepfake robocalls and other forms of telephone fraud. However, it is important to note that this is still a developing technology, and its effectiveness may vary depending on the quality of the deepfake and the accuracy of the voiceprint database.
Robocalls have become an increasing problem for many people, and it's not just about annoying telemarketing calls anymore. With the rise of deepfakes, it has become even more challenging to determine what's real and what's fake in phone calls. To stay ahead of these tactics, it's crucial to have a reliable solution that can protect you from these unwanted calls.
One such solution is using Robokiller.
Robokiller is the #1 robocall blocking app and the best solution to end your unwanted call problem. Besides protecting you from spam calls and robocalls through in-real-time caller identification, it even gets on the phone to fight unwanted callers for you with its hilarious Answer Bots.
RoboKiller was also one of the first spam call blockers to use audio fingerprinting technology and machine learning to identify spam calls, and it will continue to protect you once deepfake robocalls gain popularity.
