In 2002, a Japanese researcher named Tsutomu Matsumoto demonstrated how simple methods could trick a fingerprint sensor. He used a Gummy Bear candy to create a copy of a fingerprint obtained from a glass surface.
His handmade fake fingerprint successfully fooled the sensor in 4 out of 5 attempts, highlighting vulnerabilities in biometric security systems.
Let’s see: when these software tools are cleverly combined with deepfake and other plugins, they can generate all the confidential data required to circumvent identity verification which makes any internet user vulnerable to identity theft and fraud.
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What’s even more alarming is that the attacker may not even be directly connected to you. They can simply feed photos and videos from your social media accounts into these software tools to produce more realistic images and videos for use in live detection and identification.
What is the deep fake effect on identity verification?
As of April 2023, one-third of all businesses reported experiencing video and audio deepfake attacks. Latin America also experienced a 410% surge in deepfake usage for identity fraud and globally, there has been a 10X increase of deepfake use between 2022 and 2023.
The simple truth is that deepfakes and generative AI technology have made all identity verification models vulnerable to attack, it has given rise to multiple numbers of unreal people, fake account access, impersonation, identity theft, scams, and fraud.
Methods hackers use to by-pass identity verification
Spoofing
The use of spoofing to deceive users and perpetrate cybercrimes has evolved beyond simple tactics like altering letters in emails or website addresses. Now, it encompasses sophisticated techniques such as manipulating human faces, cloning voices, and even passing live detection with realistic video gestures.
For companies prioritizing security, especially to comply with AML laws, it’s crucial to grasp how these methods are employed by malicious actors.
Using images from the internet
To verify the authenticity of a user, hackers can readily gather images of their victims from social media or other sources. In some cases, they employ photo editing software to manipulate these images to suit their needs. For example, in authentication processes that require users to hold up an ID card or another form of legal identification, malicious actors can easily obtain photos from Facebook and swap faces through softwares like Deepswap, without the victim’s knowledge.
High-end edited/ pre-recorded videos
Randomly, any active social media user might unwittingly fulfill the basic requirements needed for simple verification technology. Actions like smiling or closing and opening one’s eyes can be used to deceive facial recognition systems that lack sophistication. Although many facial recognition systems require live videos, hackers can resort to unethical methods, such as using pre-recorded videos, to bypass these systems.
Akool deepfake can be used for video face swap and also add up facial gestures which illicit users can use to compromise identity systems.
The use of synthetic masks: This is a common method of spoofing employed by attackers, and it often requires double checks or highly trained models to effectively detect.
Machine learning models are typically trained on high-quality images of faces to determine whether the user’s face is genuine or not. However, attackers can exploit factors such as poor lighting conditions to deceive the system into identifying a synthetic mask as the legitimate owner of the account.
Models with limited training data may also not be sufficiently trained to accurately differentiate between real and synthetic faces.
Deep fakes
This is one of the fastest methods of identity theft, as attackers only need minute details to gather all the information necessary to validate their victim’s identity. In 2024, generative AI is at the forefront of advancing businesses into new horizons. However, it’s also a fact that hackers and fraudsters are actively seeking ways to leverage these cutting-edge technologies for malicious purposes.
This underscores the importance for companies to heavily invest in security technologies and consistently update their tech infrastructure to avoid falling victim to such attacks.
Safety measures against deepfakes
The world is already experiencing a tenfold increase in deepfake usage, signaling that any company, regardless of size, could be the next target of unidentifiable or unwanted users. For companies adhering to KYC and AML regulations, staying ahead of the game is essential. Here are a few tips:
Robust identity document checks
Given that any legal document can be easily forged, it’s imperative to conduct thorough scrutiny of each document submitted. To combat the prevalence of deepfake usage, companies can consider implementing dedicated training models integrated into their identity verification processes.
Detailed KYC
KYC checks shouldn’t stop at ID cards. If you’re a fintech product, consider mapping out strategic questions and approaches that delve deeper into verifying user identities. This gives a prior understanding of what the customer’s financial behavior should look like, also it will effectively reveal lapses and inconsistent details.
Ongoing monitoring of users
Every illicit user has an objective and a motive behind their actions, emphasizing the need for consistent monitoring. This means that every behavior is logged, and in cases of uncertainty, approaches can be developed to counteract these behaviors. For example, Twitter, a social media platform notorious for bot activity, has seen various measures implemented to combat bots, such as the Arkose challenge that suddenly appears during usage.
Conclusion
Regulations are certainly being implemented to ensure the safe use of these technologies. However, the harsh reality is that bad actors will continue to find ways to exploit vulnerabilities. At this point, everyone is prone to being vulnerable, and the best course of action is to take extra precautionary steps.
Brands can also start employing third-party identity verification companies equipped with counter AI deployment tools and additional scrutiny features to continuously safeguard their brands.
