As per Gartner’s alarming predictions, by 2026, 30% of enterprises may deem identity verification and authentication solutions unreliable due to AI-generated deepfakes. This underscores the importance of staying informed and taking proactive measures for our audience.
In a recent move to combat the increasing use of deepfakes and identity theft, Inter Miami superstar and one of the most celebrated football celebrities, Lionel Messi, has retained the rights to his audio and facial features and has only allowed PepsiCo to use his deepfake video for a recent Lays commercial. But what are deepfakes, and what’s all this fuss about?
Deepfakes are audio, videos, and images generated artificially using deep learning algorithms. This technology is getting abused often, which is a massive concern for technology leaders, enthusiasts, and celebrities globally. Deepfakes can also deem facial recognition ineffective in the coming years. These can be so convincing that it is hard to tell they are not real. So, as a business owner, technology leader, or an individual concerned about their privacy, should you be concerned about deepfakes?
In this write-up, our experts, who also provide brilliant Android app development services, will explore the impact of AI deepfakes and facial biometrics on human lives and how it may cause various security issues in the near future.
The Rise of DeepFake Technology
Deepfakes were initially developed to create synthetic data. They were then used for entertainment purposes, where famous celebrities’ and politicians’ videos and audio were cloned and manipulated. While this might seen entertaining and futuristic, deepfakes started causing identity theft, which is a severe offense.
Deepfake technology can leverage artificial intelligence (AI) to create hyper-realistic media. By using deep learning algorithms, deepfakes can create and alter images, videos, and other media to present false realities. This technology can showcase impressive mimicking of someone’s face and voice. It can also pose significant ethical, social, and security challenges.
One of the most critical advancements in deepfake technology is manipulating videos and audio in real time. This has opened the door to live deepfake applications where individuals can appear as others during video calls or live streams. The implementations of this advanced technology extend to a plethora of use cases, from entertainment to politics, where the potential for misuse is a growing concern.
- Deepfake creation involves training two neural networks, an encoder and a decoder.
- The encoder learns to recognize a person’s facial expressions, while the decoder generates a new face with similar expressions.
- Deepfakes can seamlessly pull the features of one person over an existing recording or video.
Impact on Facial Biometric Authentication
Facial recognition is one of the most commonly used forms of biometric identification. It is considered and used as a standalone biometric data security system. Facial recognition prompts customers to capture images using a smartphone or web camera. The systems can automatically authenticate the user’s identity by analyzing the unique facial features.
In today’s tech-first world, facial biometric technology can be equipped and used in smartphones. This can allow users to access their phones more easily without providing any credentials. Many companies are opting for iOS and Android app development services to create apps secured by robust facial biometric authentication.
Anything that can have transformative power and remove friction from the identity verification process is a plus for governments across nations trying to digitalize the onboarding journey.
As per the research, facial recognition technology is more trustworthy and secure than other biometric authentication methods. This is because it’s one of the most efficient and secure authentication methods to verify the users’ identities with the highest level of accuracy.
Here are some of the most alarming security and disinformation attacks caused by the unethical use of deepfakes:
- Deepfakes can spread automated disinformation attacks. For instance, there was a deepfake video impersonating Meta founder Mark Zuckerberg claiming to have “total control of billions of people’s data.”
- Deepfake technology can be used to create new identities or steal the identities of real people. Attackers use it to create fake accounts and purchase products by pretending to be that person.
- Cybercriminals use deepfake technology for various fraudulent activities. This can threaten and destabilize organizations. Suppose an attacker could impersonate a famous businessman through a deepfake video and admit to some criminal activity, such as financial crimes, or making false claims.This could have a significant impact on the business’s brand reputation.
Security Implications of Deepfake in Facial Recognition
While deepfakes have several challenges, facial recognition technology offers valuable security benefits. Here are some potential solutions that can strengthen facial recognition systems and mitigate the deepfake threat.
- Multi-factor Authentication (MFA): Relying only on facial recognition can be challenging. Implementing multi-factor authentication and extra security layers requires users to provide a second verification factor, such as a fingerprint scan, one-time code, or security question, to gain access.
- Live Detection: This authentication method goes beyond facial recognition. Checks including eye movement detection, analyzing blood flow patterns, or prompting users to make specific movements help systems distinguish between a real person or a deepfake model.
- Continuous Improvement of Facial Recognition Algorithms: Most developers are constantly refining facial recognition algorithms to better detect inconsistencies and anomalies in deepfakes. Training the systems on a wide range of data sets, including manipulated faces, can enhance their ability to identify deepfakes.
Building Resilience Against Emerging Deepfake Threats
Deepfakes call for a much-needed change in the traditional facial recognition protocols followed by most companies. They must strengthen their security protocols and implement multi-factor authentication and rigorous facial recognition algorithms.
While deepfakes have multiple positive use cases, they do reflect our society’s relationship with truth, ethics, and reality in the digital world. Understanding the multifaceted nature of deepfakes is crucial, not only for their technological implications but also for their broader impact on society, law, and individual rights.
Cubix helps various companies, from government organizations to law firms, by providing robust AI facial recognition solutions. We strengthen your security infrastructure and mitigate risks by harnessing artificial intelligence, machine learning algorithms, and biometric solutions. Our team of highly skilled developers boasts over 15 years of experience of providing AI-powered iOS and Android app development services.
Contact us today and get the solution you’re looking for!
