In 2026, AI Agent has officially entered the core business processes of enterprises. Yet, as AI becomes capable of executing sensitive operations on behalf of humans, a fatal question has emerged: how can we confirm that the person issuing the instructions is truly the one? Today, with deepfake fraud surging by 3000%, the traditional identity authentication system is facing unprecedented challenges.
I. Identity Security Crisis in the AI Era
1. Deepfake: The "Nuclear Weapon" of Identity Fraud
2023 saw an unprecedented identity security storm sweep the globe. According to the latest 2024 Identity Verification Threat Intelligence Report released by iProov, AI-based deepfake fraud has surged by 3000% year-on-year, injection attacks targeting mobile web applications have increased by 783%, and scams involving face swapping via virtual camera software have skyrocketed by 2665%.
This is not a scene from a science fiction movie. In early 2024, a financial staff member of a multinational corporation in Hong Kong held a detailed business discussion with the "company executives" during a video conference, and then transferred HK$200 million in accordance with their instructions. It was only afterwards that they discovered all the "executives" in the video were fake images generated by AI deepfake technology.
The 2025 report from the China Internet Finance Association shows that direct economic losses caused solely by deepfake-related identity fraud incidents have exceeded 1.8 billion yuan, and the total annual losses triggered by black-market fraud have soared to as much as 114.9 billion yuan.
2. Face Recognition: From the "Master Key" to a "Fragile Paper Shield"
At one time, face recognition was regarded as the "ultimate solution" in the field of biometric recognition. However, in the face of generative AI, this "master key" is losing its magic. A sobering new forecast from Gartner analysts states that by 2026, the ability of deepfake technology to generate realistic human images may cause 30% of enterprises to lose confidence in face biometric identity verification solutions. This means that face recognition systems, once considered "high-tech security solutions", may become virtually useless in the age of AI.
Traditional liveness detection methods for face recognition, such as eye blinking and head shaking, have proven fragile in the face of dynamic AI forgery. Attackers use deepfake facial videos to inject forged images directly into system data streams through virtual cameras, easily bypassing verification. iProov has tracked more than 120 tools available for real-time video face swapping, including many free and open-source solutions.
3. New Challenges in the AI Agent Era
2026 is known as the "first year of the AI-native economy". Gartner predicts that by 2026, more than 60% of new enterprise applications will embed AI capabilities, and AI Agent is penetrating all aspects of enterprise operations: financial approval, contract signing, data access, system operation, and more.
As AI Agent becomes able to execute sensitive operations on behalf of humans, the importance of identity verification has been elevated to an unprecedented level. Once an attacker successfully impersonates an authorized person, the AI Agent will faithfully execute all "legitimate" instructions—including high-risk operations such as fund transfers, data deletion, and permission modification.
The traditional model of "verify once, trust always" is obsolete. The AI era demands a continuous, highly reliable identity confirmation mechanism—and this is where iris recognition technology finds its rightful place.
II. Panoramic Comparison of Biometric Recognition Technologies
Before exploring solutions, we need to understand the characteristic differences of current mainstream biometric recognition technologies. The core value of biometric recognition lies in irreplaceability—proving "you are you" through unique physiological features.
| Panoramic Comparison of Biometric Recognition Technologies |
| Technology Type |
Number of Feature Points |
Error Rate |
Anti-Counterfeiting Capability |
Privacy |
| Iris Recognition |
200+ |
1/10,000,000 |
Extremely High |
Active Collection |
| Face Recognition |
68-128 |
1/10,000 |
Relatively Low |
Passive Collection Possible |
| Fingerprint Recognition |
40-100 |
1/50,000 |
Medium |
Contact Collection |
| Voiceprint Recognition |
20-40 |
1/1,000 |
Low |
Easily Recordable |
As is clearly shown in the table, iris recognition leads the pack in three core dimensions: feature richness, recognition accuracy, and anti-counterfeiting capability. More importantly, iris recognition requires active user cooperation for data collection, fundamentally avoiding the privacy risks caused by the "passive collection" of face recognition.
III. Iris Recognition: Why It Is the Optimal Solution for the AI Era
1. Innate "Anti-Counterfeiting Genes"
The iris is an annular area between the pupil and sclera of the human eye, containing a wealth of textured structures: spots, filaments, coronas, stripes, crypts, and more. These features form during fetal development, remain unchanged for a lifetime, and no two irises in the world are identical.
Iris recognition technology can capture 266 feature points, several times that of face recognition. This information density allows the False Acceptance Rate (FAR) of iris recognition to be as low as 1 in 10 million, far surpassing other biometric recognition technologies.
More crucially, as part of the human internal organs, the iris is protected by structures such as the eyelids and cornea, making it almost impossible to copy or forge without the user's knowledge. Current tests in academia and industry have shown that no method—including video recording, photos, artificial eyes, or printed contact lenses—can breach mature iris recognition algorithms.
2. "Immunity Characteristics" for the AI Era
The core reason why deepfake technology can breach face recognition is that the human face is an externally visible organ. Attackers can obtain a large amount of facial data of targets through social media, surveillance footage, and other channels, then use AI to generate highly realistic reconstructions.
The iris is entirely different. Iris texture is almost invisible in daily life, and even high-definition photos cannot capture enough details for forgery. Coupled with the near-infrared light sources and liveness detection technology equipped in iris recognition systems, any form of counterfeit attack can be effectively identified and rejected.
This means that no matter how advanced AI technology becomes, attackers lack the training data to generate forgeries that can pass iris verification. This is the innate "immunity characteristic" of iris recognition in the AI era.
3. Dual Protection for Privacy and Security
The revised version of the Cyber Security Law, which came into force on January 1, 2026, explicitly classifies biometric data as "sensitive personal information" and imposes more stringent compliance requirements on its collection, storage, and use.
Iris recognition has unique advantages in terms of compliance:
● Collection requires active user cooperation (in contrast to the "passive collection" of face recognition);
● Iris templates cannot be reversely reconstructed into original images (in line with the compliance requirement of "data available but invisible");
● Edge-side processing and local storage (reducing the risk of data leakage).
IV. Homsh's Solutions
As a leading enterprise in China's iris recognition field, Homsh focuses on the independent R&D of core algorithms and hardware devices, providing enterprises with full-stack solutions from chips to systems.
1. Qianxin Series: The "Core" Choice for Enterprise-Grade Security
The Qianxin Series of iris recognition chips is equipped with the self-developed PhaseIris 3.0 algorithm, achieving a dual breakthrough in recognition speed and accuracy.
| Item |
Description |
| Recognition Speed |
< 200ms, supports real-time matching with 10,000-person-level database |
| Recognition Accuracy |
FAR < 1/1,000,000, FRR < 0.1% |
| Liveness Detection |
Multi-dimensional liveness detection algorithm, effectively defends against photo, video, and artificial eye attacks |
| Deployment Method |
Supports edge computing and cloud deployment, flexibly adapts to enterprise architectures |
2. Product Matrix: Covering All Enterprise Scenarios
Series L Iris Login Terminals: Designed exclusively for enterprise IT systems, replacing traditional passwords and OTP to realize strong identity authentication for workstations, servers, and VPNs. Supporting Windows/Linux/macOS multi-platforms, it can be seamlessly integrated with existing AD/LDAP systems.
Series D Iris Access Control Terminals: Suitable for high-security areas such as data centers, R&D laboratories, and finance offices. Supporting iris + employee card two-factor authentication, with a recognition distance of 20-40cm and a passing efficiency of up to 20 people per minute.
Series G Iris Channel Gates: Targeting high-traffic scenarios such as industrial parks and office buildings, supporting on-the-move recognition with a single-channel passing capacity of up to 40 people per minute, balancing security and convenience.
Series C Iris Capture Modules: Embedded solutions for system integrators and equipment manufacturers, which can be integrated into various devices such as ATMs, self-service terminals, and VR head-mounted displays.
3. AI Agent Linkage Solution
In response to the special needs of the AI Agent era, Homsh has launched a Continuous Identity Authentication solution:
When an AI Agent executes sensitive operations (such as large-sum fund transfers, permission changes, and data export), the system automatically triggers a secondary iris verification to ensure the real identity of the operator. The verification results are recorded in the audit log in real time, forming a complete identity traceability chain.
This solution has been successfully applied to the intelligent customer service systems of many financial institutions and unattended service windows of government service platforms, effectively plugging the identity security loopholes brought by AI Agent.
V. Practical Implementation: From Theory to Value
Case 1: Core System Upgrade of a Joint-Stock Commercial Bank
The bank's original face recognition access control system faced three consecutive deepfake attack attempts in 2024 (all manually intercepted by security personnel). In Q3 2025, the bank decided to upgrade the access control system of its core data center to Homsh's Series D iris access control solution.
Implementation Effects:
● Zero security incidents in the 6 months since deployment;
● 35% improvement in employee passing efficiency (no need for card swiping and password entry);
● Full compliance with the CBRC's regulatory requirements for biometric data protection.
Case 2: AI R&D Center of a Technology Group
The group's AI R&D center stores a large amount of core algorithms and training data. With the widespread application of AI Agent in internal workflows, the management has put forward higher requirements for identity security.
Solution:
Deploy Series L iris login terminals and deeply integrate them with the internal AI Agent platform. When the AI Agent executes sensitive operations such as code submission, model deployment, and data export, iris verification is automatically triggered.
Implementation Effects:
● Significant reduction in the risk of R&D data leakage;
● Full auditability and traceability of AI Agent operations;
● An increase in the average daily number of authentications for employees, but a decrease in total time spent (iris recognition is faster than password entry).
Conclusion
In the AI Agent era, identity security is no longer the icing on the cake, but the line between life and death for enterprises' digital transformation. As deepfake technology renders face recognition fragile, and as AI can execute sensitive operations on behalf of humans, we need a higher level of security protection.
Iris recognition, with its innate anti-counterfeiting features, outstanding recognition accuracy, and full protection of privacy, is becoming the ultimate line of defense for enterprise identity security. Homsh is willing to join hands with partners in all industries to jointly safeguard the security of digital assets in the AI era.
