生物识别
计算机科学
密码
加密
编码(内存)
认证(法律)
鉴定(生物学)
模式识别(心理学)
人工智能
计算机安全
数据挖掘
植物
生物
作者
Gerges M. Salama,Safaa El‐Gazar,Basma Omar,Rana Nassar,Ashraf A. M. Khalaf,Ghada M. El‐Banby,Hesham F. A. Hamed,Walid El‐Shafai,Fathi E. Abd El‐Samie
出处
期刊:Optics Express
[The Optical Society]
日期:2022-09-28
卷期号:30 (21): 37816-37816
被引量:5
摘要
The security issue is essential in the Internet-of-Things (IoT) environment. Biometrics play an important role in securing the emerging IoT devices, especially IoT robots. Biometric identification is an interesting candidate to improve IoT usability and security. To access and control sensitive environments like IoT, passwords are not recommended for high security levels. Biometrics can be used instead, but more protection is needed to store original biometrics away from invaders. This paper presents a cancelable multimodal biometric recognition system based on encryption algorithms and watermarking. Both voice-print and facial images are used as individual biometrics. Double Random Phase Encoding (DRPE) and chaotic Baker map are utilized as encryption algorithms. Verification is performed by estimating the correlation between registered and tested models in their cancelable format. Simulation results give Equal Error Rate (EER) values close to zero and Area under the Receiver Operator Characteristic Curve (AROC) equal to one, which indicates the high performance of the proposed system in addition to the difficulty to invert cancelable templates. Moreover, reusability and diversity of biometric templates is guaranteed.
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