Physically Unclonable Fingerprints for Authentication

被引:2
作者
Baban, Navajit S. [1 ]
Zhou, Jiarui [1 ]
Bhattacharya, Sarani [2 ]
Chatterjee, Urbi [3 ]
Bhattacharjee, Sukanta [4 ]
Vijayavenkataraman, Sanjairaj [1 ]
Song, Yong-Ak [1 ]
Mukhopadhyay, Debdeep [2 ]
Chakrabarty, Krishnendu [5 ]
Karri, Ramesh [6 ]
机构
[1] New York Univ Abu Dhabi, Abu Dhabi 129188, U Arab Emirates
[2] Indian Inst Technol Kharagpur, Kharagpur 721302, W Bengal, India
[3] Indian Inst Technol Kanpur, Kanpur 208016, Uttar Pradesh, India
[4] Indian Inst Technol Guwahati, Gauhati 781039, India
[5] Arizona State Univ, Tempe, AZ 85287 USA
[6] NYU, New York, NY 11201 USA
来源
APPLIED CRYPTOGRAPHY AND NETWORK SECURITY WORKSHOPS, PT II, ACNS 2024-AIBLOCK 2024, AIHWS 2024, AIOTS 2024, SCI 2024, AAC 2024, SIMLA 2024, LLE 2024, AND CIMSS 2024 | 2024年 / 14587卷
基金
美国国家科学基金会;
关键词
Fingerprints; Physically Unclonable; Security; Intellectual Property; Deep Learning; Transfer Learning; Trusted Third Party;
D O I
10.1007/978-3-031-61489-7_21
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We have developed an innovative fingerprinting method using the melt-electrospinning printing process for product authentication. This method generates unique, unclonable fingerprints that can be made tamper-proof with a transparent polymer coating. We have successfully tested this approach by printing 393 unique fingerprints on glass substrates, achieving a 95.8% deep learning-based authentication accuracy. Furthermore, fluorescent ink can be employed to enhance fingerprint visibility, enabling analysis through fluorescence microscopy and facilitating spectral authentication. Additionally, the transparent polymer coating obfuscates and encrypts the fingerprint, which can be decrypted using Speeded-Up Robust Features (SURF) techniques. Our ongoing research focuses on assessing the vulnerability of fingerprint images to adversarial attacks, as well as conducting analyses of uniqueness, uniformity, and reliability. We are also ensuring their robustness through machine and deep learning techniques. The proposed authentication scheme aims to provide a dependable solution tailored to the complexities of modern manufacturing and supply chains, effectively mitigating potential intellectual property threats.
引用
收藏
页码:235 / 239
页数:5
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