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Computer Science > Cryptography and Security

arXiv:2404.02150 (cs)
[Submitted on 2 Apr 2024 ]

Title: From Seaweed to Security: The Emergence of Alginate in Compromising IoT Fingerprint Sensors

Title: 从海藻到安全:海藻酸盐在破坏物联网指纹传感器中的出现

Authors:Pouria Rad, Gokila Dorai, Mohsen Jozani
Abstract: The increasing integration of capacitive fingerprint recognition sensors in IoT devices presents new challenges in digital forensics, particularly in the context of advanced fingerprint spoofing. Previous research has highlighted the effectiveness of materials such as latex and silicone in deceiving biometric systems. In this study, we introduce Alginate, a biopolymer derived from brown seaweed, as a novel material with the potential for spoofing IoT-specific capacitive fingerprint sensors. Our research uses Alginate and cutting-edge image recognition techniques to unveil a nuanced IoT vulnerability that raises significant security and privacy concerns. Our proof-of-concept experiments employed authentic fingerprint molds to create Alginate replicas, which exhibited remarkable visual and tactile similarities to real fingerprints. The conductivity and resistivity properties of Alginate, closely resembling human skin, make it a subject of interest in the digital forensics field, especially regarding its ability to spoof IoT device sensors. This study calls upon the digital forensics community to develop advanced anti-spoofing strategies to protect the evolving IoT infrastructure against such sophisticated threats.
Abstract: 在物联网设备中越来越多地集成电容式指纹识别传感器,给数字取证带来了新的挑战,尤其是在高级指纹欺骗的背景下。先前的研究已经强调了乳胶和硅等材料在欺骗生物识别系统方面的有效性。在本研究中,我们引入了一种从褐藻中提取的生物聚合物——海藻酸盐,作为一种具有潜在欺骗物联网专用电容式指纹传感器的新材料。我们的研究使用海藻酸盐和先进的图像识别技术,揭示了一个微妙的物联网漏洞,这引发了严重的安全和隐私问题。我们的概念验证实验使用了真实的指纹模具来制作海藻酸盐复制品,这些复制品在视觉和触觉上与真实指纹非常相似。海藻酸盐的导电性和电阻率特性与人类皮肤非常接近,使其成为数字取证领域关注的对象,特别是其欺骗物联网设备传感器的能力。本研究呼吁数字取证社区开发先进的防欺骗策略,以保护不断发展的物联网基础设施免受此类复杂威胁。
Subjects: Cryptography and Security (cs.CR)
Cite as: arXiv:2404.02150 [cs.CR]
  (or arXiv:2404.02150v1 [cs.CR] for this version)
  https://doi.org/10.48550/arXiv.2404.02150
arXiv-issued DOI via DataCite

Submission history

From: Pouria Rad [view email]
[v1] Tue, 2 Apr 2024 17:58:24 UTC (1,903 KB)
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