  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.
