Youqian Zhang (The Hong Kong Polytechnic University), Zheng Fang (The Hong Kong Polytechnic University), Huan Wu (The Hong Kong Polytechnic University & Technological and Higher Education Institute of Hong Kong), Sze Yiu Chau (The Chinese University of Hong Kong), Chao Lu (The Hong Kong Polytechnic University), Xiapu Luo (The Hong Kong Polytechnic University)

Optical fibers are widely regarded as reliable communication channels due to their resistance to external interference and low signal loss.
This paper demonstrates a critical side channel within telecommunication optical fiber that allows for acoustic eavesdropping. By exploiting the sensitivity of optical fibers to acoustic vibrations, attackers can remotely monitor sound-induced deformations in the fiber structure and further recover information from the original sound waves.

This issue becomes particularly concerning with the proliferation of Fiber-to-the-Home (FTTH) installations in modern buildings. Attackers with access to one end of an optical fiber can use commercially available Distributed Acoustic Sensing (DAS) systems to tap into the private environment surrounding the other end. However, because the optical fiber alone is not sensitive enough to airborne sound, we introduce a “Sensory Receptor” that improves acoustic capture. Our results demonstrate the ability to recover critical information, such as human activities, indoor localization, and conversation contents, raising important privacy concerns for fiber-optic communication networks.

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BKPIR: Keyword PIR for Private Boolean Retrieval

Jie Song (Institute of Information Engineering, Chinese Academy of Sciences; Intelligent Policing Key Laboratory of Sichuan Province, Sichuan Police College; School of Cyber Security, University of Chinese Academy of Sciences), Zhen Xu (Institute of Information Engineering, Chinese Academy of Sciences), Yan Zhang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University…

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Connecting the Dots: An Investigative Study on Linking Private...

Junkyu Kang (KAIST), Soyoung Lee (KAIST), Yonghwi Kwon (University of Maryland), Sooel Son (KAIST)

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IsolatOS: Detecting Double Fetch Bugs in COTS RTOS by...

Yingjie Cao (Sun Yat-sen University and The Hong Kong Polytechnic University), Xiaogang Zhu (Adelaide University), Dean Sullivan (University of New Hampshire, US), Haowei Yang, Lei Xue (Sun Yat-sen University), Xian Li (Swinburne University of Technology, Australia), Chenxiong Qian (University of Hong Kong, China), Minrui Yan (Swinburne University of Technology, Australia), Xiapu Luo (The Hong Kong…

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