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Bibliographic Details
Main Authors: Dong, Shuaike, Shen, Siyu, Li, Zhou, Zhang, Kehuan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2505.06822
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author Dong, Shuaike
Shen, Siyu
Li, Zhou
Zhang, Kehuan
author_facet Dong, Shuaike
Shen, Siyu
Li, Zhou
Zhang, Kehuan
contents In this paper, we proposes an automatic firmware analysis tool targeting at finding hidden services that may be potentially harmful to the IoT devices. Our approach uses static analysis and symbolic execution to search and filter services that are transparent to normal users but explicit to experienced attackers. A prototype is built and evaluated against a dataset of IoT firmware, and The evaluation shows our tool can find the suspicious hidden services effectively.
format Preprint
id arxiv_https___arxiv_org_abs_2505_06822
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hunting the Ghost: Towards Automatic Mining of IoT Hidden Services
Dong, Shuaike
Shen, Siyu
Li, Zhou
Zhang, Kehuan
Cryptography and Security
In this paper, we proposes an automatic firmware analysis tool targeting at finding hidden services that may be potentially harmful to the IoT devices. Our approach uses static analysis and symbolic execution to search and filter services that are transparent to normal users but explicit to experienced attackers. A prototype is built and evaluated against a dataset of IoT firmware, and The evaluation shows our tool can find the suspicious hidden services effectively.
title Hunting the Ghost: Towards Automatic Mining of IoT Hidden Services
topic Cryptography and Security
url https://arxiv.org/abs/2505.06822