Hunting the Ghost: Towards Automatic Mining of IoT Hidden Services
Shuaike Dong, Siyu Shen, Zhou Li, Kehuan Zhang
TL;DR
This paper presents an automated static analysis and symbolic execution tool designed to detect hidden, potentially malicious services in IoT device firmware, enhancing security by uncovering covert functionalities.
Contribution
The paper introduces a novel automated firmware analysis method combining static analysis and symbolic execution for identifying hidden IoT services.
Findings
Effective detection of suspicious hidden services in IoT firmware
Prototype successfully evaluated on real IoT firmware datasets
Tool demonstrates high accuracy and efficiency in uncovering covert services
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Malware Detection Techniques · Digital and Cyber Forensics · Spam and Phishing Detection