ForenThings: An Interactive Framework for Crime Scene Reconstruction in IoT Forensics

In IoT platforms, devices and sensors can interact with each other via smart apps that utilize automation settings preconfigured by users, resulting in significant amounts of potential forensic data. Existing IoT forensic approaches can pinpoint relevant data sources for specific activities in smart environments using static code analysis and instrumentation techniques. However, recent IoT platforms like SmartThings no longer run application code on their infrastructure, making access to source code impossible for existing IoT forensic solutions. To bridge this gap, this paper introduces ForenThings , an interactive framework for crime scene reconstruction in smart environments. The main idea is to convert each IoT device and smart app to a responsive agent, enabling them to participate in a forensic investigation of a security incident collaboratively. Instead of relying on static code analysis or instrumentation, ForenThings reconstructs the scene from the device and app events forwarded by the IoT platform. We develop a ForenThings prototype for the SmartThings platform and test its effectiveness for both normal scenarios and 12 real-world IoT attack scenarios. The evaluation shows that ForenThings can achieve 100% data provenance coverage in reconstructing various crime scenes in a smart environment with negligible runtime and resource overhead.

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Publication Details

Journal
ACM Transactions on Internet of Things
Published
2025-10-17
DOI
https://doi.org/10.1145/3772067
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
0.00
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article

ForenThings: An Interactive Framework for Crime Scene Reconstruction in IoT Forensics

Suryadipta Majumdar, Ehsan Khodayarseresht, Mauro Conti, Lianying Zhao et al.
ACM Transactions on Internet of Things
Digital and Cyber Forensics
article

ForenThings: An Interactive Framework for Crime Scene Reconstruction in IoT Forensics

Suryadipta Majumdar, Ehsan Khodayarseresht, Mauro Conti, Lianying Zhao, Sofya Smolyakova, Armin Mansouri
article en

Abstract

In IoT platforms, devices and sensors can interact with each other via smart apps that utilize automation settings preconfigured by users, resulting in significant amounts of potential forensic data. Existing IoT forensic approaches can pinpoint relevant data sources for specific activities in smart environments using static code analysis and instrumentation techniques. However, recent IoT platforms like SmartThings no longer run application code on their infrastructure, making access to source code impossible for existing IoT forensic solutions. To bridge this gap, this paper introduces ForenThings , an interactive framework for crime scene reconstruction in smart environments. The main idea is to convert each IoT device and smart app to a responsive agent, enabling them to participate in a forensic investigation of a security incident collaboratively. Instead of relying on static code analysis or instrumentation, ForenThings reconstructs the scene from the device and app events forwarded by the IoT platform. We develop a ForenThings prototype for the SmartThings platform and test its effectiveness for both normal scenarios and 12 real-world IoT attack scenarios. The evaluation shows that ForenThings can achieve 100% data provenance coverage in reconstructing various crime scenes in a smart environment with negligible runtime and resource overhead.

ACM Transactions on Internet of ThingsVol. 7(1)
University of Padua (IT), Concordia University (US), Concordia University (CA), Carleton University (CA)
Openalex Percentile: Top 57%
Digital and Cyber Forensics
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ForenThings: An Interactive Framework for Crime Scene Reconstruction in IoT Forensics — Suryadipta Majumdar, Ehsan Khodayarseresht, et al. · ACM Transactions on Internet of Things (2025) | TGRS Research Map | TGRS