Hardware-Based System Fingerprinting for IoT Devices Using Configuration Data
DOI:
https://doi.org/10.65879/3070-5789.2026.02.02Keywords:
System Fingerprinting, Hardware Forensics, IoT Device Identification, Configuration Analysis, Digital Forensics, Device Profiling.Abstract
The proliferation of IoT devices challenges digital forensic investigations. Traditional software-based fingerprinting often fails under network changes or software updates. Unlike prior multi-modal approaches relying on active network traffic, this paper proposes a hardware-based fingerprinting framework using passively acquired device configuration data. In practice, configuration data can be extracted from forensic disk images (e.g., /proc/cpuinfo) without physical access. Our method constructs persistent fingerprints from processor, memory, network, and storage features. With 89% persistence over 90 days (including firmware updates), the framework distinguishes legitimate evolution from tampering. Experiments on 1,250 devices (84 variants) achieve 96.3% identification accuracy, outperforming MAC-based, DHCP, and PRNU methods. The approach provides a forensically admissible foundation for IoT device attribution.
References
[1] Aswal K, Pathak H. Advancing vehicle security: deep learning-based solution for defending CAN networks in the Internet of Vehicles. EAI Endorsed Trans Internet Things. 2024;10.
https://doi.org/10.4108/eetiot.6523
[2] Bezawada B, Bachani M, Peterson J, Shirazi H, Ray I, Ray I. Behavioral fingerprinting of IoT devices. In: Proceedings of the 2018 Workshop on Attacks and Solutions in Hardware Security; 2018. p. 1–11. https://doi.org/10.1145/3266444.3266452
[3] Brik V, Banerjee S, Gruteser M, Oh S. Wireless device identification with radiometric signatures. In: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking; 2008. p. 116–127.
https://doi.org/10.1145/1409944.1409959
[4] Chen M, Fridrich J, Goljan M, Lukáš J. Determining image origin and integrity using sensor noise. IEEE Trans Inf Forensics Secur. 2008;3(1):74–90. https://doi.org/10.1109/TIFS.2007.916285
[5] Das A, Borisov N, Caesar M. Fingerprinting smart devices through embedded accelerometers. In: Proceedings of the 2016 ACM Workshop on Privacy in the Electronic Society; 2016. p. 1–12.
[6] Ekwueme CP, Adam IH, Dwivedi A, et al. Lightweight cryptography for Internet of Things: a review. EAI Endorsed Trans Internet Things. 2024;10. https://doi.org/10.4108/eetiot.5565
[7] Feng J, Zhao T, Sarkar S, Konrad D, Jacques T, Cabric D, et al. Fingerprinting IoT devices using latent physical side-channels. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2023;7(2):1–26.
https://doi.org/10.1145/3596247
[8] Fernandez JJ, Nithyanandam P. Biometric watermarking: an application-based review. Int J Inf Priv Secur Integr. 2023;5(3):211–226.
https://doi.org/10.1504/IJIPSI.2023.131546
[9] FingerBank. The ultimate DHCP fingerprint database [Internet]. 2020 [cited 2024 Jan 1]. Available from: https://fingerbank.org
[10] Formby D, Durmuth M, Beyah R. Who's in control of your control system? Device fingerprinting for cyber-physical systems. In: Network and Distributed System Security Symposium; 2016.
https://doi.org/10.14722/ndss.2016.23142
[11] Franklin J, McCoy D, Tabriz P, Neagoe V, Van Randwyk J, Sicker D. Passive data link layer 802.11 wireless device driver fingerprinting. In: USENIX Security Symposium; 2006. p. 167–178.
[12] Greis J, Yushchenko A, Vogel D, Meier M, Steinhage V. Automated identification of vulnerable devices in networks using traffic data and deep learning. Int J Inf Priv Secur Integr. 2021;5(1):1–17.
https://doi.org/10.1504/IJIPSI.2021.119166
[13] Holcomb DE, Burleson WP, Fu K. Power-up SRAM state as an identifying fingerprint and source of true random numbers. IEEE Trans Comput. 2009;58(9):1198–1210.
https://doi.org/10.1109/TC.2008.212
[14] Jang Y, Kim J, Han D. Camera-based user authentication and device fingerprinting using sensor pattern noise. IEEE Trans Inf Forensics Secur. 2017;12(11):2573–2586.
[15] Kang L, Zhang L, Huang X, Hu W, Yang X. Hardware fingerprint authentication in optical networks assisted by anomaly detection. IEEE Photonics Technol Lett. 2022;34(19):1030–1033.
https://doi.org/10.1109/LPT.2022.3199106
[16] Kohno T, Broido A, Claffy K. Remote physical device fingerprinting. IEEE Trans Dependable Secur Comput. 2005;2(2):93–108.
https://doi.org/10.1109/TDSC.2005.26
[17] Kumar V, Paul K. Device fingerprinting for cyber-physical systems: a survey. ACM Comput Surv. 2023;55(14s):1–41.
https://doi.org/10.1145/3584944
[18] Li JJ, Liou JC. An experiment of hit-and-run wireless attacks. Int J Inf Priv Secur Integr. 2017;3(1):58–74.
https://doi.org/10.1504/IJIPSI.2017.10007837
[19] Li S. Zero trust based Internet of Things. EAI Endorsed Trans Internet Things. 2019;5(20):e1.
https://doi.org/10.4108/eai.5-6-2020.165168
[20] Lukáš J, Fridrich J, Goljan M. Digital camera identification from sensor pattern noise. IEEE Trans Inf Forensics Secur. 2006;1(2):205–214.
https://doi.org/10.1109/TIFS.2006.873602
[21] Miettinen M, Marchal S, Hafeez I, Asokan N, Sadeghi AR, Tarkoma S. IoT Sentinel: automated device-type identification for security enforcement in IoT. In: IEEE Int Conf Distrib Comput Syst; 2017. p. 2177–2184.
https://doi.org/10.1109/ICDCS.2017.283
[22] Sánchez PMS, Valero JMJ, Celdrán AH, Bovet G, Pérez MG, Pérez GM. A methodology to identify identical single-board computers based on hardware behavior fingerprinting. J Netw Comput Appl. 2023;212:103579.
https://doi.org/10.1016/j.jnca.2022.103579
[23] Smailes J, Köhler S, Birnbach S, Strohmeier M, Martinovic I. SATIQ: extensible and stable satellite authentication using hardware fingerprinting. ACM Trans Priv Secur. 2025.
https://doi.org/10.1145/3768619
[24] Zander S, Nguyen T, Armitage G. Automated traffic classification and application identification using machine learning. In: IEEE Conf Local Comput Netw; 2007. p. 369–376.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Shancang Li, Tianli Yang (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
