Obfuscating network structure from blockchain analysis
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Date
2025
Authors
Khalid, Asfa
Murphy, Seán Óg
Sreenan, Cormac J.
Roedig, Utz
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Nature Switzerland
Published Version
Abstract
In the context of large-scale data collection like in the Internet of Things, Data Confidence Fabrics are expected to play an essential role in verifying and authenticating sensor data. To this end, metadata is generated at each network node and stored on the blockchain. However, storing metadata on the blockchain introduces significant privacy risks, as it can be exploited to reveal sensitive information, such as network structures and communication paths. This paper addresses these challenges by proposing two novel schemes to protect network structures: Hostname Mapping and Hostname Encryption. Our work demonstrates that the Hostname Mapping approach effectively conceals network patterns but introduces inefficiencies due to additional table storage and computational overhead. In contrast, the Hostname Encryption method eliminates the need for additional table management, offering a more efficient and secure alternative. Despite these advancements, the timestamp field in metadata could still allow attackers to infer patterns using machine learning, highlighting the need for further research to fully secure metadata. By combining encryption with some enhancements to timestamp obfuscation, our approach lays the foundation for additional privacy protection against metadata exploitation.
Description
Keywords
Network security , Data Confidence Fabrics , Blockchain forensics , Metadata privacy , Obfuscation techniques
Citation
Khalid, A., Murphy, S. Ó., Sreenan, C. J., Roedig, U. (2025) 'Obfuscating network structure from blockchain analysis', in Barolli, L. (ed.) Advanced Information Networking and Applications. AINA 2025. Lecture Notes on Data Engineering and Communications Technologies, 251. pp. 95-104. Springer, Cham. https://doi.org/10.1007/978-3-031-87781-0_11