Accountant: Protection of Data Integrity and Identification of Malicious Nodes in In-network Data Processing

David Jost, Mathias Fischer

Abstract

Data integrity in distributed data sensing and processing platforms or middlewares is an important issue, especially if those platforms are open to anyone. To leverage the resources of participating nodes and to enhance the scalability, nodes can be included in the data processing, e.g., in the aggregation of results. In an open system, it is also likely that some participating nodes are malicious and lie about their sensed values or about the results of data processed by them. Current approaches that preserve data integrity for in-network processing require expensive cryptographic operations. With Accountant we propose a new approach, which requires significantly less computation at the expense of slightly more signalling overhead. Furthermore, our approach cannot only preserve data integrity, but also allows to identify malicious nodes. For that, Accountant uses multiple inner node-disjoint trees for data dissemination and hash trees for preserving the data integrity. We compare it to existing solutions, showing that with only minor additional messaging overhead, Accountant can protect the data integrity and can identify attackers at the same time.

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Paper Citation


in Harvard Style

Jost D. and Fischer M. (2020). Accountant: Protection of Data Integrity and Identification of Malicious Nodes in In-network Data Processing.In Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-399-5, pages 561-568. DOI: 10.5220/0008974405610568


in Bibtex Style

@conference{icissp20,
author={David Jost and Mathias Fischer},
title={Accountant: Protection of Data Integrity and Identification of Malicious Nodes in In-network Data Processing},
booktitle={Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2020},
pages={561-568},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008974405610568},
isbn={978-989-758-399-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Accountant: Protection of Data Integrity and Identification of Malicious Nodes in In-network Data Processing
SN - 978-989-758-399-5
AU - Jost D.
AU - Fischer M.
PY - 2020
SP - 561
EP - 568
DO - 10.5220/0008974405610568