Privacy-preserving network provenance

Author:

Zhang Yuankai1,O'Neill Adam1,Sherr Micah1,Zhou Wenchao1

Affiliation:

1. Georgetown University

Abstract

Network accountability, forensic analysis, and failure diagnosis are becoming increasingly important for network management and security. Network provenance significantly aids network administrators in these tasks by explaining system behavior and revealing the dependencies between system states. Although resourceful, network provenance can sometimes be too rich, revealing potentially sensitive information that was involved in system execution. In this paper, we propose a cryptographic approach to preserve the confidentiality of provenance (sub)graphs while allowing users to query and access the parts of the graph for which they are authorized. Our proposed solution is a novel application of searchable symmetric encryption (SSE) and more generally structured encryption (SE). Our SE-enabled provenance system allows a node to enforce access control policies over its provenance data even after the data has been shipped to remote nodes ( e.g. , for optimization purposes). We present a prototype of our design and demonstrate its practicality, scalability, and efficiency for both provenance maintenance and querying.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LLMs for the Post-Hoc Creation of Provenance;2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW);2024-07-08

2. Reliable Data Provenance in HCN;Wireless Networks;2023-12-19

3. Data Provenance in Security and Privacy;ACM Computing Surveys;2023-07-17

4. Enhanced Clustering Based OSN Privacy Preservation to Ensure k-Anonymity, t-Closeness, l-Diversity, and Balanced Privacy Utility;Computers, Materials & Continua;2023

5. ProvNet: Networked bi-directional blockchain for data sharing with verifiable provenance;Journal of Parallel and Distributed Computing;2022-08

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