Abstract
The paper studies how to release data about a critical infrastructure network (e.g., a power network or a transportation network) without disclosing sensitive information that can be exploited by malevolent agents, while preserving the realism of the network. It proposes a novel obfuscation mechanism that combines several privacy-preserving building blocks with a bi-level optimization model to significantly improve accuracy. The obfuscation is evaluated for both realism and privacy properties on real energy and transportation networks. Experimental results show the obfuscation mechanism substantially reduces the potential damage of an attack exploiting the released data to harm the real network.
Original language | English |
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Title of host publication | Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence |
Editors | Sarit Kraus |
Place of Publication | Marina del Rey CA USA |
Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
Pages | 1086-1092 |
Number of pages | 7 |
ISBN (Electronic) | 9780999241141 |
DOIs | |
Publication status | Published - 2019 |
Externally published | Yes |
Event | International Joint Conference on Artificial Intelligence 2019 - Macao, China Duration: 10 Aug 2019 → 16 Aug 2019 Conference number: 28th https://ijcai19.org/ https://www.ijcai.org/proceedings/2019/ (Proceedings) |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
Volume | 2019-August |
ISSN (Print) | 1045-0823 |
Conference
Conference | International Joint Conference on Artificial Intelligence 2019 |
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Abbreviated title | IJCAI 2019 |
Country/Territory | China |
City | Macao |
Period | 10/08/19 → 16/08/19 |
Internet address |
Keywords
- Constraints and SAT
- Constraints
- Applications
- Multidisciplinary Topics and Applications
- Security and Privacy