Abstract
Aiming to reduce the cost and complexity of maintaining networking infrastructures, organizations are increasingly outsourcing their network functions (e.g., firewalls, traffic shapers and intrusion detection systems) to the cloud, and a number of industrial players have started to offer network function virtualization (NFV)-based solutions. Alas, outsourcing network functions in its current setting implies that sensitive network policies, such as firewall rules, are revealed to the cloud provider. In this paper, we investigate the use of cryptographic primitives for processing outsourced network functions, so that the provider does not learn any sensitive information. More specifically, we present a cryptographic treatment of privacy-preserving outsourcing of network functions, introducing security definitions as well as an abstract model of generic network functions, and then propose a few instantiations using partial homomorphic encryption and public-key encryption with keyword search. We include a proof-of-concept implementation of our constructions and show that network functions can be privately processed by an untrusted cloud provider in a few milliseconds.
Original language | English |
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Title of host publication | Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization |
Place of Publication | New York |
Publisher | Association for Computing Machinery, Inc |
Pages | 39-44 |
Number of pages | 6 |
ISBN (Electronic) | 9781450340786 |
DOIs | |
Publication status | Published - 11 Mar 2016 |
Externally published | Yes |
Event | 6th ACM Conference on Data and Application Security and Privacy : ACM CODASPY 2016 - New Orleans, United States Duration: 9 Mar 2016 → 11 Mar 2016 https://sites.google.com/site/codaspy20162/ |
Conference
Conference | 6th ACM Conference on Data and Application Security and Privacy |
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Abbreviated title | ACM CODASPY 2016 |
Country/Territory | United States |
City | New Orleans |
Period | 9/03/16 → 11/03/16 |
Internet address |
Keywords
- homomorphic encryption
- NFV privacy
- PEKS