Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2020
Abstract
The end-users communicating over a network path currently have no control over the path. For a better quality of service, the source node often opts for a superior (or premium) network path to send packets to the destination node. However, the current Internet architecture provides no assurance that the packets indeed follow the designated path. Network path validation schemes address this issue and enable each node present on a network path to validate whether each packet has followed the specific path so far. In this work, we introduce two notions of privacy—path privacy and index privacy—in the context of network path validation. We show that, in case a network path validation scheme does not satisfy these two properties, the scheme is vulnerable to certain practical attacks (that affect the privacy, reliability, neutrality and quality of service offered by the underlying network). To the best of our knowledge, ours is the first work that addresses privacy issues related to network path validation. We design PrivNPV, a privacy-preserving network path validation protocol, that satisfies both path privacy and index privacy. We discuss several attacks related to network path validation and how PrivNPV defends against these attacks. Finally, we discuss the practicality of PrivNPV based on relevant parameters.
Keywords
index privacy, Network path validation, path privacy, source authentication
Discipline
Information Security | OS and Networks
Research Areas
Cybersecurity
Publication
ACM Transactions on Internet Technology
Volume
20
Issue
1
First Page
5:1
Last Page
5:27
ISSN
1533-5399
Identifier
10.1145/3372046
Publisher
Association for Computing Machinery (ACM)
Citation
SENGUPTA, Binanda; LI, Yingjiu; BU, Kai; and DENG, Robert H..
Privacy-preserving network path validation. (2020). ACM Transactions on Internet Technology. 20, (1), 5:1-5:27.
Available at: https://ink.library.smu.edu.sg/sis_research/5099
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3372046