HackerPapers

arXiv:1908.05310cs.CR

Network Reconnaissance and Vulnerability Excavation of Secure DDS Systems

Ruffin White, Gianluca Caiazza, Chenxu Jiang, Xinyue Ou, Zhiyue Yang, Agostino Cortesi, Henrik Christensen

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

Distribution Service (DDS) is a realtime peer-to-peer protocol that serves as a scalable middleware between distributed networked systems found in many Industrial IoT domains such as automotive, medical, energy, and defense. Since the initial ratification of the standard, specifications have introduced a Security Model and Service Plugin Interface (SPI) architecture, facilitating authenticated encryption and data centric access control while preserving interoperable data exchange. However, as Secure DDS v1.1, the default plugin specifications presently exchanges digitally signed capability lists of both participants in the clear during the crypto handshake for permission attestation; thus breaching confidentiality of the context of the connection. In this work, we present an attacker model that makes use of network reconnaissance afforded by this leaked context in conjunction with formal verification and model checking to arbitrarily reason about the underlying topology and reachability of information flow, enabling targeted attacks such as selective denial of service, adversarial partitioning of the data bus, or vulnerability excavation of vendor implementations.

arXiv comments
10 pages, 7 figures, 1 algorithm, 10 sections plus references
Journal reference
Workshop on Software Security for Internet of Things (SSIoT) at IEEE EuroS&P 2019
DOI
Subjects
cs.CRCryptography and Security cs.NINetworking and Internet Architecture

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Aug 2019 to Aug 2019. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.