Biblio

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2020-03-16
White, Ruffin, Caiazza, Gianluca, Jiang, Chenxu, Ou, Xinyue, Yang, Zhiyue, Cortesi, Agostino, Christensen, Henrik.  2019.  Network Reconnaissance and Vulnerability Excavation of Secure DDS Systems. 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :57–66.

Data 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.

2020-01-29
C. {Cheh}, A. {Fawaz}, M. A. {Noureddine}, B. {Chen}, W. G. {Temple}, W. H. {Sanders}.  2018.  Determining Tolerable Attack Surfaces that Preserves Safety of Cyber-Physical Systems. 2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC). :125-134.

As safety-critical systems become increasingly interconnected, a system's operations depend on the reliability and security of the computing components and the interconnections among them. Therefore, a growing body of research seeks to tie safety analysis to security analysis. Specifically, it is important to analyze system safety under different attacker models. In this paper, we develop generic parameterizable state automaton templates to model the effects of an attack. Then, given an attacker model, we generate a state automaton that represents the system operation under the threat of the attacker model. We use a railway signaling system as our case study and consider threats to the communication protocol and the commands issued to physical devices. Our results show that while less skilled attackers are not able to violate system safety, more dedicated and skilled attackers can affect system safety. We also consider several countermeasures and show how well they can deter attacks.