Visible to the public Biblio

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I
Ivan Ruchkin, Ashwini Rao, Dio De Niz, Sagar Chaki, David Garlan.  2015.  Eliminating Inter-Domain Vulnerabilities in Cyber-Physical Systems: An Analysis Contracts Approach. CPS-SPC '15 Proceedings of the First ACM Workshop on Cyber-Physical Systems-Security and/or PrivaCy.

Designing secure cyber-physical systems (CPS) is a particularly difficult task since security vulnerabilities stem not only from traditional cybersecurity concerns, but also physical ones. Many of the standard methods for CPS design make strong and unverified assumptions about the trustworthiness of physical devices, such as sensors. When these assumptions are violated, subtle inter-domain vulnerabilities are introduced into the system model. In this paper we use formal specification of analysis contracts to expose security assumptions and guarantees of analyses from reliability, control, and sensor security domains. We show that this specification allows us to determine where these assumptions are violated, opening the door to malicious attacks. We demonstrate how this approach can help discover and prevent vulnerabilities using a self-driving car example.

Ivan Ruchkin, Ashwini Rao, Dio De Niz, Sagar Chaki, David Garlan.  2015.  Eliminating Inter-Domain Vulnerabilities in Cyber-PhysicalSystems: An Analysis Contracts Approach. CPS-SPC '15 Proceedings of the First ACM Workshop on Cyber-Physical Systems-Security and/or PrivaCy.

Designing secure cyber-physical systems (CPS) is a particularly difficult task since security vulnerabilities stem not only from traditional cybersecurity concerns, but also physical ones. Many of the standard methods for CPS design make strong and unverified assumptions about the trustworthiness of physical devices, such as sensors. When these assumptions are violated, subtle inter-domain vulnerabilities are introduced into the system model. In this paper we use formal specification of analysis contracts to expose security assumptions and guarantees of analyses from reliability, control, and sensor security domains. We show that this specification allows us to determine where these assumptions are violated, opening the door to malicious attacks. We demonstrate how this approach can help discover and prevent vulnerabilities using a self-driving car example.

A
Amit Vasudevan, Sagar Chaki, Limin Jia, Anupam Datta.  2016.  überSpark: Enforcing Verifiable Object Abstractions for Automated Compositional Security Analysis of a Hypervisor. 25th USENIX Security Symposium (USENIX Security 16).

We present überSpark (üSpark), an innovative architecture for compositional verification of security properties of extensible hypervisors written in C and Assembly. üSpark comprises two key ideas: (i) endowing low-level system software with abstractions found in higher-level languages (e.g., objects, interfaces, function-call semantics for implementations of interfaces, access control on interfaces, concurrency and serialization), enforced using a combination of commodity hardware mechanisms and lightweight static analysis; and (ii) interfacing with platform hardware by programming in Assembly using an idiomatic style (called CASM) that is verifiable via tools aimed at C, while retaining its performance and low-level access to hardware. After verification, the C code is compiled using a certified compiler while the CASM code is translated into its corresponding Assembly instructions. Collectively, these innovations enable compositional verification of security invariants without sacrificing performance. We validate üSpark by building and verifying security invariants of an existing open-source commodity x86 micro-hypervisor and several of its extensions, and demonstrating only minor performance overhead with low verification costs.