Visible to the public Biblio

Filters: Author is Dio De Niz  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
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.