Biblio

The safety of critical cyber-physical IoT devices hinges on the security of their embedded software that implements control algorithms for monitoring and control of the associated physical processes, e.g., robotics and drones. Reverse engineering of the corresponding embedded controller software binaries enables their security analysis by extracting high-level, domain-specific, and cyber-physical execution semantic information from executables. We present MISMO, a domain-specific reverse engineering framework for embedded binary code in emerging cyber-physical IoT control application domains. The reverse engineering outcomes can be used for firmware vulnerability assessment, memory forensics analysis, targeted memory data attacks, or binary patching for dynamic selective memory protection (e.g., important control algorithm parameters). MISMO performs semantic-matching at an algorithmic level that can help with the understanding of any possible cyber-physical security flaws. MISMO compares low-level binary symbolic values and high-level algorithmic expressions to extract domain-specific semantic information for the binary's code and data. MISMO enables a finer-grained understanding of the controller by identifying the specific control and state estimation algorithms used. We evaluated MISMO on 2,263 popular firmware binaries by 30 commercial vendors from 6 application domains including drones, self-driving cars, smart homes, robotics, 3D printers, and the Linux kernel controllers. The results show that MISMO can accurately extract the algorithm-level semantics of the embedded binary code and data regions. We discovered a zero-day vulnerability in the Linux kernel controllers versions 3.13 and above.

Intelligent software applications are becoming ubiquitous and pervasive affecting various aspects of our lives and livelihoods. At the same time, the risks to which these systems expose the organizations and end users are growing dramatically. Trustworthiness of software applications is becoming a paramount necessity. Trust is to be regarded as a first-class citizen in the total product life cycle and should be addressed across all stages of software development. Trust can be looked at from two facets: one at an algorithmic level (e.g., bias-free, discrimination-aware, explainable and interpretable techniques) and the other at a process level by making development processes more transparent, auditable, and adhering to regulations and best practices. In this paper, we address the latter and propose a blockchain enabled governance framework for building trustworthy software. Our framework supports the recording, monitoring, and analysis of various activities throughout the application development life cycle thereby bringing in transparency and auditability. It facilitates the specification of regulations and best practices and verifies for its adherence raising alerts of non-compliance and prescribes remedial measures.