Related papers: Runtime Verification for Trustworthy Computing

Guaranteeing runtime integrity of embedded system software is an open problem. Trade-offs between security and other priorities (e.g., cost or performance) are inherent, and resolving them is both challenging and important. The…

Confidential Virtual Machines (CVMs) protect data in use by running workloads within hardware-enforced Trusted Execution Environments (TEEs). However, existing CVM attestation mechanisms only certify what code is running, not where it is…

The integration of Artificial Intelligence (AI) into safety-critical systems introduces a new reliability paradigm: silent failures, where AI produces confident but incorrect outputs that can be dangerous. This paper introduces the Formal…

Monitoring is the study of a system at runtime, looking for input and output events to discover, check or enforce behavioral properties. Interactive debugging is the study of a system at runtime in order to discover and understand its bugs…

To guarantee that machine learning models yield outputs that are not only accurate, but also robust, recent works propose formally verifying robustness properties of machine learning models. To be applicable to realistic safety-critical…

Finite-state models are ubiquitous in the study of concurrent systems, especially controllers and servers that operate in a repetitive cycle. In this paper, we show how to extract finite state models from a run of a multi-threaded Java…

Vehicular Ad hoc Networks (VANETs) facilitate vehicles to wirelessly communicate with neighboring vehicles as well as with roadside units (RSUs). However, the existence of inaccurate information within the network can cause traffic…

Scientific computing sometimes involves computation on sensitive data. Depending on the data and the execution environment, the HPC (high-performance computing) user or data provider may require confidentiality and/or integrity guarantees.…

Cyber-physical systems (CPS) are vulnerable to attacks targeting outgoing actuation commands that modify their physical behaviors. The limited resources in such systems, coupled with their stringent timing constraints, often prevents the…

Safety evaluation is an essential component of clinical trials. To protect study participants, these studies often implement safety stopping rules that will halt the trial if an excessive number of toxicity events occur. Existing safety…

Runtime verification (RV) has the potential to enable the safe operation of safety-critical systems that are too complex to formally verify, such as Robot Operating System 2 (ROS2) applications. Writing correct monitors can itself be…

This paper addresses the problem of maintaining safety during training in Reinforcement Learning (RL), such that the safety constraint violations are bounded at any point during learning. In a variety of RL applications the safety of the…

With the rapidly evolving next-generation systems-of-systems, we face new security, resilience, and operational assurance challenges. In the face of the increasing attack landscape, it is necessary to cater to efficient mechanisms to verify…

In real-time embedded systems (RTS), failures due to security breaches can cause serious damage to the system, the environment and/or injury to humans. Therefore, it is very important to understand the potential threats and attacks against…

We use runtime verification (RV) to check various specifications in a smart apartment. The specifications can be broken down into three types: behavioral correctness of the apartment sensors, detection of specific user activities (known as…

In runtime verification, a monitor watches a trace of a system and, if possible, decides after observing each finite prefix whether or not the unknown infinite trace satisfies a given specification. We generalize the theory of runtime…

Foundation Models (FMs) display exceptional performance in tasks such as natural language processing and are being applied across a growing range of disciplines. Although typically trained on large public datasets, FMs are often fine-tuned…

Current large language model agent frameworks prioritize autonomy but lack the governability mechanisms required for enterprise deployment. High-risk write operations proceed without independent review, complex tasks lack acceptance…

Trusted Execution Environments (TEEs) have emerged as a cornerstone for securing sensitive computations by providing isolated enclaves protected from untrusted software. However, their security guarantees are undermined by vulnerabilities…

Robot learning methods have recently made great strides, but generalization and robustness challenges still hinder their widespread deployment. Failing to detect and address potential failures renders state-of-the-art learning systems not…