kill-switch mechanisms

论文探讨了如何通过形式化验证方法提高软件驱动的人造器官的安全性，该方法能证明代码在所有允许执行情况下的正确性。

This study addresses safety risks arising from software faults in cyber-physical systems (CPS) for electric bicycles. We propose a simulation-driven functional Failure Mode and Effects Analysis (FMEA) method, leveraging Simulink Fault Analyzer to construct fault models, integrated with expert review and a systematic FMEA process to close the loop among fault modeling, simulation-based analysis, and impact assessment. Experimental evaluation identified 13 real-world faults with 100% model accuracy; among them, five revealed previously unrecognized safety implications, and 38.4% induced anomalous system behavior. The study distills ten reusable engineering practice guidelines, significantly enhancing the effectiveness and practicality of FMEA in industrial-scale CPS. It provides empirical validation and methodological contributions toward the operational deployment of simulation-driven safety analysis.

论文提出一种权威分解框架，通过行动相关方法确定哪些信任域联合体能导致受保护执行，解决高风险自动化系统中控制分布问题。

Current operational design domain (ODD) specifications for high-level automated driving systems lack formal foundations, undermining safety argument traceability and impeding integrated development and verification. To address this, this paper proposes a formal ODD modeling method based on the Pkl configuration language. Leveraging Pkl’s structured syntax, type safety, and modular organization, the approach enables machine-readable, verifiable ODD representations and supports end-to-end traceable evidence generation—from requirements definition to safety assurance. Evaluated on representative automotive scenarios, the method significantly improves ODD description precision, specification consistency, and assessment efficiency. Its core contribution lies in the first systematic adoption of Pkl for ODD modeling, uniquely balancing expressive flexibility with the rigor and engineering practicality demanded by functional safety standards. The approach demonstrates strong cross-domain applicability across automated systems.

This work addresses the security risks associated with executing industrial control software on unauthorized hardware, a challenge inadequately mitigated by conventional protection mechanisms that often fail to balance security and functional correctness. The authors propose a novel hardware-software binding approach that integrates Physical Unclonable Functions (PUFs) with symbolic execution to enforce program behavior constraints and verify critical security properties. This method ensures that the software operates correctly only on authorized target devices while maintaining secure behavior—even in the presence of unauthorized execution environments or PUF failures. Notably, this study is the first to leverage symbolic execution for preserving software security properties under anomalous execution conditions, thereby achieving a robust combination of strong anti-reverse-engineering capabilities and high reliability.

本文通过Isabelle/HOL形式化了ERC-8319提出的六个监管行动的执行语义，并验证了Solidity/EVM实现，解决了安全令牌标准中监管操作的法律效果和证据问题。

This work addresses the persistent reliance on manual intervention for recovering from faults in process plants that fall outside predefined monitoring logic. To enhance automation and safety, the authors propose a knowledge-guided large language model (LLM) agent framework that functions as a constrained supervisory planner. By integrating domain-specific plant knowledge, the framework generates safe recovery actions and ensures execution reliability through symbolic or simulation-based verification mechanisms. The study innovatively defines three core design dimensions for LLM agents in this context: fault recovery patterns, verification strategies, and deployment constraints. Additionally, it provides two open-source Python environments to facilitate reproduction of canonical cases and support user-defined extensions, thereby significantly advancing the automation and safety of fault recovery in industrial settings.

本文提出Agile-V Assurance Spine，通过权威源配置文件、工件绑定、风险适当独立性和时效性等方法解决工程生命周期中对代理输出的正当行动问题。

论文提出通过系统工程方法解决LLM错误修正无法持久的问题，建立一套包含七个原则的操作规范，并通过案例说明其有效性。

This work addresses the challenge in safety-critical systems where complexity hinders development teams from fully comprehending system behavior and providing trustworthy explanations. To bridge this gap, the paper proposes Behavior-Driven Explainability (BDX), a method that directly translates structured scenarios from Behavior-Driven Development (BDD) into formal behavioral specifications and automatically generates user-oriented explainable outputs. BDX seamlessly integrates system specification with explanation generation, making it applicable across any development phase and abstraction level. The approach is validated through a case study on exception handling in a RISC-V processor, demonstrating that BDX effectively supports explainability requirements early in the design process, thereby significantly enhancing system transparency and trustworthiness.