The paper proposes a distributed, privacy-preserving monitoring architecture that uses secret-sharing to efficiently monitor systems with continuous state, overcoming the scalability issues of traditi…

This paper proves that a strongly consistent solution to the Causal Observability Problem is unachievable at the observable boundary and explores the impact of instrumentation placement on monitor gua…

RegGuard is a unified framework that enhances optimistic rollups with three coordinated mechanisms—semantic validation, cross-layer state consistency checks, and fair ordering—to make them suitable fo…

The paper proposes a novel method to automatically enforce differential privacy in stream-based runtime monitoring specifications by analyzing temporal dependencies and injecting calibrated noise.

TraceGuard introduces a structured, multi-dimensional monitoring protocol that significantly improves the detection of subtle attacks in AI agents while maintaining collusion resistance.

ChainGuards is a decentralized system that uses product-specific rules and blockchain technology to verify the reliability of sensor-derived data collected across a supply chain, successfully detectin…

The paper introduces MonitoringBench, a semi-automated red-teaming methodology that generates diverse and stronger attacks, revealing that current coding-agent monitors often fail against sophisticate…

The paper argues that watermarking must be viewed as a monitoring primitive, introducing an observer-based threat model that shows even zero-bit watermarking can enable entity-level attribution throug…

The paper introduces the Reconstructive Authority Model (RAM), a novel framework that proves execution validity by assessing state coverage rather than just state integrity, showing that existing atte…

ClawGuard introduces a passive, out-of-band security monitor that detects LLM agent workflow hijacking by analyzing unique electromagnetic (EM) emanations generated during agent skill execution.

The paper proposes a comprehensive monitoring and triage methodology for agentic systems, demonstrating that structural defects mask task-level errors and require specialized monitoring scopes for det…

QML-PipeGuard introduces a contract-based framework that monitors the behavioral fingerprint of quantum machine learning pipelines to detect both hardware drift and malicious channel substitution.

The paper proposes an evidence-driven protocol combining Deterministic Build Systems and Trusted Execution Environments to provide cryptographically verifiable guarantees of software artifact integrit…

The paper reframes LLM reliability from an impossible universal problem to a manageable, local patch-based problem, showing that sufficient interventions can be found by focusing on recurring failure…

The paper presents a novel technology that uses zero-knowledge proofs to formally verify a software system's correctness against a public specification without revealing the system's internal details.

The paper proposes a zero-trust supply-chain assurance rubric for O-RAN RIC applications to secure the entire lifecycle, from development to runtime.

The paper proves that platform-deterministic inference is a necessary and sufficient condition for trustworthy AI, establishing that AI trust fundamentally relies on consistent arithmetic.

This paper introduces a formal framework to rigorously verify the security guarantees (confidentiality, integrity, and availability) of AMD SEV confidential virtual machines.

This paper introduces a formal framework to rigorously verify the security guarantees (confidentiality, integrity, and availability) of AMD SEV confidential virtual machines.

The paper develops a novel, sound, and complete deductive proof system for proving contract satisfaction, which is crucial for verifying CPU security against side-channel attacks.