This paper proposes a lightweight, multi-layer Machine Learning-based security framework for Industrial IoT (IIoT) to enhance trust convergence and detect advanced threats.

This survey reviews hardware-rooted trust mechanisms, such as PUFs and TPMs, demonstrating that hardware-based solutions are superior to software-only methods for ensuring secure authentication and AI…

The paper proposes HammerWatch, a novel remote attestation protocol that enables external verifiers to detect hardware-induced disturbances, specifically Rowhammer-like attacks, by analyzing memory-le…

The Device Context Protocol (DCP) introduces a compact, safety-first communication standard designed to allow LLMs to reliably control resource-constrained physical microcontrollers, significantly imp…

Space Fabric introduces a novel satellite-based Trusted Execution Architecture (TEE) that establishes trust for orbital computing by generating cryptographic secrets and binding workload execution to…

The paper presents a highly optimized, low-stack implementation of the HAETAE signature scheme, reducing peak stack usage significantly to enable its use on severely memory-constrained microcontroller…

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.

The paper introduces a novel toolkit to enhance RISC-V Trusted Execution Environments (TEEs) by adding modular extensions for secure enclave update, migration, state continuity, and trusted time, ther…

The paper proposes Q-FE, a novel Quantum-Native 6G Far-Edge architecture that secures Industrial IoT Digital Twins by integrating micro-digital twins, compact post-quantum key exchange, and asynchrono…

TeeDAO introduces a novel three-layer framework that autonomously organizes and manages multiple heterogeneous Trusted Execution Environments (TEEs) to provide robust, distributed-trust systems with h…

The paper introduces $I$-$(OT)^2$, a novel base 1-out-of-2 Oblivious Transfer (OT) protocol designed to minimize computation and interaction for resource-constrained IoT devices.

The paper introduces MolTrust, a production-deployed trust infrastructure built on W3C standards (VCs and DIDs) that provides a verifiable, multi-layered authorization framework for autonomous AI agen…

FIDEM introduces a standard-compliant framework that uses Zero-Knowledge Proofs to securely bind IoT devices to their Manufacturer Usage Description (MUD) profiles, mitigating risks associated with in…

CHRONOS is a hardware-assisted framework that significantly reduces the latency of secure federated learning by decoupling cryptographic key setup from the active training phase, while maintaining hig…

The paper proposes a resource-efficient, threshold-based authentication scheme for constrained IIoT devices using SRAM PUFs, addressing inherent unreliability through a combination of Hamming code err…

This paper provides the first comprehensive review of threats and defenses specifically targeting on-device AI inference, revealing a significant imbalance where certain attack types, like adversarial…

The paper proposes a RADIUS-based framework to maintain persistent device identity for Network Access Control (NAC) despite modern operating system MAC address randomization, ensuring regulatory compl…

The paper proposes a lightweight, Merkle-tree-based pipeline for verifying the integrity of IoT audit logs, achieving high throughput and low latency without the overhead of blockchain technology.

The paper proposes a Secure-driven time synchronization mechanism to resolve the conflict between RTOS timekeeping (which requires periodic interrupts) and the atomicity requirements of trusted comput…

The paper introduces AIP, a novel protocol using Invocation-Bound Capability Tokens (IBCTs) to provide verifiable identity and secure delegation across Model Context Protocol (MCP) and Agent-to-Agent…