The paper proposes a dynamically reconfigurable resistor-capacitor (RC)-based Physically Unclonable Function (PUF) that demonstrates strong resistance against advanced machine learning and deep learni…

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 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 QT-PUF, a novel quantum tunneling leakage-based Physical Unclonable Function (PUF) designed for ultralow-power, implantable IoMT devices, achieving high reliability and minimal powe…

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…

This paper introduces a unified threat model and evaluation framework to systematically compare privacy-preserving techniques for distributed learning in IoT systems, highlighting the trade-off betwee…

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…

LiteAtt introduces a verifier-less, Peer-to-Peer Self-Attestation (P2P-SA) framework for modern IoT MCUs, enabling mutual authentication and firmware attestation directly within the connection handsha…

The paper proposes a graduated trust gating mechanism for IoT location verification that moves beyond binary decisions, allowing systems to dynamically escalate verification rigor based on signal inte…

NetVAD proposes a novel, identifier-free Variational Autoencoder that leverages frozen Foundation Models to achieve highly competitive unsupervised performance for zero-day intrusion detection.

The paper demonstrates that using the transformer-based foundation model TabPFNv2.5 can significantly speed up IoT intrusion detection compared to traditional ensemble methods while maintaining high a…

This paper evaluates the security of the L-Band Digital Aviation Communication System (LDACS) using Physical Unclonable Functions (PUFs) for authentication, identifying vulnerabilities related to pred…

This paper enhances an existing autonomous online Intrusion Detection System (AOC-IDS) for IoT by addressing class imbalance, pseudo-label reliability, and computational overhead, achieving significan…

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 introduces Constraint-Guided Semantic Testing (ConSeT), a novel framework that systematically finds critical, pre-authentication vulnerabilities in 5G User Equipment (UE) by exploiting seman…

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

FedEDAuth is a lightweight, embedding-level authentication framework that enhances federated learning for counterfeit IC detection by identifying and filtering malicious participants before model aggr…

The paper introduces VIPER, a novel backdoor attack framework that exploits the functional fusion of malicious and benign logic within dynamic prompt architectures, demonstrating a new, high-risk thre…

This paper evaluates the security of Universal Circuits (UCs) for hardware obfuscation, demonstrating that they are effective against both oracle-guided and oracle-less attacks.

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…