IEEE Internet of Things Journal

Electromagnetic information leakage has emerged as a critical side-channel threat, enabling adversaries to reconstruct sensitive display content by capturing unintended emissions from electronic devices. This phenomenon, known as TEMPEST, poses heightened risks in the Internet of Things (IoT) era, where numerous connected devices with embedded displays are deployed across industrial, financial, a…

Privacy-preserving statistical analysis (PSA) over distributed datasets is essential for achieving a balance between data utility and privacy protection. This process requires supporting diverse queries on sensitive data while ensuring both data and queries confidentiality. However, the existing Privacy Probability Computation (PPC) methods are typically restricted to discrete point queries due t…

Inertial navigation and WiFi are two common approaches for pedestrian localization. However, conventional pedestrian dead reckoning (PDR) and WiFi fingerprinting suffer from limited adaptability to different users and poor robustness to environmental changes, respectively. Recent deep-learning-based methods address pedestrian localization by modeling sequential dependencies in inertial data, but …

Smart intersection monitoring systems face critical limitations when relying on single-sensor modalities, with cameras degrading under poor visibility and radar struggling with sparse point clouds. This work presents a novel multi-modal sensor fusion framework that integrates radar and camera detections through adaptive range-dependent strategies for robust vehicle detection across diverse operat…

The advancement of Internet of Things (IoT) and autonomous driving applications has resulted in significantly increased demands for lane-level navigation using consumer-grade smartphones. However, the frequent occurrence of carrier phase cycle slips in smartphones severely degrade positioning accuracy, posing a major obstacle to achieving reliable lane-level navigation. While various cycle slip d…

Security Operations Center (SOC) analysts experience notable performance degradation under elevated cognitive stress, yet existing systems treat stress detection and decision support as separate problems. This paper presents a Cognitive–Physiological Synchronization (CPS) Framework for IoT-based Security Operations Centers (IoT-SOCs) that integrates multimodal physiological stress inference with …

Defect inversion is a critical quantitative assessment technique to evaluate the integrity of energy transportation systems. In practice, non-stationary states and frequent situation switches in real-world industrial processes make it difficult to acquire ideal sensor signals with precise annotations, there by compromising accurate defect inversion. Simulation systems is a viable solution. Howeve…

With the growing deployment of text-to-image diffusion models in real-world applications, concerns about model copyright have become increasingly prominent. Model watermarking has emerged as a promising solution. However, existing methods often suffer from degradation of model fidelity and poor scalability in model distribution scenarios. Moreover, recent studies have shown that some watermarking…