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The DeeMe experiment to search for muon-to-electron conversions with a sensitivity 10--100 times better than those achieved by previous experiments is in preparation at the Japan Proton Accelerator Research Complex. The magnetic…
Modern Implantable Medical Devices (IMDs) feature wireless connectivity, which makes them vulnerable to security attacks. Particular to IMDs is the battery Denial-of-Service attack whereby attackers aim to fully deplete the battery by…
The proposed switching mechanism is based on an electronically-induced metal-insulator transition occurring in conditions of the excess non-equilibrium carrier density under the applied electric field. First, this mechanism is developed on…
The modern power system is evolving with increasing penetration of power electronics introducing complicated electromagnetic phenomenon. Electromagnetic transient (EMT) simulation is essential to understand power system behavior under…
This paper reviews Voltage-Source Converters (VSCs) EMT and Phasor models currently used to simulate converter-interfaced generation (CIG) and renewable energy resources integration to power systems. Several modelling guidelines and…
Vision Transformers are increasingly embedded in industrial systems due to their superior performance, but their memory and power requirements make deploying them to edge devices a challenging task. Hence, model compression techniques are…
Transfer learning (TL) has been widely used in electroencephalogram (EEG)-based brain-computer interfaces (BCIs) for reducing calibration efforts. However, backdoor attacks could be introduced through TL. In such attacks, an attacker embeds…
The multi-phase inverter has become more complicated, particularly in an Electric Vehicle (EV)'s power train, which requires a robust fault protection system. The proposed active short circuit and safe discharge mechanisms are also included…
The fundamental building blocks of modern silicon-based microelectronics, such as double gate transistors in non-volatile Flash memories, are based on the control of electrical resistance by electrostatic charging. Flash memories could soon…
Lithium ion batteries are promising for small off- grid energy storage applications in developing countries because of their high energy density and long life. However, costs are prohibitive. Instead, we consider 'used' Li-ion batteries for…
Model inversion attacks (MIAs) aim to create synthetic images that reflect the class-wise characteristics from a target classifier's private training data by exploiting the model's learned knowledge. Previous research has developed…
Autonomous vehicles, including self driving cars, ground robots, and drones, rely on multi-modal sensor pipelines for safe operation, yet remain vulnerable to adversarial sensor attacks. A critical gap is the lack of a systematic end-to-end…
Although the adverse effects of using power electronic conversion on the insulation systems used in different apparatuses have been investigated, they are limited to low slew rates and repetitions. These results cannot be used for…
Cloud-based battery management system (BMS) requires accurate terminal voltage measurement data to ensure optimal and safe charging of Lithium-ion batteries. Unfortunately, an adversary can corrupt the battery terminal voltage data as it…
Not long ago, it was thought that only software applications and general purpose digital systems i.e. computers were prone to various types of attacks against their security. The underlying hardware, hardware implementations of these…
Modular battery integrated converters or so called dynamically reconfigurable battery packs are expanding into emerging applications, including electromobility and grid storage. Although they offer many degrees of freedom, the state of the…
This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. Prior work has shown that an attacker-defender bi-level linear program (ADBLP) can be used to…
This paper investigates the vulnerability of discrete-time linear time-invariant systems to stealthy sensor attacks during the learning phase. In particular, we demonstrate that a {data-driven} adversary, without access to the system model,…
Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This paper introduces Transient Turn Injection(TTI), a new multi-turn attack technique that…
As AI agents automate critical workloads, they remain vulnerable to indirect prompt injection (IPI) attacks. Current defenses rely on monitoring protocols that jointly evaluate an agent's Chain-of-Thought (CoT) and tool-use actions to…