Threshold signature is a powerful cryptographic technique with a large number of real-life applications. As designed by Boneh and Komlo (CRYPTO’22), TAPS is a new threshold signature integrating privacy and accountability. It allows a combiner to combine t signature shares while protecting t and the signing group from the public. It also enables a tracer to trace a threshold signature to its original signing group. Despite being valuable, TAPS neglects the witnessing of tracing, i.e., leaves the tracing activity unrestrained. In this paper, we introduce Accountable and Private Threshold Signature with Hidden Witnesses (HiTAPS) that not only provides privacy and accountability, but also incorporates witnessed tracing. In specific, we first utilize Dynamic Threshold Public-Key Encryption (DTPKE) and ElGamal encryption to designate a set of t^′ witnesses for endorsing the tracing activity. We then compute a keyed-hash tag for the t^′ witnesses to initiate the tracing activity secretly. Moreover, we present an optimized protocol HiTAPS2 to reduce communication overhead of the combiner. We formalize the definitions, security, and privacy for HiTAPS. We formally prove its security and privacy. To evaluate the performance of HiTAPS and HiTAPS2, we build a prototype based on pypbc. Experimental results show that HiTAPS takes 217(370) ms to combine (track) a threshold signature of 5 signers (witnesses). The optimized HiTAPS2 only takes 137 ms to combine a threshold signature of 5 signers.

This paper deals with the problem of active disturbance rejection control (ADRC) design for a class of uncertain nonlinear systems with sporadic measurements. A novel extended state observer (ESO) is designed in a cascade form consisting of a continuous time estimator, a continuous observation error predictor, and a reset compensator. The proposed ESO estimates not only the system state but also the total uncertainty, which may include the effects of the external perturbation, the parametric uncertainty, and the unknown nonlinear dynamics. Such a reset compensator, whose state is reset to zero whenever a new measurement arrives, is used to calibrate the predictor. Due to the cascade structure, the resulting error dynamics system is presented in a non-hybrid form, and accordingly, analyzed in a general sampled-data system framework. Based on the output of the ESO, a continuous ADRC law is then developed. The convergence of the resulting closed-loop system is proved under given conditions. Two numerical simulations demonstrate the effectiveness of the proposed control method.

A particulate matter micro-sensor for automotive exhaust systems based on a gateless wide-bandgap AlGaN/GaN high electron mobility transistor was developed and tested. Soot particles were generated by a laminar diesel flame and characterized with Raman spectroscopy, thermogravimetric analysis and scanning electron microscopy. Particle adsorption at the rate of 0.25 µg/min on the sensor surface resulted in 5.52% sensing response after 20 s and large signal variation of 4.44 mA, indicating fast response time. Saturated response of 34.72% (27.94 mA) was obtained after 10 min of deposition. The sensitivity towards soot is attributed to the modulation of the two-dimensional electron gas density by charged particles on the sensing surface. After soot deposition, the sensor was successfully regenerated by thermal oxidation of the carbonaceous particles at 600 °C. The sensing response remained unchanged post-regeneration indicating high temperature stability and harsh environment operation compatibility of the demonstrated GaN-based sensor. Nevertheless, interconnect metal optimization is still required to mitigate high-temperature interdiffusion.

O₂ plasma-based digital etching of Al_0.25Ga_0.75N with a 0.8 nm AlN spacer on GaN was investigated using an inductively coupled plasma etcher. Silicon oxide layer was used as the hard mask. At 40 W RF bias power and 40 sccm oxygen flow, the etch depth of Al_0.25Ga_0.75N was 5.7 nm per cycle. The 0.8 nm AlN spacer layer acted as an etch-stop layer in three cycles. The surface roughness improved from 0.66 to 0.33 nm after the three and seven digital etch cycles. Compared to the dry etch only approach, this technique smoothed the surface instead of causing surface roughening. Compared to the selective thermal oxidation with a wet etch approach, this method is less demanding on the epitaxial growth and saves the oxidation process. It was shown to be effective in precisely controlling the AlGaN etch depth required for recessed-AlGaN HEMTs.

Digital etching is an effective method to lower dry etch damages in A1GaN/GaN HEMTs. This work systematically investigated O₂-plasma-based digital etching of AlGaN and p-GaN. AlN layers were used as the etch stop layers in the AlGaN etch. Important process aspects such as the use of the AlN layers, the RF power, the oxygen flow rate, the oxidation time and the resulting roughness were studied. These are technically relevant to obtain controllable, uniform etch surfaces with low surface damages for better HEMT performance.

The number of deployed Internet of Things (IoT) devices is steadily increasing to manage and interact with community assets of smart cities, such as transportation systems and power plants. This may lead to degraded network performance due to the growing amount of network traffic and connections generated by various IoT devices. To tackle these issues, one promising direction is to leverage the physical proximity of communicating devices and inter-device communication to achieve low latency, bandwidth efficiency, and resilient services. In this work, we aim at enhancing the performance of indoor IoT communication (e.g., smart homes, SOHO) by taking advantage of emerging technologies such as visible light and ultrasound. This approach increases the network capacity, robustness of network connections across IoT devices, and provides efficient means to enable distance-bounding services. We have developed communication modules using off-the-shelf components for visible light and ultrasound and evaluate their network performance and energy consumption. In addition, we show the efficacy of our communication modules by applying them in a practical indoor IoT scenario to realize secure IoT group communication.