arXiv subjects

Chun-Ying Huang

Publications and source records attributed to Chun-Ying Huang.

22 records · Page 2Linked to original sources

arXiv2023

DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase

Differentially private synthetic data is a promising alternative for sensitive data release. Many differentially private generative models have been proposed in the literature. Unfortunately, they all suffer from the low utility of the synthetic data, particularly for images of high resolutions. Here, we propose DPAF, an effective differentially private generative model for high-dimensional image synthesis. Different from the prior private stochastic gradient descent-based methods that add Gaussian noises in the backward phase during the model training, DPAF adds a differentially private feature aggregation in the forward phase, bringing advantages, including the reduction of information loss in gradient clipping and low sensitivity for the aggregation. Moreover, as an improper batch size has an adverse impact on the utility of synthetic data, DPAF also tackles the problem of setting a proper batch size by proposing a novel training strategy that asymmetrically trains different parts of the discriminator. We extensively evaluate different methods on multiple image datasets (up to images of 128x128 resolution) to demonstrate the performance of DPAF.

cs.CV↗

arXiv2022

Designing magnetic properties in CrSBr through hydrostatic pressure and ligand substitution

The ability to control magnetic properties of materials is crucial for fundamental research and underpins many information technologies. In this context, two-dimensional materials are a particularly exciting platform due to their high degree of tunability and ease of implementation into nanoscale devices. Here we report two approaches for manipulating the A-type antiferromagnetic properties of the layered semiconductor CrSBr through hydrostatic pressure and ligand substitution. Hydrostatic pressure compresses the unit cell, increasing the interlayer exchange energy while lowering the Néel temperature. Ligand substitution, realized synthetically through Cl alloying, anisotropically compresses the unit cell and suppresses the Cr-halogen covalency, reducing the magnetocrystalline anisotropy energy and decreasing the Néel temperature. A detailed structural analysis combined with first-principles calculations reveal that alterations in the magnetic properties are intricately related to changes in direct Cr-Cr exchange interactions and the Cr-anion superexchange pathways. Further, we demonstrate that Cl alloying enables chemical tuning of the interlayer coupling from antiferromagnetic to ferromagnetic, which is unique amongst known two-dimensional magnets. The magnetic tunability, combined with a high ordering temperature, chemical stability, and functional semiconducting properties, make CrSBr an ideal candidate for pre- and post-synthetic design of magnetism in two-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2021

An Empirical Evaluation of Bluetooth-based Decentralized Contact Tracing in Crowds

Digital contact tracing is being used by many countries to help contain COVID-19's spread in a post-lockdown world. Among the various available techniques, decentralized contact tracing that uses Bluetooth received signal strength indication (RSSI) to detect proximity is considered less of a privacy risk than approaches that rely on collecting absolute locations via GPS, cellular-tower history, or QR-code scanning. As of October 2020, there have been millions of downloads of such Bluetooth-based contract-tracing apps, as more and more countries officially adopt them. However, the effectiveness of these apps in the real world remains unclear due to a lack of empirical research that includes realistic crowd sizes and densities. This study aims to fill that gap, by empirically investigating the effectiveness of Bluetooth-based contact tracing in crowd environments with a total of 80 participants, emulating classrooms, moving lines, and other types of real-world gatherings. The results confirm that Bluetooth RSSI is unreliable for detecting proximity, and that this inaccuracy worsens in environments that are especially crowded. In other words, this technique may be least useful when it is most in need, and that it is fragile when confronted by low-cost jamming. Moreover, technical problems such as high energy consumption and phone overheating caused by the contact-tracing app were found to negatively influence users' willingness to adopt it. On the bright side, however, Bluetooth RSSI may still be useful for detecting coarse-grained contact events, for example, proximity of up to 20m lasting for an hour. Based on our findings, we recommend that existing contact-tracing apps can be re-purposed to focus on coarse-grained proximity detection, and that future ones calibrate distance estimates and adjust broadcast frequencies based on auxiliary information.

cs.CY↗

arXiv2016

Decapitation via Digital Epidemics: A Bio-Inspired Transmissive Attack

The evolution of communication technology and the proliferation of electronic devices have rendered adversaries powerful means for targeted attacks via all sorts of accessible resources. In particular, owing to the intrinsic interdependency and ubiquitous connectivity of modern communication systems, adversaries can devise malware that propagates through intermediate hosts to approach the target, which we refer to as transmissive attacks. Inspired by biology, the transmission pattern of such an attack in the digital space much resembles the spread of an epidemic in real life. This paper elaborates transmissive attacks, summarizes the utility of epidemic models in communication systems, and draws connections between transmissive attacks and epidemic models. Simulations, experiments, and ongoing research challenges on transmissive attacks are also addressed.

cs.CR↗