Attention, Please! Adversarial Defense via Attention Rectification and Preservation

This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change. In particular, we observed that: (1) images with incomplete attention regions are more vulnerable to adversarial attacks; and (2) successful adversarial attacks lead to deviated and scattered attention map. Accordingly, an attention-based adversarial defense framework is designed to simultaneously rectify the attention map for prediction and preserve the attention area between adversarial and original images. The problem of adding iteratively attacked samples is also discussed in the context of visual attention change. We hope the attention-related data analysis and defense solution in this study will shed some light on the mechanism behind the adversarial attack and also facilitate future adversarial defense/attack model design

Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark

Large language models (LLMs) have demonstrated powerful capabilities in both text understanding and generation. Companies have begun to offer Embedding as a Service (EaaS) based on these LLMs, which can benefit various natural language processing (NLP) tasks for customers. However, previous studies have shown that EaaS is vulnerable to model extraction attacks, which can cause significant losses for the owners of LLMs, as training these models is extremely expensive. To protect the copyright of LLMs for EaaS, we propose an Embedding Watermark method called EmbMarker that implants backdoors on embeddings. Our method selects a group of moderate-frequency words from a general text corpus to form a trigger set, then selects a target embedding as the watermark, and inserts it into the embeddings of texts containing trigger words as the backdoor. The weight of insertion is proportional to the number of trigger words included in the text. This allows the watermark backdoor to be effectively transferred to EaaS-stealer's model for copyright verification while minimizing the adverse impact on the original embeddings' utility. Our extensive experiments on various datasets show that our method can effectively protect the copyright of EaaS models without compromising service quality.Comment: Accepted by ACL 202

Connective tissue growth factor is induced in bleomycin-induced skin scleroderma

The origin of fibrotic cells within connective tissue is unclear. For example, the extent to which microvascular pericytes contribute to the number of myofibroblasts present in dermal fibrosis in uncertain. Connective tissue growth factor (CTGF/CCN2) is a marker and mediator of fibrosis. In this report, we use an antibody recognizing CCN2 to assess the cell types in mouse dermis which express CCN2 in the bleomycin model of skin scleroderma. Control (PBS injected) and fibrotic (bleomycin-injected) dermis was examined for CCN2, α-smooth muscle actin (α-SMA) (to detect myofibroblasts), and NG2 (to detect pericytes) expression. Consistent with previously published data, CCN2 expression was largely absent in the dermis of control mice. However, upon exposure to bleomycin, CCN2 was observed in the dermis. Cells that expressed CCN2 were α−SMA-expressing myofibroblasts. Approximately 85% of myofibroblasts were NG2-positive, CCN2-expressing pericytes, indicating that pericytes significantly contributed to the presence of myofibroblasts in sclerotic dermis. Thus CCN2 is induced in fibrotic skin, correlating with the induction of myofibroblast induction. Moreover, CCN2-expressing pericytes significantly contribute to the appearance of myofibroblasts in bleomycin-induced skin scleroderma

Influence of occupation type on the association between sleep duration and impaired fasting glucose: results from a Chinese population-based study

Objectives Systematic evaluation of the influence of occupation type on the association between sleep–glucose metabolismDesign A cross-sectional study.Setting The Nantong Metabolic Syndrome Study is a Chinese population-based study.Participants 20 502 participants aged 18–74 years old.Intervention No intervention.Primary and secondary outcome measures Impaired fasting glucose (IFG).Results A total of 1503 participants (7.33%) with a slightly longer sleep duration had IFG. After being stratified according to occupation, a sleep duration of ≥10 hours daily corresponded to a 1.321-fold risk of IFG (95% CI 1.071 to 1.628, p=0.0092) among moderate and heavy physical workers compared with those with a daily sleep duration of 7–9 hours. There was no significant relationship between sleep and IFG among other types of workers. Moreover, we discovered a gender difference in the influence of occupation on the sleep–IFG. A positive association among moderate and heavy physical men and a negative association among light or sedentary men were established, but not in unemployed men. However, a positive association was evident only in unemployed women; there was no significant association among other occupations.Conclusion This study highlights the role of occupation in the relationship of sleep–glucose metabolism. A gender difference was found to have been influenced by occupational types on the sleep–metabolic association