A New Class of Attacks on Time Series Data Mining

Traditional research on preserving privacy in data mining focuses on time-invariant privacy issues. With the emergence of time series data mining, traditional snapshot-based privacy issues need to be extended to be multi-dimensional with the addition of time dimension. We find current techniques to preserve privacy in data mining are not effective in preserving time-domain privacy. We present the data flow separation attack on privacy in time series data mining, which is based on blind source separation techniques from statistical signal processing. Our experiments with real data show that this attack is effective. By combining the data flow separation method and the frequency matching method, an attacker can identify data sources and compromise time-domain privacy. We propose possible countermeasures to the data flow separation attack in the paper

A New Class of Attacks on Time Series Data Mining

Traditional research on preserving privacy in data mining focuses on time-invariant privacy issues. With the emergence of time series data mining, traditional snapshot-based privacy issues need to be extended to be multi-dimensional with the addition of time dimension. We find current techniques to preserve privacy in data mining are not effective in preserving time-domain privacy. We present the data flow separation attack on privacy in time series data mining, which is based on blind source separation techniques from statistical signal processing. Our experiments with real data show that this attack is effective. By combining the data flow separation method and the frequency matching method, an attacker can identify data sources and compromise time-domain privacy. We propose possible countermeasures to the data flow separation attack in the paper

Experimental study on secondary bearing mechanism of weakly cemented broken rock mass

In order to study the secondary bearing mechanism of weakly cemented broken surrounding rock, the surface of granite, limestone and mudstone broken rock samples were poured by cement slurry, and the weakly cemented rock mass was formed by static pressure infiltration method, and then an uniaxial loading test was carried out. The results show that the weakly cemented broken rock mass has a certain bearing capacity, but the bearing capacity is low, and the dispersion is high. The secondary bearing capacity of weakly cemented rock mass is affected by factors such as broken rock strength, rock particle size and rock gradation. The larger the rock particle size and strength are, the higher the secondary bearing capacity of the weakly cemented rock mass is. The average bearing capacity of the mudstone weak cementation specimen is 18.77 kN, and the residual bearing capacity is 1.46 kN, and a dispersion coefficient is 0.34. The average bearing capacity of granite is 343.65 kN, and the residual carrying capacity is 25.81 kN, and a dispersion coefficient is 0.11. The average bearing capacity of limestone is 367.22 kN, and the residual carrying capacity is 22.78 kN, and a dispersion coefficient is 0.3. After a certain grading, the average residual secondary bearing capacity of the weakly cemented rock mass is obviously improved, and the dispersion coefficient of peak bearing capacity is reduced. The grading scheme 1 has an average peak carrying capacity of 330.06 kN, a residual carrying capacity of 34.56 kN, and a dispersion coefficient is 0.07. The averaging scheme 2 has an average peak carrying capacity of 297.8 kN, a residual carrying capacity of 29.86 kN, and a dispersion coefficient is 0.14. The cementation regeneration mechanism of the broken rock mass mainly includes the cement-bonding effect of the cement slurry inside and on the broken rock mass. Under the loaded condition, the internal load-bearing network of the broken rock mass is the main mechanism for the secondary load of the broken rock mass, and the stability of the force-chain network is affected by the constraint. After the loss of the confinement, the force chain network fails, and the residual secondary bearing mechanism of the weakly cemented broken rock mass is transformed into the friction between the broken rock masses in the residual core rock pillar

COVER: A Heuristic Greedy Adversarial Attack on Prompt-based Learning in Language Models

Prompt-based learning has been proved to be an effective way in pre-trained language models (PLMs), especially in low-resource scenarios like few-shot settings. However, the trustworthiness of PLMs is of paramount significance and potential vulnerabilities have been shown in prompt-based templates that could mislead the predictions of language models, causing serious security concerns. In this paper, we will shed light on some vulnerabilities of PLMs, by proposing a prompt-based adversarial attack on manual templates in black box scenarios. First of all, we design character-level and word-level heuristic approaches to break manual templates separately. Then we present a greedy algorithm for the attack based on the above heuristic destructive approaches. Finally, we evaluate our approach with the classification tasks on three variants of BERT series models and eight datasets. And comprehensive experimental results justify the effectiveness of our approach in terms of attack success rate and attack speed. Further experimental studies indicate that our proposed method also displays good capabilities in scenarios with varying shot counts, template lengths and query counts, exhibiting good generalizability

Explaining Income-Related Inequalities in Dietary Knowledge: Evidence from the China Health and Nutrition Survey

Lack of adequate dietary knowledge may result in poor health conditions. This study aims to measure income-related inequality in dietary knowledge, and to explain the sources of the inequality. Data were from the China Health and Nutrition Survey (CHNS) conducted in 2015. A summary of the dietary knowledge score and dietary guideline awareness was used to measure the dietary knowledge of respondents. The concentration index was employed as a measure of socioeconomic inequality and was decomposed into its determining factors. The study found that the proportion of respondents who correctly answered questions on dietary knowledge was significantly low for some questions. Compared to rural residents, urban residents had a higher proportion of correctly answered dietary knowledge questions. In addition, there are pro-rich inequalities in dietary knowledge. This observed inequality is determined not only by individual factors but also high-level area factors. Our study recommends that future dietary education programs could take different strategies for individuals with different educational levels and focus more on disadvantaged people. It would be beneficial to consider local dietary habits in developing education materials

CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market

In recent years, great advances in pre-trained language models (PLMs) have sparked considerable research focus and achieved promising performance on the approach of dense passage retrieval, which aims at retrieving relative passages from massive corpus with given questions. However, most of existing datasets mainly benchmark the models with factoid queries of general commonsense, while specialised fields such as finance and economics remain unexplored due to the deficiency of large-scale and high-quality datasets with expert annotations. In this work, we propose a new task, policy retrieval, by introducing the Chinese Stock Policy Retrieval Dataset (CSPRD), which provides 700+ prospectus passages labeled by experienced experts with relevant articles from 10k+ entries in our collected Chinese policy corpus. Experiments on lexical, embedding and fine-tuned bi-encoder models show the effectiveness of our proposed CSPRD yet also suggests ample potential for improvement. Our best performing baseline achieves 56.1% MRR@10, 28.5% NDCG@10, 37.5% Recall@10 and 80.6% Precision@10 on dev set