Differential Privacy for the Vast Majority

Bibliometric Analysis of Marine Traditional Chinese Medicine in Pharmacopoeia of the People's Republic of China: Development, Differences, and Trends Directions

Background

Marine traditional Chinese medicine (MTCM) is a class of traditional medicine that has antitumor, anti-inflammatory, and antiviral properties. Bibliometric approaches were used in this study to conduct systematic research in order to gain a complete picture of MTCM research around the world.

Methods

CiteSpace and NoteExpress software were utilized as tools to examine the information about authors, sources, keywords, etc. Chinese publications were collected from the CNKI, VIP, and WANFANG databases; English publications were collected from the Web of Science database.

Results

A total of 10080 publications were screened, and the search volume of Chinese literature is greater than that of English literature; Nanjing University of Chinese Medicine, China, and Jeju National University, South Korea, published a greater number of articles than other institutions; the scholars Zhaohui-Zhang and Youjin-Jeon have published the highest number of articles in the world. MTCM of shells was often researched for inorganic elements, and data mining methods were applied frequently; MTCM of animals was commonly used for antifatigue and was taken authenticity identification owing to the scarcity of resources; scholars conducted the most research on MTCM of plants, this category usually for antitumor, anti-inflammatory, and antioxidant purposes, and the mechanisms of action were studied in depth. The Chinese literature has undertaken a multifaceted research study based on the theories of processing and the nature of TCM. In the English literature, in-depth studies have been done from the perspectives of the mechanism of action, the extraction and purification of active substances, etc.

Conclusions

According to the analysis of keywords, different medicinal parts present their own special research directions, and different research hotspots have also emerged under different medical theories. The development of MTCM is moving in the direction of standardization and modernization, thanks to the development of cross-disciplinary research as well as the use of several new technologies and statistical techniques.

Differential Privacy via Haar Wavelet Transform and Gaussian Mechanism for Range Query

Range query is the hot topic of the privacy-preserving data publishing. To preserve privacy, the large range query means more accumulate noise will be injected into the input data. This study presents a research on differential privacy for range query via Haar wavelet transform and Gaussian mechanism. First, the noise injected into the input data via Laplace mechanism is analyzed, and we conclude that it is difficult to judge the level of privacy protection based on the Haar wavelet transform and Laplace mechanism for range query because the sum of independent random Laplace variables is not a variable of a Laplace distribution. Second, the method of injecting noise into Haar wavelet coefficients via Gaussian mechanism is proposed in this study. Finally, the maximum variance for any range query under the framework of Haar wavelet transform and Gaussian mechanism is given. The analysis shows that using Haar wavelet transform and Gaussian mechanism, we can preserve the differential privacy for each input data and any range query, and the variance of noise is far less than that just using the Gaussian mechanism. In an experimental study on the dataset age extracted from IPUM's census data of the United States, we confirm that the proposed mechanism has much smaller maximum variance of noises than the Gaussian mechanism for range-count queries.

Privacy and Confidentiality in Process Mining: Threats and Research Challenges

Privacy and confidentiality are very important prerequisites for applying process mining to comply with regulations and keep company secrets. This article provides a foundation for future research on privacy-preserving and confidential process mining techniques. Main threats are identified and related to a motivation application scenario in a hospital context as well as to the current body of work on privacy and confidentiality in process mining. A newly developed conceptual model structures the discussion that existing techniques leave room for improvement. This results in a number of important research challenges that should be addressed by future process mining research.