Property Inference Attacks Against GANs

While machine learning (ML) has made tremendous progress during the past decade, recent research has shown that ML models are vulnerable to various security and privacy attacks. So far, most of the attacks in this field focus on discriminative models, represented by classifiers. Meanwhile, little attention has been paid to the security and privacy risks of generative models, such as generative adversarial networks (GANs). In this paper, we propose the first set of training dataset property inference attacks against GANs. Concretely, the adversary aims to infer the macro-level training dataset property, i.e., the proportion of samples used to train a target GAN with respect to a certain attribute. A successful property inference attack can allow the adversary to gain extra knowledge of the target GAN’s training dataset, thereby directly violating the intellectual property of the target model owner. Also, it can be used as a fairness auditor to check whether the target GAN is trained with a biased dataset. Besides, property inference can serve as a building block for other advanced attacks, such as membership inference. We propose a general attack pipeline that can be tailored to two attack scenarios, including the full black-box setting and partial black-box setting. For the latter, we introduce a novel optimization framework to increase the attack efficacy. Extensive experiments over four representative GAN models on five property inference tasks show that our attacks achieve strong performance. In addition, we show that our attacks can be used to enhance the performance of membership inference against GANs

Teacher Model Fingerprinting Attacks Against Transfer Learning

Transfer learning has become a common solution to address training data scarcity in practice. It trains a specified student model by reusing or fine-tuning early layers of a well-trained teacher model that is usually publicly available. However, besides utility improvement, the transferred public knowledge also brings potential threats to model confidentiality, and even further raises other security and privacy issues. In this paper, we present the first comprehensive investigation of the teacher model exposure threat in the transfer learning context, aiming to gain a deeper insight into the tension between public knowledge and model confidentiality. To this end, we propose a teacher model fingerprinting attack to infer the origin of a student model, i.e., the teacher model it transfers from. Specifically, we propose a novel optimizationbased method to carefully generate queries to probe the student model to realize our attack. Unlike existing model reverse engineering approaches, our proposed fingerprinting method neither relies on fine-grained model outputs, e.g., posteriors, nor auxiliary information of the model architecture or training dataset. We systematically evaluate the effectiveness of our proposed attack. The empirical results demonstrate that our attack can accurately identify the model origin with few probing queries. Moreover, we show that the proposed attack can serve as a stepping stone to facilitating other attacks against machine learning models, such as model stealing

Regression analysis result.

With the changes of social and economic development, more and more people pay attention to the development of non-profit organizations, and the performance research of non-profit organizations has become the focus of research. As the internal governance organization of non-profit organization, the board of directors and the management organization are related internal factors that will affect the organizational performance of non-profit organization. Based on the data of Form 990 of the US Internal Revenue Service, this paper conducted an empirical study on the relationship between internal governance and organizational performance of non-profit organizations, and studied the moderating effects of board size, average weekly working hours, number of managers, members’ work involvement and compensation incentives on internal governance and organizational performance of non-profit organizations. The results show that the number of managers in non-profit organizations is negatively correlated with organizational performance, the average weekly working hours of managers are significantly correlated with organizational performance, and the compensation of managers is significantly correlated with organizational performance. Through the empirical demonstration, this study promotes the management and development practice of non-profit organizations, and lays a solid foundation for the construction of socialist harmonious society in China.</div

Common factor eigenvalues and contribution rates.

With the changes of social and economic development, more and more people pay attention to the development of non-profit organizations, and the performance research of non-profit organizations has become the focus of research. As the internal governance organization of non-profit organization, the board of directors and the management organization are related internal factors that will affect the organizational performance of non-profit organization. Based on the data of Form 990 of the US Internal Revenue Service, this paper conducted an empirical study on the relationship between internal governance and organizational performance of non-profit organizations, and studied the moderating effects of board size, average weekly working hours, number of managers, members’ work involvement and compensation incentives on internal governance and organizational performance of non-profit organizations. The results show that the number of managers in non-profit organizations is negatively correlated with organizational performance, the average weekly working hours of managers are significantly correlated with organizational performance, and the compensation of managers is significantly correlated with organizational performance. Through the empirical demonstration, this study promotes the management and development practice of non-profit organizations, and lays a solid foundation for the construction of socialist harmonious society in China.</div

Factor load and factor score load.

With the changes of social and economic development, more and more people pay attention to the development of non-profit organizations, and the performance research of non-profit organizations has become the focus of research. As the internal governance organization of non-profit organization, the board of directors and the management organization are related internal factors that will affect the organizational performance of non-profit organization. Based on the data of Form 990 of the US Internal Revenue Service, this paper conducted an empirical study on the relationship between internal governance and organizational performance of non-profit organizations, and studied the moderating effects of board size, average weekly working hours, number of managers, members’ work involvement and compensation incentives on internal governance and organizational performance of non-profit organizations. The results show that the number of managers in non-profit organizations is negatively correlated with organizational performance, the average weekly working hours of managers are significantly correlated with organizational performance, and the compensation of managers is significantly correlated with organizational performance. Through the empirical demonstration, this study promotes the management and development practice of non-profit organizations, and lays a solid foundation for the construction of socialist harmonious society in China.</div

Table_1_Interactions Between Marine Group II Archaea and Phytoplankton Revealed by Population Correlations in the Northern Coast of South China Sea.XLSX

Marine Group II (MGII) archaea (Poseidoniales) are the most abundant surface marine planktonic archaea and are widely distributed in both coastal and pelagic waters. The factors affecting their distribution and activity are poorly understood. MGII archaea have the metabolic potential to utilize algae-derived organic matter and are frequently observed in high abundance during or following phytoplankton blooms, suggesting that they are key players of the marine food web. In this study, we studied interactions between MGII archaea and the diverse taxa of phytoplankton in the northern coast of South China Sea. Non-metric multidimensional scaling and cluster analyses demonstrated distinct MGII community patterns in the Pearl River plume (PRP) and the open regions of the northern South China Sea (ONSCS), with MGIIb dominating the former and MGIIa and MGIIb showing remarkable variations in the latter for the same sampling season. Nevertheless, positive correlations (Pearson correlation: R > 0.8 and P < 0.01) in absolute abundances of ribosomal RNA (rRNA)-derived complementary DNA and rRNA genes from network analyses were found between MGII archaea and phytoplankton (cyanobacteria, haptophytes, and stramenopiles in both PRP and ONSCS) among different particle size fractions, indicating their intrinsic relationships under changing environmental conditions. The results of this study may shed light on the multiple interactions between co-existing species in the micro-niches of different oceanic regions.</p

Additional file 10 of Integrated transcriptome and proteome revealed that the declined expression of cell cycle-related genes associated with follicular atresia in geese

Additional file 10: Table S7. KEGG enrichment of differentially expressed genes between normal and atretic follicles

The original data was shown in supporting information.

The original data was shown in supporting information.</p

Additional file 11 of Integrated transcriptome and proteome revealed that the declined expression of cell cycle-related genes associated with follicular atresia in geese

Additional file 11: Table S8. The expression of all proteins in the goose follicles

Additional file 3 of Integrated transcriptome and proteome revealed that the declined expression of cell cycle-related genes associated with follicular atresia in geese

Additional file 3: Fig. S3. (a) Western blotting of MMP3 protein in normal and atretic follicles. The remaining three bands, also normal follicles, were cropped out of the manuscript picture. (b) Western blotting of MMP9 protein in normal and atretic follicles. (c) Western blotting of ACTIN protein. AF-1, AF-2 and AF-3 represent the three repeats of atreated follicles, while NF-1, NF-2 and NF-3 represent the three repeats of normal follicles. The red area is the cropped area in the manuscript. The PVDF membrane was cut before incubation with antibodies