Steganalysis of neural networks based on parameter statistical bias

Many pretrained deep learning models have been released to help engineers and researchers develop deep learning-based systems or conduct research with minimall effort. Previous work has shown that at secret message can be embedded in neural network parameters without compromising the accuracy of the model. Malicious developers can, therefore, hide malware or other baneful information in pretrained models, causing harm to society. Hence, reliable detection of these vicious pretrained models is urgently needed. We analyze existing approaches for hiding messages and find that they will ineluctably cause biases in the parameter statistics. Therefore, we propose steganalysis methods for steganography on neural network parameters that extract statistics from benign and malicious models and build classifiers based on the extracted statistics. To the best of our knowledge, this is the first study on neural network steganalysis. The experimental results reveal that our proposed algorithm can effectively detect a model with an embedded message. Notably, our detection methods are still valid in cases where the payload of the stego model is low.     

基于知识图谱的核电设备健康管理知识建模与分析

随着信息技术发展,设备健康数据与知识图谱技术结合为设备健康发展带来新的发展机遇,知识图谱利用其多种特异性优势,使企业系统中积累的海量设备维修数据得到有效整合利用.本文提出基于知识图谱的核电设备健康管理知识建模与分析方法,并根据实体关系模型构建维修知识图谱本体框架,同时基于核电企业实际的维修工单数据,从统计分析和关联分析两方面取得良好的实践效果.研究结果表明,知识图谱能够在设备维修知识的集成上解决传统的数据孤岛问题,同时能基于故障的可视化分析为维修人员和管理人员提供决策和知识支持.     

Impact of the RMB Joining in the SDR Basket on Its Internationalization from the Perspective of Risk Spillover

For evaluating the influence of the Chinese renminbi(RMB) joining in the special drawing right(SDR) basket on RMB's internationalization, the authors systemically study the risk spillover networks and examine the dynamic relationship of exchange rates among the SDR currencies including the US dollar(USD), European Union euro(EUR), Japanese yen(JPY) and British pound(GBP).The empirical results demonstrate that the USD takes a dominant position and holds the biggest risk spillover to other currencies, and the RMB's inclusion to the SDR basket makes the risk spillover to get average, giving rise to the SDR currency system more stable to a certain degree. The inclusion of the RMB in the SDR not only can reduce the systematic risk of the SDR, but also has a certain impact on the international exchange rate markets. Nowadays, in front of the growing trade friction, more such researches could help to effectively deal with the currency disputes.     

双向认知网络物理层安全策略建模及仿真研究

为提高移动通信系统的性能,构建了一个存在主网络干扰和窃听者的双向认知中继网络的物理层安全传输模型,设计了一种中继选择和功率分配的联合优化策略,用于对抗窃听者,保护收发节点的信息传输。通过仿真分析得出,此非凸优化问题限制条件较多,难以保证粒子群优化算法随机生成的初始解的可行性,从而造成求解困难。提出了一种基于可变网格优化和粒子群优化算法的混合优化算法。仿真结果表明此算法提高了次级网络的保密速率,提升了次级网络的安全性能。     

Molecular function of the novel α7β2 nicotinic receptor

The α7 nicotinic receptor is a promising drug target for neurological and inflammatory disorders. Although it is the homomeric member of the family, a novel α7β2 heteromeric receptor has been discovered. To decipher the functional contribution of the β2 subunit, we generated heteromeric receptors with fixed stoichiometry by two different approaches comprising concatenated and unlinked subunits. Receptors containing up to three β2 subunits are functional. As the number of β2 subunits increases in the pentameric arrangement, the durations of channel openings and activation episodes increase progressively probably due to decreased desensitization. The prolonged activation episodes conform the kinetic signature of α7β2 and may have an impact on neuronal excitability. For activation of α7β2 receptors, an α7/α7 binding-site interface is required, thus indicating that the three β2 subunits are located consecutively in the pentameric arrangement. α7-positive allosteric modulators (PAMs) are emerging as novel therapeutic drugs. The presence of β2 in the pentamer affects neither type II PAM potentiation nor activation by an allosteric agonist whereas it impairs type I PAM potentiation. This first single-channel study provides fundamental basis required to decipher the role and function of the novel α7β2 receptor and opens doors to develop selective therapeutic drugs.     

Macropinocytosis,mTORC1 and cellular growth control

The growth and proliferation of metazoan cells are driven by cellular nutrient status and by extracellular growth factors. Growth factor receptors on cell surfaces initiate biochemical signals that increase anabolic metabolism and macropinocytosis, an actin-dependent endocytic process in which relatively large volumes of extracellular solutes and nutrients are internalized and delivered efficiently into lysosomes. Macropinocytosis is prominent in many kinds of cancer cells, and supports the growth of cells transformed by oncogenic K-Ras. Growth factor receptor signaling and the overall metabolic status of the cell are coordinated in the cytoplasm by the mechanistic target-of-rapamycin complex-1 (mTORC1), which positively regulates protein synthesis and negatively regulates molecular salvage pathways such as autophagy. mTORC1 is activated by two distinct Ras-related small GTPases, Rag and Rheb, which associate with lysosomal membranes inside the cell. Rag recruits mTORC1 to the lysosomal surface where Rheb directly binds to and activates mTORC1. Rag is activated by both lysosomal luminal and cytosolic amino acids; Rheb activation requires phosphoinositide 3-kinase, Akt, and the tuberous sclerosis complex-1/2. Signals for activation of Rag and Rheb converge at the lysosomal membrane, and several lines of evidence support the idea that growth factor-dependent endocytosis facilitates amino acid transfer into the lysosome leading to the activation of Rag. This review summarizes evidence that growth factor-stimulated macropinocytosis is essential for amino acid-dependent activation of mTORC1, and that increased solute accumulation by macropinocytosis in transformed cells supports unchecked cell growth.     

A Method to Visualize the Skeleton Industrial Structure with Input-Output Analysis and Its Application in China,Japan and USA

The paper established a double filtering method (DFM) to visualize the skeleton industrial structure (SIS) of one economy and find its evolution rule. Different with the previous researches, this method is from a new view of industrial conjunctions combined by leading sectors to depict the industrial structure. It was proved that the leading sector selected by DFM must be key sector selected by Hirschman-Rasmussen method. Applied DFM to input-output tables of China, Japan and USA and MFA to Japan and USA, the results analysis showed that DFM could overtake the two main shortcomings of minimum flow analysis (MFA), scratch SIS of each economy with its own characteristics, visualize the general evolution rules of the industrial structure with crisscrossed conjunctions among leading sectors.