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.     

基于码头闸口数据的集卡周转时间短时预测方法

为给车辆调度优化以及集卡预约系统设计提供重要参考,利用所采集的深圳市某港口的码头闸口数据,建立一种基于数据挖掘的集卡周转时间短时预测方法.首先,通过对码头闸口数据进行分析,获取车辆到达时间分布、任务类型、作业方式等集卡作业特征以及集卡在码头内的周转时间;在此基础上,利用循环神经网络并结合训练集数据,建立集卡作业特征与其周转时间之间的映射关系.其次,为减少随机波动对周转时间预测效果的影响,利用小波分解算法对循环神经网络拟合结果的残差进行高频噪声分离,并通过自回归模型拟合过滤后的低频序列.最后,将拟合后的循环神经网络与自回归模型进行结合,建立一种支持集卡周转时间短时预测的组合模型,并利用测试集数据进行有效性验证.结果 表明,相比单一的循环神经网络,该组合模型可以大幅提升预测精度.     

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.     

结合流形结构与柔性嵌入的多标签特征选择

将线性回归模型与流形结构相结合,构成了弱线性多标签特征选择的联合框架。首先,用最小二乘损失函数来学习回归系数矩阵;其次,通过标签流形结构来学习数据特征的权重矩阵;再次,用L2,1-范数来约束回归系数矩阵和特征权重矩阵,这样既能引导稀疏性,又有利于特征选择。此外,设计并证明了具有收敛性的迭代更新算法来解决上述提出的问题。最后,所提出的方法在多个经典多标签数据集上进行了验证,实验结果表明了所提算法的有效性。     

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。     

Blockage of the NLRP3 inflammasome by MCC950 improves anti-tumor immune responses in head and neck squamous cell carcinoma

The NLRP3 inflammasome is a critical innate immune pathway responsible for producing active interleukin (IL)-1β, which is associated with tumor development and immunity. However, the mechanisms regulating the inflammatory microenvironment, tumorigenesis and tumor immunity are unclear. Herein, we show that the NLRP3 inflammasome was over-expressed in human HNSCC tissues and that the IL-1β concentration was increased in the peripheral blood of HNSCC patients. Additionally, elevated NLRP3 inflammasome levels were detected in tumor tissues of Tgfbr1/Pten 2cKO HNSCC mice, and elevated IL-1β levels were detected in the peripheral blood serum, spleen, draining lymph nodes and tumor tissues. Blocking NLRP3 inflammasome activation using MCC950 remarkably reduced IL-1β production in an HNSCC mouse model and reduced the numbers of myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs) and tumor-associated macrophages (TAMs). Moreover, inhibiting NLRP3 inflammasome activation increased the numbers of CD4⁺ and CD8⁺ T cells in HNSCC mice. Notably, the numbers of exhausted PD-1⁺ and Tim3⁺ T cells were significantly reduced. A human HNSCC tissue microarray showed that NLRP3 inflammasome expression was correlated with the expression of CD8 and CD4, the Treg marker Foxp3, the MDSC markers CD11b and CD33, and the TAM markers CD68 and CD163, PD-1 and Tim3. Overall, our results demonstrate that the NLRP3 inflammasome/IL-1β pathway promotes tumorigenesis in HNSCC and inactivation of this pathway delays tumor growth, accompanied by decreased immunosuppressive cell accumulation and an increased number of effector T cells. Thus, inhibition of the tumor microenvironment through the NLRP3 inflammasome/IL-1β pathway may provide a novel approach for HNSCC therapy.     

Improved hemimorphite flotation using xanthate as a collector with S(Ⅱ) and Pb(Ⅱ) activation

The flotation of hemimorphite using the S(Ⅱ)–Pb(Ⅱ)–xanthate process,which includes sulfidization with sodium sulfide,activation by lead cations,and subsequent flotation with xanthate,was investigated.The flotation results indicated that hemimorphite floats when the S(Ⅱ)–Pb(Ⅱ)–xanthate process is used; a maximum recovery of approximately 90% was obtained.Zeta-potential,contact-angle,scanning electron microscopy–energy-dispersive spectrometry(SEM–EDS),and diffuse-reflectance infrared Fourier transform spectroscopy(DRIFTS) measurements were used to characterize the activation products on the hemimorphite surface and their subsequent interaction with sodium butyl xanthate(SBX).The results showed that a Zn S coating formed on the hemimorphite surface after the sample was conditioned in an Na2 S solution.However,the formation of a Zn S coating on the hemimorphite surface did not improve hemimorphite flotation.With the subsequent addition of lead cations,Pb S species formed on the mineral surface.The formation of the Pb S species on the surface of hemimorphite significantly increased the adsorption capacity of SBX,forming lead xanthate(referred to as chemical adsorption) and leading to a substantial improvement in hemimorphite flotation.Our results indicate that the addition of lead cations is a critical step in the successful flotation of hemimorphite using the sulfidization–lead ion activation–xanthate process.     

An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.