智能电网中的移动应用安全技术

移动应用技术引入智能电网使其信息系统和网络边界骤然放大,在安全层面引发了一系列重要挑战,具体问题涵盖移动终端、移动网络和移动应用3个领域。文中从智能电网的移动应用场景入手,分析了移动应用安全需求和相应的技术手段,并给出了一个可信的智能电网移动应用安全架构,从而应对智能电网中的移动应用安全威胁。     

Inhibition of nitrogen compounds on the hydrodesulfurization of substituted dibenzothiophenes in light cycle oil

The influence of nitrogen compounds on the hydrodesulfurization (HDS) activities of a series of substituted dibenzothiophenes in light cycle oil (LCO) was studied over a NiMo/Al₂O₃ commercial catalyst. Three types of light cycle oil with nitrogen compounds of different concentrations and chemical natures were used as feed—an original fluid catalytic cracking light cycle oil (LCO), LCO with most of its basic nitrogen removed, and an ultra-low nitrogen LCO. Experiments were conducted in a fixed-bed microreactor at a total pressure of 70 atm, temperatures between 330 and 400 °C, and liquid hourly space velocities (LHSV) in the range of 1.0 to 3.5 h⁻¹. The inhibition effects of nitrogen compounds on the HDS reactivity of the three sulfur groups—total sulfur, hard sulfur, easy sulfur—and 14 specific mono-, di- and tri-alkyl substituted dibenzothiophenes were investigated. The results showed that the HDS rate significantly increased using ultra-low nitrogen LCO. Pseudo first-order rate constants were estimated for the 14 mono-, di- and tri-alkyl substituted dibenzothiophenes. The HDS rates could be classified into three groups based on the position of the substituents. It was found that 4 and 6 substituted dibenzothiophenes had the lowest HDS rates. The HDS rate of the 14 substituted dibenzothiophenes were all increased when the ultra-low nitrogen feed was used. The improvement was greater for 4 and 6 substituted dibenzothiophenes than for those with one of the substituents at either the 4 or 6 positions. This finding indicates that the hydrogenation route is more strongly suppressed than hydrogenolysis route by nitrogen compounds since the hydrogenation route is believed to be the predominant reaction pathway for 4 and 6 alkyl-substituted dibenzothiophenes.     

Mo/γ-Al2O3催化剂制备及催化氧化船用燃料油脱硫

以γ-Al2O3为载体,采用浸渍法制备了负载型催化剂Mo/γ-Al2O3。利用X-射线衍射仪(XRD)、N2-吸附脱附、H2程序升温还原(H2-TPR)等手段对催化剂进行了表征。分别以二苯并噻吩(DBT)、4,6-二甲基二苯并噻吩(4,6-DMDBT)、苯并噻吩(BT)和噻吩(Th)的正辛烷溶液作为模拟燃料油,异丙苯过氧化氢(CHP)为氧化剂,评价了Mo/γ-Al2O3的催化氧化脱硫(ODS)活性;并将Mo/γ-Al2O3催化剂应用于馏分型船用燃料油氧化脱硫。结果表明：Mo/γ-Al2O3催化剂对不同结构的含硫化合物的催化脱硫活性由大到小的顺序为DBT、4,6-DMDBT、BT、Th;Mo/γ-Al2O3上的Al2(MoO4)3为主要活性中心;在反应温度80 ℃、氧/硫原子比5、催化剂用量1.0 g时,硫质量分数为1.6%的船用燃料油的脱硫率可达到82.6%,硫质量分数可以降至0.3%,达到了最新船用燃料油标准硫质量分数低于0.5%的规定。催化剂重复使用10次后,催化剂活性没有明显的降低。     

网络匿名扫描系统设计及优化

针对网络扫描工具在进行扫描时面临的溯源问题，提出了一种匿名网络扫描系统。首先将匿名系统与网络扫描工具结合以实现匿名扫描；然后在现有匿名系统的基础上实现了该系统的本地私有化；接着通过流量分析发现，Nmap的多进程扫描因为代理链的原因会变成单进程扫描而导致其扫描扫描性能较低；最后提出了一种基于多Namp进程并发的性能优化方案，将总体扫描任务分割为多个扫描任务，并分配给多个单独的Nmap进程并行运行。实验结果表明，该性能优化方案的扫描时延接近正常扫描情况下的时延，达到了提高匿名扫描系统性能的目的。因此，该优化后的网络匿名扫描系统在阻碍溯源的同时提升了扫描效率。     

用信息化助力空中力量投送现代化建设

本文阐述了空中投送信息化建设现状和存在的主要问题,论述了的问题产生的根源,分析了基于民航产品推进信息系统建设的必要性和可行性,提出了问题解决得思路、路径和办法,提出了预期前景,对推动空中战略投送信息化建设具有一定的借鉴意义。     

基于区块链的电子签名和印章应用体系设计

在水利信息化推进过程中,电子签名和印章推广应用的需求越来越迫切,水利行业需要电子签名和印章的互认与统一管理,为此提出一种基于区块链的水利行业电子签名和印章应用体系的设计方案。通过将区块链应用于水利行业电子签名和印章场景,实现水利行业电子签名和印章的互认与统一管理。方案改进传统基于第三方信任机构的电子签名和印章应用,使用区块链技术,基于国密SM2算法的无证书公钥密码体系,降低信息泄露风险,提高电子签名和印章应用的适用性,同时依托区块链的防伪、防篡改、可追溯等特性,实现对电子印章生命周期的全程管理。     

HTTP malicious traffic detection method based on hybrid structure deep neural network

In response to the HTTP malicious traffic detection problem,a preprocessing method based on cutting mechanism and statistical association was proposed to perform statistical information correlation as well as normalization processing of traffic.Then,a hybrid neural network was proposed based on the combination of raw data and empirical feature engineering.It combined convolutional neural network (CNN) and multilayer perceptron (MLP) to process text and statistical information.The effect of the model was significantly improved compared with traditional machine learning algorithms (e.g.,SVM).The F₁value reached 99.38% and had a lower time complexity.At the same time,a data set consisting of more than 450 000 malicious traffic and more than 20 million non-malicious traffic was created.In addition,prototype system based on model was designed with detection precision of 98.1%~99.99% and recall rate of 97.2%~99.5%.The application is excellent in real network environment.     

Aircraft Auto-detection in Domestic High Resolution Remote SensingImages Using Deep-learning

It is of great significance to automatically detect aircrafts from remote sensing imagery to get their locations.However,due to aircraft posture variance,complicated background and incomplete outlines,it is challenging to achieve a high aircraft detection accuracy.Traditional aircraft detection methods are usually based on hand\|crafted features and machine learning based classifiers,which is not robust enough for the translation and rotation variations.To tackle the above issues,this paper introduces deep convolutional neural network and the strategy of transfer learning to detect aircrafts from Chinses domestic satellite remote sensing images.Specifically,this paper first constructs an aircraft sample database,which consists aircrafts of different sizes and poses.Afterwards,YOLO V2 trained with natural images is utilized as the detection model and is further fine\|tuned with aircraft samples to increase the robustness and performance.Experiments were done on the Shanghai Pudong airport from Chinese GF\|2 remote sensing data.Experimental results showed a good performance with a recall of 92.25% and a precision of 94.93%.It is indicated that deep learning together with model transfer can get a high aircraft detection accuracy with limited training samples.The method in this paper can be generalized to other land object detection problems which shows a good promotional value.     

机器学习中成员推理攻击和防御研究综述

机器学习被广泛应用于各个领域, 已成为推动各行业革命的强大动力, 极大促进了人工智能的繁荣与发展。同时, 机器学习模型的训练和预测均需要大量数据, 而这些数据可能包含隐私信息, 导致其隐私安全面临严峻挑战。成员推理攻击主要通过推测一个数据样本是否被用于训练目标模型来破坏数据隐私, 其不仅可以破坏多种机器学习模型(如, 分类模型和生成模型)的数据隐私, 而且其隐私泄露也渗透到图像分类、语音识别、自然语言处理、计算机视觉等领域, 这对机器学习的长远发展产生了极大的安全威胁。因此, 为了提高机器学习模型对成员推理攻击的安全性, 本文从机器学习隐私安全攻防角度, 全面系统性分析和总结了成员推理攻击和防御的基本原理和特点。首先, 介绍了成员推理攻击的定义、威胁模型, 并从攻击原理、攻击场景、背景知识、攻击的目标模型、攻击领域、攻击数据集大小六个方面对成员推理攻击进行分类, 比较不同攻击的优缺点; 然后, 从目标模型的训练数据、模型类型以及模型的过拟合程度三个角度分析成员推理攻击存在原因, 并从差分隐私、正则化、数据增强、模型堆叠、早停、信任分数掩蔽和知识蒸馏七个层面对比分析不同防御措施; 接着, 归纳总结了成员推理攻击和防御常用的评估指标和数据集, 以及其在其他方面的应用。最后, 通过对比分析已有成员推理攻击和防御的优缺点, 对其面临的挑战和未来研究方向进行了展望。     

基于辫子群的不经意传输协议

分析指出现有辫子群上的不经意传输协议通过辫元的指数形式隐藏接收者的选择信息进而保证其隐私性,辫元指数形式的存在导致该协议计算效率较低。基于辫子群上同时共轭搜索问题和分解问题的难解性,提出了一个N取M不经意传输协议,当M=1时对应协议比现有协议的计算效率更高。