通过交叉验证堆栈和VAD信息检测Windows代码注入

Windows 32/64位代码注入攻击是恶意软件常用的攻击技术,在内存取证领域,现存的代码注入攻击检测技术在验证完整性方面不能处理动态内容,并且在解析内存中数据结构方面无法兼容不同版本的Windows系统。因此提出了通过交叉验证进程堆栈和VAD信息定位注入代码方法,将基于遍历栈帧得到的函数返回地址、模块名等信息结合进程VAD结构来检测函数返回地址、匹配文件名以定位注入代码,并且研发了基于Volatility取证框架的Windows代码注入攻击检测插件codefind。测试结果表明,即使在VAD节点被恶意软件修改,方法仍能够有效定位Windows 32/64位注入代码攻击。

Asymmetric Electrolytes Design for Aqueous Multivalent Metal Ion Batteries

With the rapid development of portable electronics and electric road vehicles,high-energy-density batteries have been becoming front-burner issues.Traditionally,homogeneous electrolyte cannot simultaneously meet diametrically opposed demands of high-potential cathode and low-potential anode,which are essential for high-voltage batteries.Meanwhile,homogeneous electrolyte is difficult to achieve bi-or multi-functions to meet different requirements of electrodes.In comparison,the asymmetric electrolyte with bi-or multi-layer disparate components can satisfy distinct requirements by playing different roles of each electrolyte layer and meanwhile compensates weakness of individual electrolyte.Consequently,the asymmetric electrolyte can not only suppress by-product sedimentation and continuous electrolyte decomposition at the anode while preserving active substances at the cathode for high-voltage batteries with long cyclic lifespan.In this review,we comprehensively divide asymmetric electrolytes into three categories:decoupled liquid-state electrolytes,bi-phase solid/liquid electrolytes and decoupled asymmetric solid-state electrolytes.The design principles,reaction mechanism and mutual compatibility are also studied,respectively.Finally,we provide a comprehensive vision for the simplification of structure to reduce costs and increase device energy density,and the optimization of solvation structure at anolyte/catholyte interface to realize fast ion transport kinetics.

Active and passive modulation of solar light transmittance in a uniquely multifunctional dual-band single molecule for smart window applications

Functional materials may change color by heat and electricity separately or simultaneously in smart windows.These materials have not only demonstrated remarkable potential in the modulation of solar radiation but are also leading to the development of indoor environments that are more comfortable and conducive to improving individuals'quality of life.Unfortunately,dual-responsive materials have not received ample research attention due to economic and technological challenges.As a consequence,the broader utilization of smart windows faces hindrances.To address this new generational multistimulus responsive chromic materials,our group has adopted a developmental strategy to create a poly(NIPAM)n-HV as a switchable material by anchoring active viologen(HV)onto a phase-changing poly(NIPAM)n-based smart material for better utility and activity.These constructed smart windows facilitate individualistic reversible switching,from a highly transparent state to an opaque state(thermochromic)and a red state(electrochromic),as well as facilitate a simultaneous dual-stimuli response reversible switching from a clear transparent state to a fully opaque(thermochromic)and orange(electrochromic)states.Absolute privacy can be attained in smart windows designed for exclusive settings by achieving zero transmittance.Each unique chromic mode operates independently and modulates visible and near-infrared(NIR)light in a distinct manner.Hence,these smart windows with thermal and electric dual-stimuli responsiveness demonstrate remarkable heat regulation capabilities,rendering them highly attractive for applications in building facades,energy harvesting,privacy protection,and color display.

基于Windows/RTX的实时仿测软件设计

针对传统测试软件实时性有限、传统仿真接口软件通用性程度低的问题,为满足半实物仿真软件需兼顾单元测试和控制系统仿真验证的需求,设计了基于Windows/RTX的实时仿测软件。仿测软件采用模块化的设计原则,开发了GUI层人机交互界面和RTX层实时运行程序。为保证实时性,采用无锁循环缓冲区+双线程技术,解决了RTX环境下仿真步长为1 ms时串口数据收发的超时问题;提出一种超时检测算法监测仿真节点的实时状态。借助cJSON优化了测试用例配置文件,用户可以更灵活地编辑测试用例,利用RTW自动代码生成将弹体模型编译集成到RTX仿测软件工程。实验结果表明:该仿测软件有效兼顾了单测与仿真,提高了仿测软件的通用性和二次开发效率,降低了开发难度。

投稿须知

一、特别约定(一)所有投稿文章都应是未经发表的原创作品,请作者根据提示自行将投稿上传到本刊投稿平台:https://openedu.sou.edu.cn。文章查重率不超过10%。杜绝一切抄袭等学术不端行为。为了避免在投稿过程中可能出现浏览器兼容问题导致的无法上传稿件故障,建议使用Windows7和WindowsXP等系统和低版本浏览器。(二)编辑部有权对稿件进行编辑和修改。如有异议,请在来稿的明显位置加以说明,否则视为默许。(三)投稿者可通过投稿平台查看稿件审稿进度。

投稿须知

一、特别约定(一)所有投稿文章都应是未经发表的原创作品,请作者根据提示自行将投稿上传到本刊投稿平台:https://openedu.sou.edu.cn。文章查重率不超过10%。杜绝一切抄袭等学术不端行为。为了避免在投稿过程中可能出现浏览器兼容问题导致的无法上传稿件故障,建议使用Windows7和WindowsXP等系统和低版本浏览器。(二)编辑部有权对稿件进行编辑和修改。如有异议,请在来稿的明显位置加以说明,否则视为默许。(三)投稿者可通过投稿平台查看稿件审稿进度。投稿三个月后,如仍未收到编辑部的任何通知,投稿者可改投其他期刊。投稿期间请勿一稿多投。

Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention mechanisms.Supervised machine learning classifiers have emerged as promising tools for malware detection.However,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware detection.Addressing this gap can provide valuable insights for enhancing cybersecurity strategies.While numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware detection.Understanding the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security measures.This study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows systems.The objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows malware.Evaluating the accuracy,efficiency,and suitability of each classifier for real-world malware detection scenarios.Identifying the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and researchers.Offering recommendations for selecting the most effective classifier for Windows malware detection based on empirical evidence.The study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and evaluation.Exploratory data analysis involves understanding the dataset’s characteristics and identifying preprocessing requirements.Data preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for training.Model training utilizes various supervised classifiers,and their performance is evaluated using metrics such as accuracy,precision,recall,and F1 score.The study’s outcomes comprise a comparative analysis of supervised machine learning classifiers for Windows malware detection.Results reveal the effectiveness and efficiency of each classifier in detecting different types of malware.Additionally,insights into their strengths and limitations provide practical guidance for enhancing cybersecurity defenses.Overall,this research contributes to advancing malware detection techniques and bolstering the security posture of Windows systems against evolving cyber threats.

My Favorite Festival

My favorite festival is the Spring Festival.The Spring Festival falls on the first day of the lunar New Year.There are all kinds of activities during the Spring Festival.To begin with,we clean our houses,paint doors and windows red,put up red couplets,decorate the doors and windows with paper cuts,buy clothes and have a haircut on New Year’s Eve.

电脑美术课的“思”“学”“做”

电脑美术在部编人教版美术教材一至六年级上下册均出现,可见电脑美术在美术教学中不可或缺,是美术教师必须实施的课程。但是很多美术教师对此选择忽略,有的是因为校内无相关设备,有的是因为教师没有这方面的技能。针对以上现象,本文简要阐述笔者对电脑美术课的“思”“学”“做”。

基于CATIA二次开发的汽车产品数据处理

汽车整车零部件设计部门输出的产品数据包含较多的设计信息,工艺部门需要对数据进行处理后再进行其他工艺工装设计,以达到删除不必要的设计信息,保护知识产权,简化数据的目的。各大汽车主机厂对整车零部件数据的处理基本处在人工手动操作的水平上,这完全依赖于CATIA提供的现有功能,即使人员操作熟悉度再高也免不了操作费时费力的状况,同时受人员水平的限制,还会有出现错漏的风险。为解决上述问题,提出了一种在CATIA中可实现由产品数据批量转换为消参零件方法,并对转化后的零件进行分类优化处理。通过CATIA Automation技术,利用CATIA提供的API以及Windows API,以VBA为载体,利用递归思想,实现了CATIA产品数据的一次性批量处理。通过实例验证可知,二次开发相对于手动操作效率提升极为显著,在进行数据转化处理同时无需人员额外进行监控,人力资源得以释放,不影响人员其他工作的处理;二次开发可以保证数据处理100%准确,避免人员手动操作出现的错漏,为后续工艺工装设计提供坚实的基础。

基于终端DNS协议安全设计缺陷的代偿技术研究

针对DNS协议安全设计缺陷,文章对终端设备本地hosts缓存重定向技术、终端设备应用层DNS代理技术、操作系统内核驱动层DNS阻断技术进行了深入研究,提出了终端设备DNS协议安全设计缺陷代偿技术模型。该模型不仅能从终端设备操作系统底层拦截DNS域名解析请求数据包,还能联动威胁情报。经验证,它能在不影响用户正常体验的前提下对恶意域名进行准确识别和首包拦截,从而满足各行业的企、事业单位员工及供应链人员对终端设备的安全管理需求。

AIPC:重塑PC的未来

5月20日,微软发布了全新PC产品——Windows 11AIPC,将旗下AI助手Copilot全面引入了Windows系统,并将内置OpenAI的GPT—4o模型。AIPC是指硬件上集成了混合AI算力单元,能够本地运行“个人大模型”,创建个性化的本地知识库,实现多模态人机交互的PC终端。AIPC的推出,标志着个人计算设备进入了一个新的时代,也标志着AI技术的进一步集成,预示着PC终端有了全新的发展方向。

基于域控管理的计算机锁屏宣传海报的设计实现

随着信息技术的快速发展,大型信息系统在各领域的应用越来越广泛,核心价值和形象展示在企业、机构乃至政府部门的重要性也越来越高。由于传统的宣传方式难以兼顾时效性、成本、覆盖范围,使得企业在宣传业务上浪费大量的时间、经济成本,且效果无法保证。为了解决上述问题,提出了一种在Windows终端部署、基于域控管理的计算机锁屏宣传海报设计方案,通过统一的的策略中心进行控制。同时结合定制客户端工具,实现Windows客户端锁屏宣传海报的定期更换。这样既方便文宣人员的操作使用,又利用现有设备降低成本,为企业内部信息系统的海报宣传提供了一种新的思路。

快速拓展Windows实时性!史上最小的PLC运动控制器发布

为了解决Windows系统下可视化界面友好、软件开发容易、兼容性好,但无法实现实时性控制;其它带有实时控制功能的系统存在软件平台搭建困难、开发难度高、兼容性差等问题。立迈胜研发了一种NIMC301-A微型运动控制器,可以做到开箱即用,极大地增加了用户的易用性。其自带CANopen主站,具备PLC控制功能,也可为WindoWs平台提供实时性拓展,而体积仅相当于“U盘”大小!

多媒体课件在Windows系统中的个性化创意设计

文章从Windows桌面操作系统中图形界面应用出发,探讨通过个性化的设计方法创建自己的Windows Space,给用户创造出虚拟的桌面和软件界面应用,以多媒体课件的设计为实例,分析了多媒体课件界面设计的组成要素以及运用Flash和Dreamweaver进行个性化创意设计的基本步骤。

基于强化学习的自动化Windows域渗透方法

Windows域为用户之间的资源共享及信息交互提供统一的系统服务,在便利内网管理的同时带来了巨大的安全隐患。近年来,针对域控制器的各式攻击层出不穷,实现自动化渗透能够灵活检测Windows域中存在的漏洞威胁,保障办公网络安全稳定地持久运行,其核心是高效挖掘环境内可行的攻击路径。为此,将渗透测试过程进行强化学习建模,通过智能体与域环境的真实交互发现漏洞组合,进而验证有效的攻击序列;基于主机对渗透进程的贡献差异,减少强化学习模型中非必要的状态与动作,优化路径选择策略,提升实际攻击效率;使用状态动作删减、探索策略优化的Q学习算法筛选最优攻击路径,自动验证域环境中所有可能的安全隐患,为域管理员提供防护依据。实验针对典型内网业务场景展开测试,从生成的13种高效攻击路径中筛选最优路径,通过与相关研究成果对比,突出了所提方法在域控权限获取、主机权限获取、攻击步长、收敛性以及时间代价等方面的性能优化效果。

质子治疗控制系统的逻辑设计研究

质子治疗控制系统是质子治疗装置的配套软件,它具体来协调、控制各子系统之间的状态和工作。该研究初步开展质子治疗控制系统的软件架构和硬件实现设计工作,为整体系统调试打下基础。运用C#编程语言及Windows呈现基础编程框架,质子治疗技术文档给定的传输控制协议网络通信协议和模型-视图-视图模型模式在Windows环境下对软件的各个层次的逻辑设计与实现进行了研究,约定了TCP通信协议之下各个子系统的通信接口,对质子治疗的摆位野和治疗野流程进行了逻辑设计和研究,并采用上述技术对用户界面进行了设计和开发。该程序实现了质子治疗控制系统与各个子系统之间的通信,从而控制和监控整个治疗流程。该质子治疗控制系统为质子治疗装置的远程整体调试以及在线监控提供了软件基础。

移动存储设备跨平台加密技术研究与实现

当前,移动存储设备造成的数据泄露问题日益严重,虽然基于硬件的加密移动存储设备可以有效地进行控制,但是目前市场上流行的加密一定程度上都属于硬件加密,成本高而且加密算法单一,对存储的容量有一定限制,且严重依赖出厂物理硬件;随着以UOS、麒麟等为代表的信创系统崛起和广泛应用,传统在Windows下的基于加密移动存储设备在信创系统和Linux等系统下便无法使用,因此提出了一种跨平台下对移动存储设备进行软件加解密技术方案.在该方案下,注册加密存储数据区经过人机交互界面口令认证才能被系统识别,数据的加解密均是透明无感知的,注册过的移动存储设备,在纯净Windows系统、信创系统(UOS、麒麟等)、纯净Linux系统等环境下,用户体验和存储数据都是一致的.该系统创新性地解决了移动存储设备经加密后在不同系统下的兼容问题,利用加解密技术增强了原数据裸存下的安全性,防止数据泄露事件发生,保护用户的数据安全.

Sol-gel-based porous Ti-doped tungsten oxide films for high-performance dual-band electrochromic smart windows

Dual-band electrochromic smart windows(DESWs)with independent control of the transmittance of near-infrared and visible light show great potential in the application of smart and energy-saving buildings.The current strategy for building DESWs is to screen materials for composite or prepare plasmonic nanocrystal films.These rigorous preparation processes seriously limit the further development of DESWs.Herein,we report a facile and effective sol-gel strategy using a foaming agent to achieve porous Ti-doped tungsten oxide film for the high performance of DESWs.The introduction of foaming agent polyvinylpyrrolidone during the film preparation can increase the specific surface area and free carrier concentration of the films and enhance their independent regulation ability of near-infrared electrochromism.As a result,the optimal film shows excellent dual-band electrochromic properties,including high optical modulation(84.9%at 633 nm and 90.3%at 1200 nm),high coloration efficiency(114.9 cm^(2) C^(-1) at 633 nm and 420.3 cm^(2) C^(-1) at 1200 nm),quick switching time,excellent bistability,and good cycle stability(the transmittance modulation losses at 633 and 1200 nm were 11%and 3.5%respectively after 1000 cycles).A demonstrated DESW fabricated by the sol-gel film showed effective management of heat and light of sunlight.This study represents a significant advance in the preparation of dual-band electrochromic films,which will shed new light on advancing electrochromic technology for future energy-saving smart buildings.

基于KNN分类算法的恶意软件检测

随着科技的发展,层出不穷的恶意软件对用户计算机系统的数据都构成了极大的威胁,如何准确、高效地检测出恶意软件是令人担忧的问题。几十年来,恶意软件检测已引起反恶意软件行业和研究人员的关注。面对日益复杂的恶意软件,需要新的防御技术来检测和打击新奇的攻击和威胁。人工智能、深度学习也为Windows恶意软件检测提供了新的技术。文章研究如何在现有的一些恶意软件检测方法的基础上,改进特征码的提取和检测模型算法,以提高恶意软件检测的准确度,保护用户计算机系统以及数据的安全性。