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...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。展开更多
CO_(2)electrochemical reduction reaction(CO_(2)RR)to formate is a hopeful pathway for reducing CO_(2)and producing high-value chemicals,which needs highly selective catalysts with ultra-broad potential windows to meet...CO_(2)electrochemical reduction reaction(CO_(2)RR)to formate is a hopeful pathway for reducing CO_(2)and producing high-value chemicals,which needs highly selective catalysts with ultra-broad potential windows to meet the industrial demands.Herein,the nanorod-like bimetallic ln_(2)O_(3)/Bi_(2)O_(3)catalysts were successfully synthesized by pyrolysis of bimetallic InBi-MOF precursors.The abundant oxygen vacancies generated from the lattice mismatch of Bi_(2)O_(3)and ln_(2)O_(3)reduced the activation energy of CO_(2)to*CO_(2)·^(-)and improved the selectivity of*CO_(2)·^(-)to formate simultaneously.Meanwhile,the carbon skeleton derived from the pyrolysis of organic framework of InBi-MOF provided a conductive network to accelerate the electrons transmission.The catalyst exhibited an ultra-broad applied potential window of 1200 mV(from-0.4 to-1.6 V vs RHE),relativistic high Faradaic efficiency of formate(99.92%)and satisfactory stability after 30 h.The in situ FT-IR experiment and DFT calculation verified that the abundant oxygen vacancies on the surface of catalysts can easily absorb CO_(2)molecules,and oxygen vacancy path is dominant pathway.This work provides a convenient method to construct high-performance bimetallic catalysts for the industrial application of CO_(2)RR.展开更多
Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the comp...Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.展开更多
To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,...To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.展开更多
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 malwar...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.展开更多
Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron.Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW.Results of a...Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron.Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW.Results of a cold test and tuning procedures are described.The final measured S11 curves under the required bandwidth are less than-32.0 and-26.9 dB for alumina and beryllia windows,respectively.The windows are tested up to CW 143 kW for traveling waves and CW 110 kW for standing waves using a solid-state amplifier as an RF power source.Multipactor simulations for windows and benchmark studies for the thermal analysis of ceramic disks are introduced.展开更多
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 st...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.展开更多
Purpose: We aimed to investigate the effects of installing false windows next to hospital beds without windows on the amount of light received by patients and their sleep quality. Methods: The study included patients ...Purpose: We aimed to investigate the effects of installing false windows next to hospital beds without windows on the amount of light received by patients and their sleep quality. Methods: The study included patients admitted to the Department of Neurology at our hospital between September 2020 and August 2021. An Actigraph device was fitted to patients’ wrist and their beds to measure the amount of light received and sleep quality. Patients were divided into three groups: bed with a window, aisle bed with a false window, and aisle bed without a window. Mean sleep efficiency (%), mean steps (per day), and the amount of light (lux) received by the patients and beds were measured. Results: Valid data were obtained for 48 participants (median age, 66.5 years). There were 23 patients in beds with a window, 13 patients in aisle beds without a false window, and 12 in aisle beds with a false window. No statistically significant differences were found in terms of mean sleep efficiency, number of steps taken, and the amount of light received by the patients (P > 0.05);however, difference in the mean amount of light received by the beds at the location of the bed was statistically significant (P Conclusion: The amount of light that the patient receives is not necessarily affected by the location of the bed or the presence of a false window.展开更多
分析了基于Windows服务器终端的远程信息获取技术,包括Microsoft Windows Server远程桌面服务、远程管理服务及网络管理服务。研究表明,使用Windows Server远程终端可实现信息获取与交互,通过套接字技术及TCP/IP等多种协议可完成Window...分析了基于Windows服务器终端的远程信息获取技术,包括Microsoft Windows Server远程桌面服务、远程管理服务及网络管理服务。研究表明,使用Windows Server远程终端可实现信息获取与交互,通过套接字技术及TCP/IP等多种协议可完成Windows服务器终端通信,结合完成端口可搭建较为完成的系统框架。目前,搭建的系统框架能够满足客户的日常需求、服务器终端信息获取,采用加密技术可完成对隐私信息的网络保护。展开更多
基金financially supported by the National Natural Science Foundation of China(52072409)the Major Scientific and Technological Innovation Project of Shandong Province(2020CXGC010403)+1 种基金the Taishan Scholar Project(No.ts201712020)the Natural Science Foundation of Shandong Province(ZR2021QE062)
文摘CO_(2)electrochemical reduction reaction(CO_(2)RR)to formate is a hopeful pathway for reducing CO_(2)and producing high-value chemicals,which needs highly selective catalysts with ultra-broad potential windows to meet the industrial demands.Herein,the nanorod-like bimetallic ln_(2)O_(3)/Bi_(2)O_(3)catalysts were successfully synthesized by pyrolysis of bimetallic InBi-MOF precursors.The abundant oxygen vacancies generated from the lattice mismatch of Bi_(2)O_(3)and ln_(2)O_(3)reduced the activation energy of CO_(2)to*CO_(2)·^(-)and improved the selectivity of*CO_(2)·^(-)to formate simultaneously.Meanwhile,the carbon skeleton derived from the pyrolysis of organic framework of InBi-MOF provided a conductive network to accelerate the electrons transmission.The catalyst exhibited an ultra-broad applied potential window of 1200 mV(from-0.4 to-1.6 V vs RHE),relativistic high Faradaic efficiency of formate(99.92%)and satisfactory stability after 30 h.The in situ FT-IR experiment and DFT calculation verified that the abundant oxygen vacancies on the surface of catalysts can easily absorb CO_(2)molecules,and oxygen vacancy path is dominant pathway.This work provides a convenient method to construct high-performance bimetallic catalysts for the industrial application of CO_(2)RR.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2024-00437494)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.
基金supported by Natural Science Foundation Project of Gansu Provincial Science and Technology Department(No.1506RJZA084)Gansu Provincial Education Department Scientific Research Fund Grant Project(No.1204-13).
文摘To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.
基金This researchwork is supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R411),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘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.
文摘Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron.Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW.Results of a cold test and tuning procedures are described.The final measured S11 curves under the required bandwidth are less than-32.0 and-26.9 dB for alumina and beryllia windows,respectively.The windows are tested up to CW 143 kW for traveling waves and CW 110 kW for standing waves using a solid-state amplifier as an RF power source.Multipactor simulations for windows and benchmark studies for the thermal analysis of ceramic disks are introduced.
基金supported by the National Natural Science Foundation of China(51902064)the Natural Science Foundation of Guangxi(2022GXNSFFA0350325)+2 种基金the Scientific and Technological Bases and Talents of Guangxi(Guike AD20159073)the special fund for“Guangxi Bagui Scholars”the“Guangxi HundredTalent Program”。
文摘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.
文摘Purpose: We aimed to investigate the effects of installing false windows next to hospital beds without windows on the amount of light received by patients and their sleep quality. Methods: The study included patients admitted to the Department of Neurology at our hospital between September 2020 and August 2021. An Actigraph device was fitted to patients’ wrist and their beds to measure the amount of light received and sleep quality. Patients were divided into three groups: bed with a window, aisle bed with a false window, and aisle bed without a window. Mean sleep efficiency (%), mean steps (per day), and the amount of light (lux) received by the patients and beds were measured. Results: Valid data were obtained for 48 participants (median age, 66.5 years). There were 23 patients in beds with a window, 13 patients in aisle beds without a false window, and 12 in aisle beds with a false window. No statistically significant differences were found in terms of mean sleep efficiency, number of steps taken, and the amount of light received by the patients (P > 0.05);however, difference in the mean amount of light received by the beds at the location of the bed was statistically significant (P Conclusion: The amount of light that the patient receives is not necessarily affected by the location of the bed or the presence of a false window.
文摘分析了基于Windows服务器终端的远程信息获取技术,包括Microsoft Windows Server远程桌面服务、远程管理服务及网络管理服务。研究表明,使用Windows Server远程终端可实现信息获取与交互,通过套接字技术及TCP/IP等多种协议可完成Windows服务器终端通信,结合完成端口可搭建较为完成的系统框架。目前,搭建的系统框架能够满足客户的日常需求、服务器终端信息获取,采用加密技术可完成对隐私信息的网络保护。
