The Trusted Platform Module （TPM） is a dedicated hardware chip designed to provide a higher level of security for computing platform. All TPM functionalities are implemented in TPM corntrends to achieve specific sec...The Trusted Platform Module （TPM） is a dedicated hardware chip designed to provide a higher level of security for computing platform. All TPM functionalities are implemented in TPM corntrends to achieve specific security goals. We attempt to analyze the security properties of these commands, especially the key management API. Our study utilizes applied pi calculus to forrmlize the commands and determine how their security properties affect TPM key rmnagement. The attacker is assumed to call TPM comrmnds without bounds and without knowing the TPM root key, expecting to obtain or replace the user key. The analysis goal in our study is to guarantee the corre- sponding property of API execution and the integrity of API data. We analyze the security properties of TPM commands with a process reduction method, identify the key-handle hijack attack on a TPM newly created key, and propose reasonable solutions to solve the problem. Then, we conduct an experiment involving a key-handle attack, which suc- cessfully replaces a user key with an attacker＇s key using lmlicious TPM software. This paper discloses the weakness of the relationship between the key handle and the key object. After the TPM software stack is compromised, the attacker can hunch a keyhandle attack to obtain the user key and even break into the whole storage tree of user keys.展开更多
Pure proportional navigation(PPN) is suitable for endoatmospheric interceptions,for its commanded acceleration is perpendicular to interceptor velocity.However,if the target is much faster than the interceptor,the hom...Pure proportional navigation(PPN) is suitable for endoatmospheric interceptions,for its commanded acceleration is perpendicular to interceptor velocity.However,if the target is much faster than the interceptor,the homing performance of PPN will be degraded badly.True proportional navigation(TPN) does not have this problem,but its commanded acceleration is perpendicular to the line of sight(LOS),which is not suitable for endoatmospheric interceptions.The commanded acceleration of differential geometric guidance commands(DGGC) is perpendicular to the interceptor velocity,while the homing performance approximates the LOS referenced guidance laws(PPN series).Therefore,DGGC is suitable for endoatmospheric interception of high-speed targets.However,target maneuver information is essential for the construction of DGGC,and the guidance commands are complex and may be without robustness.Through the deep analysis of three-dimensional engagement,a new construction method of DGGC is proposed in this paper.The target maneuver information is not needed any more,and the robustness of DGGC is guaranteed,which makes the application of DGGC possible.展开更多
学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术...学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术期刊(A+)等。展开更多
学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术...学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术期刊(A+)等。展开更多
学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术...学报简介:《指挥与控制学报》(Journal of Command and Control)是中国指挥与控制学会会刊,由北方自动控制技术研究所和中国指挥与控制学会共同主办,2015年创刊。现为中文核心期刊、CSCD核心期刊、中国科技核心期刊、RCCSE中国权威学术期刊(A+)等。展开更多
With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation ...With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation of synthetic attacks,including XSS(Cross-Site Scripting),SQL Injections,and Command Injections.A web application has been developed that allows penetration testers to quickly generate high-quality payloads without the need for in-depth knowledge of artificial intelligence.The fine-tuned language model demonstrates the capability to produce synthetic payloads that closely resemble real-world attacks.This approach not only improves the model’s precision and dependability but also serves as a practical resource for cybersecurity professionals to enhance the security of web applications.The methodology and structured implementation underscore the importance and potential of advanced language models in cybersecurity,illustrating their effectiveness in generating high-quality synthetic data for penetration testing purposes.The research results demonstrate that this approach enables the identification of vulnerabilities that traditional methods may not uncover,providing deeper insights into potential threats and enhancing overall security measures.The performance evaluation of the model indicated satisfactory results,while further hyperparameter optimization could improve accuracy and generalization capabilities.This research represents a significant step forward in improving web application security and opens new opportunities for the use of LLMs in security testing,thereby contributing to the development of more effective cybersecurity strategies.展开更多
Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in ...Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.展开更多
The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and e...The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.展开更多
In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated...In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.展开更多
Purpose-To optimize train operations,dispatchers currently rely on experience for quick adjustments when delays occur.However,delay predictions often involve imprecise shifts based on known delay times.Real-time and a...Purpose-To optimize train operations,dispatchers currently rely on experience for quick adjustments when delays occur.However,delay predictions often involve imprecise shifts based on known delay times.Real-time and accurate train delay predictions,facilitated by data-driven neural network models,can significantly reduce dispatcher stress and improve adjustment plans.Leveraging current train operation data,these models enable swift and precise predictions,addressing challenges posed by train delays in high-speed rail networks during unforeseen events.Design/methodology/approach-This paper proposes CBLA-net,a neural network architecture for predicting late arrival times.It combines CNN,Bi-LSTM,and attention mechanisms to extract features,handle time series data,and enhance information utilization.Trained on operational data from the Beijing-Tianjin line,it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.Findings-This study evaluates our model’s predictive performance using two data approaches:one considering full data and another focusing only on late arrivals.Results show precise and rapid predictions.Training with full data achieves aMAEof approximately 0.54 minutes and a RMSEof 0.65 minutes,surpassing the model trained solely on delay data(MAE:is about 1.02 min,RMSE:is about 1.52 min).Despite superior overall performance with full data,the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals.For enhanced adaptability to real-world train operations,training with full data is recommended.Originality/value-This paper introduces a novel neural network model,CBLA-net,for predicting train delay times.It innovatively compares and analyzes the model’s performance using both full data and delay data formats.Additionally,the evaluation of the network’s predictive capabilities considers different scenarios,providing a comprehensive demonstration of the model’s predictive performance.展开更多
顶级品质的音响器材,由于其昂贵的价格与稀缺性,对于大多数人而言,平日里能够亲自接触并体验的机会实属难得。就在11月,我们来到了典雅音响花园,试听IsoTek EVO3 Super Titan 20A电源处理器,试听现场刚好搭配了Gryphon贵丰的Commander...顶级品质的音响器材,由于其昂贵的价格与稀缺性,对于大多数人而言,平日里能够亲自接触并体验的机会实属难得。就在11月,我们来到了典雅音响花园,试听IsoTek EVO3 Super Titan 20A电源处理器,试听现场刚好搭配了Gryphon贵丰的Commander指挥官、后级为Gryphon贵丰Apex单声道后级系统。展开更多
This paper develops a WebGIS\|based GPS vehicle monitoring system with typical three\|tier application architecture of B/S pattern. It provides ordinary registered users with a valid and convenient means to get access...This paper develops a WebGIS\|based GPS vehicle monitoring system with typical three\|tier application architecture of B/S pattern. It provides ordinary registered users with a valid and convenient means to get access to real\|time GPS location information of certain moving vehicles at any place, and further offers a powerful tool for super users to manage user information and remotely monitor those vehicles and provide corresponding services timely if necessary. The system architecture, function modules, key technologies and application interfaces are given. Finally, the validity of our system is demonstrated in practical cases.展开更多
基金This paper was supported by the National Natural Science Foundation of China under Grants No.91118006, No. 61202414 the Knowledge Innovation Project of Chinese Academy of Science under Grant No. ISCAS2009-DR14.
文摘The Trusted Platform Module （TPM） is a dedicated hardware chip designed to provide a higher level of security for computing platform. All TPM functionalities are implemented in TPM corntrends to achieve specific security goals. We attempt to analyze the security properties of these commands, especially the key management API. Our study utilizes applied pi calculus to forrmlize the commands and determine how their security properties affect TPM key rmnagement. The attacker is assumed to call TPM comrmnds without bounds and without knowing the TPM root key, expecting to obtain or replace the user key. The analysis goal in our study is to guarantee the corre- sponding property of API execution and the integrity of API data. We analyze the security properties of TPM commands with a process reduction method, identify the key-handle hijack attack on a TPM newly created key, and propose reasonable solutions to solve the problem. Then, we conduct an experiment involving a key-handle attack, which suc- cessfully replaces a user key with an attacker＇s key using lmlicious TPM software. This paper discloses the weakness of the relationship between the key handle and the key object. After the TPM software stack is compromised, the attacker can hunch a keyhandle attack to obtain the user key and even break into the whole storage tree of user keys.
文摘Pure proportional navigation(PPN) is suitable for endoatmospheric interceptions,for its commanded acceleration is perpendicular to interceptor velocity.However,if the target is much faster than the interceptor,the homing performance of PPN will be degraded badly.True proportional navigation(TPN) does not have this problem,but its commanded acceleration is perpendicular to the line of sight(LOS),which is not suitable for endoatmospheric interceptions.The commanded acceleration of differential geometric guidance commands(DGGC) is perpendicular to the interceptor velocity,while the homing performance approximates the LOS referenced guidance laws(PPN series).Therefore,DGGC is suitable for endoatmospheric interception of high-speed targets.However,target maneuver information is essential for the construction of DGGC,and the guidance commands are complex and may be without robustness.Through the deep analysis of three-dimensional engagement,a new construction method of DGGC is proposed in this paper.The target maneuver information is not needed any more,and the robustness of DGGC is guaranteed,which makes the application of DGGC possible.
基金supported by the Ministry of Science,Technological Development and Innovation of the Republic of Serbia,and these results are parts of Grant No.451-03-66/2024-03/200132 with the University of Kragujevac-Faculty of Technical Sciences Cacak.
文摘With the increasing use of web applications,challenges in the field of cybersecurity are becoming more complex.This paper explores the application of fine-tuned large language models(LLMs)for the automatic generation of synthetic attacks,including XSS(Cross-Site Scripting),SQL Injections,and Command Injections.A web application has been developed that allows penetration testers to quickly generate high-quality payloads without the need for in-depth knowledge of artificial intelligence.The fine-tuned language model demonstrates the capability to produce synthetic payloads that closely resemble real-world attacks.This approach not only improves the model’s precision and dependability but also serves as a practical resource for cybersecurity professionals to enhance the security of web applications.The methodology and structured implementation underscore the importance and potential of advanced language models in cybersecurity,illustrating their effectiveness in generating high-quality synthetic data for penetration testing purposes.The research results demonstrate that this approach enables the identification of vulnerabilities that traditional methods may not uncover,providing deeper insights into potential threats and enhancing overall security measures.The performance evaluation of the model indicated satisfactory results,while further hyperparameter optimization could improve accuracy and generalization capabilities.This research represents a significant step forward in improving web application security and opens new opportunities for the use of LLMs in security testing,thereby contributing to the development of more effective cybersecurity strategies.
基金Supported by Zhejiang Provincial Key Research and Development Program(Grant No.2021C04015)。
文摘Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.
基金supported by the Natural Science Foundation Research Plan of Shanxi Province (2023JCQN0728)。
文摘The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.
文摘In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.
基金supported in part by the National Natural Science Foundation of China under Grant 62203468in part by the Technological Research and Development Program of China State Railway Group Co.,Ltd.under Grant Q2023X011+1 种基金in part by the Young Elite Scientist Sponsorship Program by China Association for Science and Technology(CAST)under Grant 2022QNRC001in part by the Youth Talent Program Supported by China Railway Society,and in part by the Research Program of China Academy of Railway Sciences Corporation Limited under Grant 2023YJ112.
文摘Purpose-To optimize train operations,dispatchers currently rely on experience for quick adjustments when delays occur.However,delay predictions often involve imprecise shifts based on known delay times.Real-time and accurate train delay predictions,facilitated by data-driven neural network models,can significantly reduce dispatcher stress and improve adjustment plans.Leveraging current train operation data,these models enable swift and precise predictions,addressing challenges posed by train delays in high-speed rail networks during unforeseen events.Design/methodology/approach-This paper proposes CBLA-net,a neural network architecture for predicting late arrival times.It combines CNN,Bi-LSTM,and attention mechanisms to extract features,handle time series data,and enhance information utilization.Trained on operational data from the Beijing-Tianjin line,it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.Findings-This study evaluates our model’s predictive performance using two data approaches:one considering full data and another focusing only on late arrivals.Results show precise and rapid predictions.Training with full data achieves aMAEof approximately 0.54 minutes and a RMSEof 0.65 minutes,surpassing the model trained solely on delay data(MAE:is about 1.02 min,RMSE:is about 1.52 min).Despite superior overall performance with full data,the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals.For enhanced adaptability to real-world train operations,training with full data is recommended.Originality/value-This paper introduces a novel neural network model,CBLA-net,for predicting train delay times.It innovatively compares and analyzes the model’s performance using both full data and delay data formats.Additionally,the evaluation of the network’s predictive capabilities considers different scenarios,providing a comprehensive demonstration of the model’s predictive performance.
文摘顶级品质的音响器材,由于其昂贵的价格与稀缺性,对于大多数人而言,平日里能够亲自接触并体验的机会实属难得。就在11月,我们来到了典雅音响花园,试听IsoTek EVO3 Super Titan 20A电源处理器,试听现场刚好搭配了Gryphon贵丰的Commander指挥官、后级为Gryphon贵丰Apex单声道后级系统。
文摘This paper develops a WebGIS\|based GPS vehicle monitoring system with typical three\|tier application architecture of B/S pattern. It provides ordinary registered users with a valid and convenient means to get access to real\|time GPS location information of certain moving vehicles at any place, and further offers a powerful tool for super users to manage user information and remotely monitor those vehicles and provide corresponding services timely if necessary. The system architecture, function modules, key technologies and application interfaces are given. Finally, the validity of our system is demonstrated in practical cases.
