Based on the wide application of cloud computing and wireless sensor networks in various fields,the Sensor-Cloud System(SCS)plays an indispensable role between the physical world and the network world.However,due to t...Based on the wide application of cloud computing and wireless sensor networks in various fields,the Sensor-Cloud System(SCS)plays an indispensable role between the physical world and the network world.However,due to the close connection and interdependence between the physical resource network and computing resource network,there are security problems such as cascading failures between systems in the SCS.In this paper,we propose a model with two interdependent networks to represent a sensor-cloud system.Besides,based on the percolation theory,we have carried out a formulaic theoretical analysis of the whole process of cascading failure.When the system’s subnetwork presents a steady state where there is no further collapse,we can obtain the largest remaining connected subgroup components and the penetration threshold.Theoretically,this result is the critical maximum that the coupled SCS can withstand.To verify the correctness of the theoretical results,we further carried out actual simulation experiments.The results show that a scale-free network priority attack’s percolation threshold is always less than that of ER network which is priority attacked.Similarly,when the scale-free network is attacked first,adding the power law exponentλcan be more intuitive and more effective to improve the network’s reliability.展开更多
Object detection finds wide application in various sectors,including autonomous driving,industry,and healthcare.Recent studies have highlighted the vulnerability of object detection models built using deep neural netw...Object detection finds wide application in various sectors,including autonomous driving,industry,and healthcare.Recent studies have highlighted the vulnerability of object detection models built using deep neural networks when confronted with carefully crafted adversarial examples.This not only reveals their shortcomings in defending against malicious attacks but also raises widespread concerns about the security of existing systems.Most existing adversarial attack strategies focus primarily on image classification problems,failing to fully exploit the unique characteristics of object detectionmodels,thus resulting in widespread deficiencies in their transferability.Furthermore,previous research has predominantly concentrated on the transferability issues of non-targeted attacks,whereas enhancing the transferability of targeted adversarial examples presents even greater challenges.Traditional attack techniques typically employ cross-entropy as a loss measure,iteratively adjusting adversarial examples to match target categories.However,their inherent limitations restrict their broad applicability and transferability across different models.To address the aforementioned challenges,this study proposes a novel targeted adversarial attack method aimed at enhancing the transferability of adversarial samples across object detection models.Within the framework of iterative attacks,we devise a new objective function designed to mitigate consistency issues arising from cumulative noise and to enhance the separation between target and non-target categories(logit margin).Secondly,a data augmentation framework incorporating random erasing and color transformations is introduced into targeted adversarial attacks.This enhances the diversity of gradients,preventing overfitting to white-box models.Lastly,perturbations are applied only within the specified object’s bounding box to reduce the perturbation range,enhancing attack stealthiness.Experiments were conducted on the Microsoft Common Objects in Context(MS COCO)dataset using You Only Look Once version 3(YOLOv3),You Only Look Once version 8(YOLOv8),Faster Region-based Convolutional Neural Networks(Faster R-CNN),and RetinaNet.The results demonstrate a significant advantage of the proposed method in black-box settings.Among these,the success rate of RetinaNet transfer attacks reached a maximum of 82.59%.展开更多
Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm opt...Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.展开更多
Aiming at the difficulty of unknown Trojan detection in the APT flooding situation, an improved detecting method has been proposed. The basic idea of this method originates from advanced persistent threat （APT） atta...Aiming at the difficulty of unknown Trojan detection in the APT flooding situation, an improved detecting method has been proposed. The basic idea of this method originates from advanced persistent threat （APT） attack intents： besides dealing with damaging or destroying facilities, the more essential purpose of APT attacks is to gather confidential data from target hosts by planting Trojans. Inspired by this idea and some in-depth analyses on recently happened APT attacks, five typical communication characteristics are adopted to describe application’s network behavior, with which a fine-grained classifier based on Decision Tree and Na ve Bayes is modeled. Finally, with the training of supervised machine learning approaches, the classification detection method is implemented. Compared with general methods, this method is capable of enhancing the detection and awareness capability of unknown Trojans with less resource consumption.展开更多
In order to achieve the optimal attack outcome in the air combat under the beyond visual range(BVR)condition,the decision-making(DM)problem which is to set a proper assignment for the friendly fighters on the hostile ...In order to achieve the optimal attack outcome in the air combat under the beyond visual range(BVR)condition,the decision-making(DM)problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack(CMTA).In this paper,a heuristic quantum genetic algorithm(HQGA)is proposed to solve the DM problem.The originality of our work can be supported in the following aspects:(1)the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits(Q-bits);(2)the relative successful sequence probability(RSSP)is defined,based on which the priority attack vector is constructed;(3)the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper;(4)last but not the least,in some special conditions,the HQGA gets rid of the constraint described by other algorithms that to obtain a better result.In the end of this paper,two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.展开更多
A defender–attacker–target problem with non-moving target is considered.This problem is modelled by a pursuit-evasion zero-sum differential game with linear dynamics and quadratic cost functional.In this game,the pu...A defender–attacker–target problem with non-moving target is considered.This problem is modelled by a pursuit-evasion zero-sum differential game with linear dynamics and quadratic cost functional.In this game,the pursuer is the defender,while the evader is the attacker.The objective of the pursuer is to minimise the cost functional,while the evader has two objectives:to maximise the cost functional and to keep a given terminal state inequality constraint.The open-loop saddle point solution of this game is obtained in the case where the transfer functions of the controllers for the defender and the attacker are of arbitrary orders.展开更多
Many complex networks exist to facilitate the transport of material or information.In this capacity,the authors are often concerned with the continued flow of material or information when a fraction of the links in th...Many complex networks exist to facilitate the transport of material or information.In this capacity,the authors are often concerned with the continued flow of material or information when a fraction of the links in the complex network is disrupted.In other words,the authors are interested in the robustness of the complex network.In this paper,the authors survey measures of robustness like the average path length,the average clustering coefficient,the global efficiency,the size of largest cluster and use these to analyze the robustness of the bus network in Hanoi,Vietnam.The authors find that the bus network is robust against random failure but sensitive to targeted attack,in agreement with its scale-free character.By examining sharp drops in the average path length within the largest cluster of the Hanoi bus network under successive targeted attack,the authors identify five nodes whose loss lead to the fragmentation of the network into five or six disconnected clusters.These isolated clusters represent geographically the Central,Western,Southern,and Northwestern districts of Hanoi.Special considerations must therefore be given to these five nodes when planners wish to expand the bus network,or make it more robust.展开更多
The fault tolerance of scale-free networks is examined in this paper. Through the simulation on the changes of the average path length and network fragmentation of the Barabasi-Albert model when faults happen, it can ...The fault tolerance of scale-free networks is examined in this paper. Through the simulation on the changes of the average path length and network fragmentation of the Barabasi-Albert model when faults happen, it can be observed that generic scale-free networks are quite robust to random failures, but are very vulnerable to targeted attacks at the same time. Therefore, an existing optimization strategy for the robustness of scale-free networks to failures and attacks is also introduced. The simulation similar with the above proved that the so-called (1,0) network has potentially interconnectedness closer to that of a scale-free network and robustness to targeted attacks closer to that of an exponential network. Furthermore, its resistance to random failures is better than that of either of them.展开更多
For unmanned aerial vehicle(UAV)swarm dynamic combat,swarm antagonistic motion control and attack target allocation are extremely challenging sub-tasks.In this paper,the competitive learning pigeon-inspired optimizati...For unmanned aerial vehicle(UAV)swarm dynamic combat,swarm antagonistic motion control and attack target allocation are extremely challenging sub-tasks.In this paper,the competitive learning pigeon-inspired optimization(CLPIO)algorithm is proposed to handle the cooperative dynamic combat problem,which integrates the distributed swarm antagonistic motion and centralized attack target allocation.Moreover,the threshold trigger strategy is presented to switch two sub-tasks.To seek a feasible and optimal combat scheme,a dynamic game approach combined with hawk grouping mechanism and situation assessment between sub-groups is designed to guide the solution of the optimal attack scheme,and the model of swarm antagonistic motion imitating pigeon’s intelligence is proposed to form a confrontation situation.The analysis of the CLPIO algorithm shows its convergence in theory and the comparison with the other four metaheuristic algorithms shows its superiority in solving the mixed Nash equilibrium problem.Finally,numerical simulation verifis that the proposed methods can provide an effective combat scheme in the set scenario.展开更多
Wireless Machine to Machine （M2M） communications enable ubiquitous sensing, controlling, and acting via sensors, actuators, and actors. Reliability and security are of foremost importance in wireless M2M systems. A ...Wireless Machine to Machine （M2M） communications enable ubiquitous sensing, controlling, and acting via sensors, actuators, and actors. Reliability and security are of foremost importance in wireless M2M systems. A simple, target distinguishing attack can result in M2M＇s failure. This paper presents a Reliable and SEcure scheme, RISE, which is a package of policies that guarantee the reliability of data （including sensor reports and actuator instructions） and devices （including sensors, actuators, and actors）. The data reliability is improved by four algorithms, ChooseMedian, ChooseMost, ChooseNearest, and Trust-based Enhancement. Report attainability is improved via m repeat-sending and n multiple-reporting algorithms. Device reliability is guaranteed by device-indistinguishability, which comprises data-indistinguishability and behavior-indistinguishability. The security requirements are formally defined, and the security analysis proves the soundness and completeness of the scheme,展开更多
基金supported by National Natural Science Foundation of China under Grant No.62072412,61902359,U1736115in part by the Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security under Grant No.AGK2018001.
文摘Based on the wide application of cloud computing and wireless sensor networks in various fields,the Sensor-Cloud System(SCS)plays an indispensable role between the physical world and the network world.However,due to the close connection and interdependence between the physical resource network and computing resource network,there are security problems such as cascading failures between systems in the SCS.In this paper,we propose a model with two interdependent networks to represent a sensor-cloud system.Besides,based on the percolation theory,we have carried out a formulaic theoretical analysis of the whole process of cascading failure.When the system’s subnetwork presents a steady state where there is no further collapse,we can obtain the largest remaining connected subgroup components and the penetration threshold.Theoretically,this result is the critical maximum that the coupled SCS can withstand.To verify the correctness of the theoretical results,we further carried out actual simulation experiments.The results show that a scale-free network priority attack’s percolation threshold is always less than that of ER network which is priority attacked.Similarly,when the scale-free network is attacked first,adding the power law exponentλcan be more intuitive and more effective to improve the network’s reliability.
文摘Object detection finds wide application in various sectors,including autonomous driving,industry,and healthcare.Recent studies have highlighted the vulnerability of object detection models built using deep neural networks when confronted with carefully crafted adversarial examples.This not only reveals their shortcomings in defending against malicious attacks but also raises widespread concerns about the security of existing systems.Most existing adversarial attack strategies focus primarily on image classification problems,failing to fully exploit the unique characteristics of object detectionmodels,thus resulting in widespread deficiencies in their transferability.Furthermore,previous research has predominantly concentrated on the transferability issues of non-targeted attacks,whereas enhancing the transferability of targeted adversarial examples presents even greater challenges.Traditional attack techniques typically employ cross-entropy as a loss measure,iteratively adjusting adversarial examples to match target categories.However,their inherent limitations restrict their broad applicability and transferability across different models.To address the aforementioned challenges,this study proposes a novel targeted adversarial attack method aimed at enhancing the transferability of adversarial samples across object detection models.Within the framework of iterative attacks,we devise a new objective function designed to mitigate consistency issues arising from cumulative noise and to enhance the separation between target and non-target categories(logit margin).Secondly,a data augmentation framework incorporating random erasing and color transformations is introduced into targeted adversarial attacks.This enhances the diversity of gradients,preventing overfitting to white-box models.Lastly,perturbations are applied only within the specified object’s bounding box to reduce the perturbation range,enhancing attack stealthiness.Experiments were conducted on the Microsoft Common Objects in Context(MS COCO)dataset using You Only Look Once version 3(YOLOv3),You Only Look Once version 8(YOLOv8),Faster Region-based Convolutional Neural Networks(Faster R-CNN),and RetinaNet.The results demonstrate a significant advantage of the proposed method in black-box settings.Among these,the success rate of RetinaNet transfer attacks reached a maximum of 82.59%.
文摘Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.
基金Supported by the National Natural Science Foundation of China (61202387, 61103220)Major Projects of National Science and Technology of China(2010ZX03006-001-01)+3 种基金Doctoral Fund of Ministry of Education of China (2012014110002)China Postdoctoral Science Foundation (2012M510641)Hubei Province Natural Science Foundation (2011CDB456)Wuhan Chenguang Plan Project(2012710367)
文摘Aiming at the difficulty of unknown Trojan detection in the APT flooding situation, an improved detecting method has been proposed. The basic idea of this method originates from advanced persistent threat （APT） attack intents： besides dealing with damaging or destroying facilities, the more essential purpose of APT attacks is to gather confidential data from target hosts by planting Trojans. Inspired by this idea and some in-depth analyses on recently happened APT attacks, five typical communication characteristics are adopted to describe application’s network behavior, with which a fine-grained classifier based on Decision Tree and Na ve Bayes is modeled. Finally, with the training of supervised machine learning approaches, the classification detection method is implemented. Compared with general methods, this method is capable of enhancing the detection and awareness capability of unknown Trojans with less resource consumption.
基金supported by National Nature Science Foundation of China,and the supporting project is“Study on parallel intelligent optimization simulation with combination of qualitative and quantitative method”(61004089)supported by the Graduate Student Innovation Practice Foundation of Beihang University in China(YCSJ-01-201205),which is“Research of an efficient and intelligent optimization method and application in aircraft shape design”.
文摘In order to achieve the optimal attack outcome in the air combat under the beyond visual range(BVR)condition,the decision-making(DM)problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack(CMTA).In this paper,a heuristic quantum genetic algorithm(HQGA)is proposed to solve the DM problem.The originality of our work can be supported in the following aspects:(1)the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits(Q-bits);(2)the relative successful sequence probability(RSSP)is defined,based on which the priority attack vector is constructed;(3)the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper;(4)last but not the least,in some special conditions,the HQGA gets rid of the constraint described by other algorithms that to obtain a better result.In the end of this paper,two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.
文摘A defender–attacker–target problem with non-moving target is considered.This problem is modelled by a pursuit-evasion zero-sum differential game with linear dynamics and quadratic cost functional.In this game,the pursuer is the defender,while the evader is the attacker.The objective of the pursuer is to minimise the cost functional,while the evader has two objectives:to maximise the cost functional and to keep a given terminal state inequality constraint.The open-loop saddle point solution of this game is obtained in the case where the transfer functions of the controllers for the defender and the attacker are of arbitrary orders.
文摘Many complex networks exist to facilitate the transport of material or information.In this capacity,the authors are often concerned with the continued flow of material or information when a fraction of the links in the complex network is disrupted.In other words,the authors are interested in the robustness of the complex network.In this paper,the authors survey measures of robustness like the average path length,the average clustering coefficient,the global efficiency,the size of largest cluster and use these to analyze the robustness of the bus network in Hanoi,Vietnam.The authors find that the bus network is robust against random failure but sensitive to targeted attack,in agreement with its scale-free character.By examining sharp drops in the average path length within the largest cluster of the Hanoi bus network under successive targeted attack,the authors identify five nodes whose loss lead to the fragmentation of the network into five or six disconnected clusters.These isolated clusters represent geographically the Central,Western,Southern,and Northwestern districts of Hanoi.Special considerations must therefore be given to these five nodes when planners wish to expand the bus network,or make it more robust.
基金the National Natural Science Foundation of China (No. 60373023)
文摘The fault tolerance of scale-free networks is examined in this paper. Through the simulation on the changes of the average path length and network fragmentation of the Barabasi-Albert model when faults happen, it can be observed that generic scale-free networks are quite robust to random failures, but are very vulnerable to targeted attacks at the same time. Therefore, an existing optimization strategy for the robustness of scale-free networks to failures and attacks is also introduced. The simulation similar with the above proved that the so-called (1,0) network has potentially interconnectedness closer to that of a scale-free network and robustness to targeted attacks closer to that of an exponential network. Furthermore, its resistance to random failures is better than that of either of them.
基金partially supported by the Science and Technology Innovation 2030-Key Project of“New Generation Artificial Intelligence”(Grant No.2018AAA0102403)the National Natural Science Foundation of China(Grant Nos.U20B2071,91948204,T2121003,and U1913602)。
文摘For unmanned aerial vehicle(UAV)swarm dynamic combat,swarm antagonistic motion control and attack target allocation are extremely challenging sub-tasks.In this paper,the competitive learning pigeon-inspired optimization(CLPIO)algorithm is proposed to handle the cooperative dynamic combat problem,which integrates the distributed swarm antagonistic motion and centralized attack target allocation.Moreover,the threshold trigger strategy is presented to switch two sub-tasks.To seek a feasible and optimal combat scheme,a dynamic game approach combined with hawk grouping mechanism and situation assessment between sub-groups is designed to guide the solution of the optimal attack scheme,and the model of swarm antagonistic motion imitating pigeon’s intelligence is proposed to form a confrontation situation.The analysis of the CLPIO algorithm shows its convergence in theory and the comparison with the other four metaheuristic algorithms shows its superiority in solving the mixed Nash equilibrium problem.Finally,numerical simulation verifis that the proposed methods can provide an effective combat scheme in the set scenario.
基金supported by the National Natural Science Foundation of China(No.61170217)the Open Research Fund from the Shandong Provincial Key Laboratory of Computer Network(No.SDKLCN-2011-01)Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.110109)
文摘Wireless Machine to Machine （M2M） communications enable ubiquitous sensing, controlling, and acting via sensors, actuators, and actors. Reliability and security are of foremost importance in wireless M2M systems. A simple, target distinguishing attack can result in M2M＇s failure. This paper presents a Reliable and SEcure scheme, RISE, which is a package of policies that guarantee the reliability of data （including sensor reports and actuator instructions） and devices （including sensors, actuators, and actors）. The data reliability is improved by four algorithms, ChooseMedian, ChooseMost, ChooseNearest, and Trust-based Enhancement. Report attainability is improved via m repeat-sending and n multiple-reporting algorithms. Device reliability is guaranteed by device-indistinguishability, which comprises data-indistinguishability and behavior-indistinguishability. The security requirements are formally defined, and the security analysis proves the soundness and completeness of the scheme,
