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
The Chinese Academy of Sci-ences (CAS)has designatedguaranteeing food safety forthe future population peak of 1.6 bil-lion as its first and foremost targettaking into account the stress thatwill place on China’s exis...The Chinese Academy of Sci-ences (CAS)has designatedguaranteeing food safety forthe future population peak of 1.6 bil-lion as its first and foremost targettaking into account the stress thatwill place on China’s existingresources, said a CAS official at theacademy’s annual work展开更多
Driven by the rapid development of the Internet of Things,cloud computing and other emerging technologies,the connotation of cyberspace is constantly expanding and becoming the fifth dimension of human activities.Howe...Driven by the rapid development of the Internet of Things,cloud computing and other emerging technologies,the connotation of cyberspace is constantly expanding and becoming the fifth dimension of human activities.However,security problems in cyberspace are becoming serious,and traditional defense measures(e.g.,firewall,intrusion detection systems,and security audits)often fall into a passive situation of being prone to attacks and difficult to take effect when responding to new types of network attacks with a higher and higher degree of coordination and intelligence.By constructing and implementing the diverse strategy of dynamic transformation,the configuration characteristics of systems are constantly changing,and the probability of vulnerability exposure is increasing.Therefore,the difficulty and cost of attack are increasing,which provides new ideas for reversing the asymmetric situation of defense and attack in cyberspace.Nonetheless,few related works systematically introduce dynamic defense mechanisms for cyber security.The related concepts and development strategies of dynamic defense are rarely analyzed and summarized.To bridge this gap,we conduct a comprehensive and concrete survey of recent research efforts on dynamic defense in cyber security.Specifically,we firstly introduce basic concepts and define dynamic defense in cyber security.Next,we review the architectures,enabling techniques and methods for moving target defense and mimic defense.This is followed by taxonomically summarizing the implementation and evaluation of dynamic defense.Finally,we discuss some open challenges and opportunities for dynamic defense in cyber security.展开更多
The acute effect of acupuncture on Alzheimer＇s disease,i.e.,on brain activation during treatment,has been reported.However,the effect of long-term acupuncture on brain activation in Alzheimer＇s disease is unclear.Th...The acute effect of acupuncture on Alzheimer＇s disease,i.e.,on brain activation during treatment,has been reported.However,the effect of long-term acupuncture on brain activation in Alzheimer＇s disease is unclear.Therefore,in this study,we performed long-term needling at Zusanli（ST36）or a sham point（1.5 mm lateral to ST36）in a rat Alzheimer＇s disease model,for 30 minutes,once per day,for 30 days.The rats underwent 18F-fluorodeoxyglucose positron emission tomography scanning.Positron emission tomography images were processed with SPM2.The brain areas activated after needling at ST36 included the left hippocampus,the left orbital cortex,the left infralimbic cortex,the left olfactory cortex,the left cerebellum and the left pons.In the sham-point group,the activated regions were similar to those in the ST36 group.However,the ST36 group showed greater activation in the cerebellum and pons than the sham-point group.These findings suggest that long-term acupuncture treatment has targeted regulatory effects on multiple brain regions in rats with Alzheimer＇s disease.展开更多
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
1 Introduction The United States,Japan,Canada,the European Union,and other developed countries and regions have all formulated climate strategies and pledged to achieve net-zero CO_(2) emissions by 2050.China,meanwhil...1 Introduction The United States,Japan,Canada,the European Union,and other developed countries and regions have all formulated climate strategies and pledged to achieve net-zero CO_(2) emissions by 2050.China,meanwhile,has announced through the“carbon-peaking and carbon neutrality targets”in September 2020 that it aims to achieve“peak carbon use”by 2030 and“carbon neutrality”by 2060[1].According to statistical data from the International Energy Agency(IEA),Fig.1 illustrates the carbon intensity of electricity generation in various regions in the Announced Pledge Scenario(APS)from 2010 to 2040[2].One can easily observe that each region aims to accomplish a sharp decrease in the carbon intensity of electricity generation after 2020.展开更多
This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactic...This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted?self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.展开更多
The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data world.This approach allows efficient infrastructure to store and access big real-time data and smart IoE ...The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data world.This approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the cloud.The IoE-based cloud computing services are located at remote locations without the control of the data owner.The data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security capabilities.The lack of knowledge about security capabilities and control over data raises several security issues.Deoxyribonucleic Acid(DNA)computing is a biological concept that can improve the security of IoE big data.The IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher algorithms.This paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access issues.The experimental results illustrated that DNACDS performs better than other DNA-based security schemes.The theoretical security analysis of the DNACDS shows better resistance capabilities.展开更多
目的探讨非ST段抬高型急性心肌梗死(NSTEMI)患者入院心电图无缺血改变的发生率及其对预后的影响。方法回顾性分析2014年1月至2017年12月于丹阳市人民医院心内科住院的192例NSTEMI患者,根据急诊室12或18导联心电图表现,分为两组,即无缺...目的探讨非ST段抬高型急性心肌梗死(NSTEMI)患者入院心电图无缺血改变的发生率及其对预后的影响。方法回顾性分析2014年1月至2017年12月于丹阳市人民医院心内科住院的192例NSTEMI患者,根据急诊室12或18导联心电图表现,分为两组,即无缺血改变组及ST段压低组。了解NSTEMI患者心电图无缺血改变的发生率,住院期间及出院30 d心血管复合终点事件发生率。结果和ST段压低组相比,无缺血改变组多年纪轻,有近期吸烟史,心血管危险因素少。无缺血性改变组(n=110,57.3%)明显高于ST段压低组(n=82,42.7%)。无缺血改变组3支血管病变发生率低于ST段压低组(28.2%vs.41.5%,P=0.003),左主干(7.3%vs.24.4%,P=0.000)及前降支近端病变发生率(30.9%vs.41.5%,P=0.027)低于ST段压低组,无缺血改变组D-to-B时间(h)明显高于ST段压低组[(30.88±18.29)vs.(14.61±6.25),P=0.000]。住院期间MACE低于ST段压低组,但是30 d MACE两者无明显差别。结论根据入院心电图检查的结果,NSTEMI患者心电图无缺血改变发生率高、短期预后较ST段压低组好,但仍需要引起高度关注,及时实现再灌注治疗可能会改善预后。展开更多
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The Chinese Academy of Sci-ences (CAS)has designatedguaranteeing food safety forthe future population peak of 1.6 bil-lion as its first and foremost targettaking into account the stress thatwill place on China’s existingresources, said a CAS official at theacademy’s annual work
基金supported by the Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps,under grants No.2020DB005 and No.2017DB005supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions fund.
文摘Driven by the rapid development of the Internet of Things,cloud computing and other emerging technologies,the connotation of cyberspace is constantly expanding and becoming the fifth dimension of human activities.However,security problems in cyberspace are becoming serious,and traditional defense measures(e.g.,firewall,intrusion detection systems,and security audits)often fall into a passive situation of being prone to attacks and difficult to take effect when responding to new types of network attacks with a higher and higher degree of coordination and intelligence.By constructing and implementing the diverse strategy of dynamic transformation,the configuration characteristics of systems are constantly changing,and the probability of vulnerability exposure is increasing.Therefore,the difficulty and cost of attack are increasing,which provides new ideas for reversing the asymmetric situation of defense and attack in cyberspace.Nonetheless,few related works systematically introduce dynamic defense mechanisms for cyber security.The related concepts and development strategies of dynamic defense are rarely analyzed and summarized.To bridge this gap,we conduct a comprehensive and concrete survey of recent research efforts on dynamic defense in cyber security.Specifically,we firstly introduce basic concepts and define dynamic defense in cyber security.Next,we review the architectures,enabling techniques and methods for moving target defense and mimic defense.This is followed by taxonomically summarizing the implementation and evaluation of dynamic defense.Finally,we discuss some open challenges and opportunities for dynamic defense in cyber security.
基金supported by the National Basic Research Program of China(973 Program),No.2006CB504505,2012CB518504the National Natural Science Foundation of China,No.90709027+1 种基金the Student's Platform for Innovation and Entrepreneurship Training Program of Southern Medical University of China,No.201512121165the Doctoral Foundation of Guangdong Medical University of China,No.2XB13058
文摘The acute effect of acupuncture on Alzheimer＇s disease,i.e.,on brain activation during treatment,has been reported.However,the effect of long-term acupuncture on brain activation in Alzheimer＇s disease is unclear.Therefore,in this study,we performed long-term needling at Zusanli（ST36）or a sham point（1.5 mm lateral to ST36）in a rat Alzheimer＇s disease model,for 30 minutes,once per day,for 30 days.The rats underwent 18F-fluorodeoxyglucose positron emission tomography scanning.Positron emission tomography images were processed with SPM2.The brain areas activated after needling at ST36 included the left hippocampus,the left orbital cortex,the left infralimbic cortex,the left olfactory cortex,the left cerebellum and the left pons.In the sham-point group,the activated regions were similar to those in the ST36 group.However,the ST36 group showed greater activation in the cerebellum and pons than the sham-point group.These findings suggest that long-term acupuncture treatment has targeted regulatory effects on multiple brain regions in rats with Alzheimer＇s disease.
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1 Introduction The United States,Japan,Canada,the European Union,and other developed countries and regions have all formulated climate strategies and pledged to achieve net-zero CO_(2) emissions by 2050.China,meanwhile,has announced through the“carbon-peaking and carbon neutrality targets”in September 2020 that it aims to achieve“peak carbon use”by 2030 and“carbon neutrality”by 2060[1].According to statistical data from the International Energy Agency(IEA),Fig.1 illustrates the carbon intensity of electricity generation in various regions in the Announced Pledge Scenario(APS)from 2010 to 2040[2].One can easily observe that each region aims to accomplish a sharp decrease in the carbon intensity of electricity generation after 2020.
文摘This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted?self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.
文摘The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data world.This approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the cloud.The IoE-based cloud computing services are located at remote locations without the control of the data owner.The data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security capabilities.The lack of knowledge about security capabilities and control over data raises several security issues.Deoxyribonucleic Acid(DNA)computing is a biological concept that can improve the security of IoE big data.The IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher algorithms.This paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access issues.The experimental results illustrated that DNACDS performs better than other DNA-based security schemes.The theoretical security analysis of the DNACDS shows better resistance capabilities.
文摘目的探讨非ST段抬高型急性心肌梗死(NSTEMI)患者入院心电图无缺血改变的发生率及其对预后的影响。方法回顾性分析2014年1月至2017年12月于丹阳市人民医院心内科住院的192例NSTEMI患者,根据急诊室12或18导联心电图表现,分为两组,即无缺血改变组及ST段压低组。了解NSTEMI患者心电图无缺血改变的发生率,住院期间及出院30 d心血管复合终点事件发生率。结果和ST段压低组相比,无缺血改变组多年纪轻,有近期吸烟史,心血管危险因素少。无缺血性改变组(n=110,57.3%)明显高于ST段压低组(n=82,42.7%)。无缺血改变组3支血管病变发生率低于ST段压低组(28.2%vs.41.5%,P=0.003),左主干(7.3%vs.24.4%,P=0.000)及前降支近端病变发生率(30.9%vs.41.5%,P=0.027)低于ST段压低组,无缺血改变组D-to-B时间(h)明显高于ST段压低组[(30.88±18.29)vs.(14.61±6.25),P=0.000]。住院期间MACE低于ST段压低组,但是30 d MACE两者无明显差别。结论根据入院心电图检查的结果,NSTEMI患者心电图无缺血改变发生率高、短期预后较ST段压低组好,但仍需要引起高度关注,及时实现再灌注治疗可能会改善预后。
