Malware continues to pose a significant threat to cybersecurity,with new advanced infections that go beyond traditional detection.Limitations in existing systems include high false-positive rates,slow system response ...Malware continues to pose a significant threat to cybersecurity,with new advanced infections that go beyond traditional detection.Limitations in existing systems include high false-positive rates,slow system response times,and inability to respond quickly to new malware forms.To overcome these challenges,this paper proposes OMD-RAS:Implementing Malware Detection in an Optimized Way through Real-Time and Adaptive Security as an extensive approach,hoping to get good results towards better malware threat detection and remediation.The significant steps in the model are data collection followed by comprehensive preprocessing consisting of feature engineering and normalization.Static analysis,along with dynamic analysis,is done to capture the whole spectrum of malware behavior for the feature extraction process.The extracted processed features are given with a continuous learning mechanism to the Extreme Learning Machine model of real-time detection.This OMD-RAS trains quickly and has great accuracy,providing elite,advanced real-time detection capabilities.This approach uses continuous learning to adapt to new threats—ensuring the effectiveness of detection even as strategies used by malware may change over time.The experimental results showed that OMD-RAS performs better than the traditional approaches.For instance,the OMD-RAS model has been able to achieve an accuracy of 96.23%and massively reduce the rate of false positives across all datasets while eliciting a consistently high rate of precision and recall.The model’s adaptive learning reflected enhancements on other performance measures-for example,Matthews Correlation Coefficients and Log Loss.展开更多
Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been pr...Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems.We demonstrate that,to overcome these challenges,for instance,the EdgeGuard-IoT framework,a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid,is needed on the edge to integrate Secure Federated Learning(SFL)and Adaptive Anomaly Detection(AAD).With ultra-reliable low latency communication(URLLC)of 6G,artificial intelligence-based network orchestration,and massive machine type communication(mMTC),EdgeGuard-IoT brings real-time,distributed intelligence on the edge,and mitigates risks in data transmission and enhances privacy.EdgeGuard-IoT,with a hierarchical federated learning framework,helps edge devices to collaboratively train models without revealing the sensitive grid data,which is crucial in the smart grid where real-time power anomaly detection and the decentralization of the energy management are a big deal.The hybrid AI models driven adaptive anomaly detection mechanism immediately raises the thumb if the grid stability and strength are negatively affected due to cyber threats,faults,and energy distribution,thereby keeping the grid stable with resilience.The proposed framework also adopts various security means within the blockchain and zero-trust authentication techniques to reduce the adversarial attack risks and model poisoning during federated learning.EdgeGuard-IoT shows superior detection accuracy,response time,and scalability performance at a much reduced communication overhead via extensive simulations and deployment in real-world case studies in smart grids.This research pioneers a 6G-driven federated intelligence model designed for secure,self-optimizing,and resilient Industry 5.0 ecosystems,paving the way for next-generation autonomous smart grids and industrial cyber-physical systems.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algori...Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.展开更多
Impressive advances in space technology are enabling complex missions, with potentially significant and long term impacts on human life and activities. In the vision of future space exploration, communication links am...Impressive advances in space technology are enabling complex missions, with potentially significant and long term impacts on human life and activities. In the vision of future space exploration, communication links among planets, satel ites, spacecrafts and crewed vehicles wil be designed according to a new paradigm, known as the disruption tolerant networking. In this scenario, space channel peculiarities impose a massive reengineering of many of the protocols usually adopted in terrestrial networks; among them, security solutions are to be deeply reviewed, and tailored to the specific space requirements. Security is to be provided not only to the payload data exchanged on the network, but also to the telecommands sent to a spacecraft, along possibly differentiated paths. Starting from the secure space telecommand design developed by the Consultative Committee for Space Data Systems as a response to agency-based requirements, an adaptive link layer security architecture is proposed to address some of the chal enges for future space networks. Based on the analysis of the communication environment and the error diffusion properties of the authentication algorithms, a suitable mechanism is proposed to classify frame retransmission requests on the basis of the originating event （error or security attack） and reduce the impact of security operations. An adaptive algorithm to optimize the space control protocol, based on estimates of the time varying space channel, is also presented. The simulation results clearly demonstrate that the proposed architecture is feasible and efficient, especially when facing malicious attacks against frame transmission.展开更多
Communication-dependent and software-based distributed energy resources(DERs)are extensively integrated into modern microgrids,providing extensive benefits such as increased distributed controllability,scalability,and...Communication-dependent and software-based distributed energy resources(DERs)are extensively integrated into modern microgrids,providing extensive benefits such as increased distributed controllability,scalability,and observability.However,malicious cyber-attackers can exploit various potential vulnerabilities.In this study,a programmable adaptive security scanning(PASS)approach is presented to protect DER inverters against various power-bot attacks.Specifically,three different types of attacks,namely controller manipulation,replay,and injection attacks,are considered.This approach employs both software-defined networking technique and a novel coordinated detection method capable of enabling programmable and scalable networked microgrids(NMs)in an ultra-resilient,time-saving,and autonomous manner.The coordinated detection method efficiently identifies the location and type of power-bot attacks without disrupting normal NM operations.Extensive simulation results validate the efficacy and practicality of the PASS for securing NMs.展开更多
Combining the principle of antibody concentration with the idea of biological evolution, this paper proposes an adaptive target detection algorithm for cloud service security based on Bio-Inspired Performance Evaluati...Combining the principle of antibody concentration with the idea of biological evolution, this paper proposes an adaptive target detection algorithm for cloud service security based on Bio-Inspired Performance Evaluation Process Algebra(Bio-PEPA). The formal modelling of cloud services is formally modded by Bio-PEPA and the modules are transformed between cloud service internal structures and various components. Then, the security adaptive target detection algorithm of cloud service is divided into two processes, the short-term optimal action selection process which selects the current optimal detective action through the iterative operation of the expected function and the adaptive function, and the long-term detective strategy realized through the updates and eliminations of action planning table. The combination of the two processes reflects the self-adaptability of cloud service system to target detection. The simulating test detects three different kinds of security risks and then analyzes the relationship between the numbers of components with time in the service process. The performance of this method is compared with random detection method and three anomaly detection methods by the cloud service detection experiment. The detection time of this method is 50.1% of three kinds of detection methods and 86.3% of the random detection method. The service success rate is about 15% higher than that of random detection methods. The experimental results show that the algorithm has good time performance and high detection hit rate.展开更多
Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the app...Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the application of ABE. Most of existing ABE schemes support attribute revocation work under indirect revocation model such that all the users＇ private keys will be affected when the revo-cation events occur. Though some ABE schemes have realized revocation under direct revocation model such that the revocation list is embedded in the ciphertext and none of the users＇ private keys will be affected by revocation, they mostly focused on the user revocation that revokes the user＇s whole attributes, or they can only be proven to be selectively secure. In this paper, we first define a model of adaptively secure ABE supporting the at- tribute revocation under direct revocation model. Then we propose a Key-Policy ABE （KP-ABE） scheme and a Ciphertext-Policy ABE （CP-ABE） scheme on composite order bilinear groups. Finally, we prove our schemes to be adaptively secure by employing the methodology of dual system eno cryption.展开更多
The Yellow River Basin (YRB) is not only an important ecological barrier in north China,but also an important agricultural production base and energy base in China,playing a very important role in China’s economic an...The Yellow River Basin (YRB) is not only an important ecological barrier in north China,but also an important agricultural production base and energy base in China,playing a very important role in China’s economic and social development and ecological security.Under the combined actions of climate change and human activities,a series of ecological and environmental problems have emerged in the YRB,including degradation of glaciers and frozen soil,shortage of water resources,land desertification,aggravated soil and water loss,frequent floods and droughts,and reducing biodiversity.Warmer and wetter climate over the upper reaches and warmer and drier one in the middle and lower reaches have profoundly affected the ecological security of the YRB.In the future,the temperature in the YRB will continue to rise,extreme events will increase and the climate pattern of drought and water shortage will not be changed fundamentally,which will make the basin face more severe ecological security risks.For the current ecological problems and future ecological security risk challenges,it is necessary and urgent to take adaptive measures to deal with climate change and protect the ecological environment.The measures mainly include:strengthening the scientific research on the impact of climate change and extreme events on the ecological environment of the YRB and improving the ability of climate change risk management;strengthening the water conservation and protection in the upper reaches,the management of desert and soil erosion in the middle reaches and the ecological protection of water resources and wetlands in the lower reaches in the YRB and;collaborating with multiple departments to jointly tackle the ecological security challenges brought by climate change.展开更多
To describe the design approaches of IND-CCA2 （adaptive chosen ciphertext attack） secure public key encryption schemes systematically, the gaps between different kinds of intractable problems and IND-CCA2 security a...To describe the design approaches of IND-CCA2 （adaptive chosen ciphertext attack） secure public key encryption schemes systematically, the gaps between different kinds of intractable problems and IND-CCA2 security are studied. This paper points out that the construction of IND-CCA2 secure schemes is essentially to bridge these gaps. These gaps are categorized, analyzed and measured. Finally the methods to bridge these gaps are described. This explains the existing design approaches and gives an intuition about the difficulty of designing IND-CCA2 secure public key encryption schemes based on different types of assumptions.展开更多
Controversial climate change studies purport that predicted food insecurity and resource scarcity will intensify resource conflicts in developing nations. This belief is based on a prevalent assumption that African ag...Controversial climate change studies purport that predicted food insecurity and resource scarcity will intensify resource conflicts in developing nations. This belief is based on a prevalent assumption that African agricultural production systems are rigid and that their respective governments lack comprehensive adaptation ability. Therefore, I investigate whether and how effective post- drought adaptation activity is sustaining food production and livelihoods at Loitoktok district in Kenya. This study uses the theoretical three-step ecosystem service governance approach that analyzes both natural resources attributes and relational data. Results confirm a substantial decline in productivity and huge monetary losses in the agricultural sector of Loitoktok following the 2009 drought. Post-drought analysis reveals high diversification in crops and livestock that are drought-tolerant, fast maturing and high income generating such as camels, rabbits and dairy goats, horticultural and fruit production that sustain food security, income and local livelihoods. These reactive adaptation activities originate from an active public-private cooperation that promotes knowledge exchange among Loitoktok stakeholders. This cooperation is also seen in the efficient resource conflict resolution network. In conclusion, rural communities seem to be efficiently adapting to changing environmental conditions but require more financial and technical support from the government. Unfortunately, appraisal of national planned adaptation reveals effort-duplication that may divert much needed adaptation funds from being invested in research projects with multiple benefits to Kenyan food producers.展开更多
The study was carried out to understand the food security situation and coping mechanisms due to an effect of climate change on food security of Badimalika Municipality of Bajura district in the far-western region;an ...The study was carried out to understand the food security situation and coping mechanisms due to an effect of climate change on food security of Badimalika Municipality of Bajura district in the far-western region;an acute food deficit district of Nepal.Literature review,household questionnaire survey to document primary data,stakeholders’consultation with field observations were the principle methods applied to explore the possible adaptation measures for securing food and livelihood of people.The research revealed that the district is food insecure for at least six to nine months of a year which is worsened by climate induced natural disasters:flood,landslides and drought.Sudden and unpredictable precipitation both in winter and monsoon has distorted the productions over the years.Considerable proportions of grazing land and forested area have been converted into farmland especially in the highlands.Migrating working class manpower to India to seek livelihoods is a menace to development in the place while seasonal migration in and outside the country is an interesting adaptive mechanism in the district.Drought resistant crop varieties such as Finger Millet(Elusine coracana),Foxtail Millet(Setaria italic L.),Wheat(Triticum aestivum),and Amaranth(Amaranthus sp.)are highly potential cereal crops that need to be promoted.Some humanitarian agencies with the support of GoN have been playing an important role in reducing the impact of food deficiency in the region.National Food Corporation District Office supplies the deficit quantity of food to the people.The government needs to make agriculture the highest priority with increased investment schemes to avert the looming food crisis with emphasis on further research based activities through understanding the impact of climate change on specific crops and respective technological interventions,incorporating local adaptation mechanisms for disasters and climate change.Slow-forming terraces,conservation tillage,crop diversification,selection and promotion of drought-resistant varieties of crops,ecological pest management,seed and grain storages etc.are some technological innovations to be considered for enhancing food security.展开更多
The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital t...The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.展开更多
The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging at...The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.展开更多
False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading fail...False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.展开更多
In this paper, a simple adaptive linear feedback control method is proposed for controlling the scaling factor between two coupled unified chaotic systems to a desired value, based on the invarianee principle of diffe...In this paper, a simple adaptive linear feedback control method is proposed for controlling the scaling factor between two coupled unified chaotic systems to a desired value, based on the invarianee principle of differential equations. Under this control strategy, one can arbitrarily select the scaling factor. Numerical simulations are given to support the effectiveness of the proposed method and show the robustness against noise. Furthermore, a secure communication scheme based on the adaptive projective synchronization of unified chaotic systems is presented and numerical simulation shows its feasibility.展开更多
Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilizati...Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilization of heterogeneous resources and anti-eavesdropping.However,edge-end collaboration-based multi-mode PIoT faces challenges of mutual contradiction in communication and security quality of service(QoS)guarantee,inadaptability of resource management,and multi-mode access conflict.We propose an Adaptive learning based delAysensitive and seCure Edge-End Collaboration algorithm(ACE_(2))to optimize multi-mode channel selection and split device power into artificial noise(AN)transmission and data transmission for secure data delivery.ACE_(2) can achieve multi-attribute QoS guarantee,adaptive resource management and security enhancement,and access conflict elimination with the combined power of deep actor-critic(DAC),“win or learn fast(WoLF)”mechanism,and edge-end collaboration.Simulations demonstrate its superior performance in queuing delay,energy consumption,secrecy capacity,and adaptability to differentiated low-carbon services.展开更多
In this paper, based on an adaptive chaos synchronization scheme, two methods of encoding-decoding message for secure communication are proposed. With the first method, message is directly added to the chaotic signal ...In this paper, based on an adaptive chaos synchronization scheme, two methods of encoding-decoding message for secure communication are proposed. With the first method, message is directly added to the chaotic signal with parameter uncertainty. In the second method, multi-parameter modulation is used to simultaneously transmit more than one digital message （i.e., the multichannel digital communication） through just a single signal, which switches among various chaotic attractors that differ only subtly. In theory, such a treatment increases the difficulty for the intruder to directly intercept the information, and meanwhile the implementation cost decreases significantly. In addition, numerical results show the methods are robust against weak noise, which implies their practicability.展开更多
This paper proposes an adaptively secure solution to certificateless distributed key encapsulation mechanism from pairings by using Canetti＇s adaptive secure key generation scheme based on discrete logarithm. The pro...This paper proposes an adaptively secure solution to certificateless distributed key encapsulation mechanism from pairings by using Canetti＇s adaptive secure key generation scheme based on discrete logarithm. The proposed scheme can withstand adaptive attackers that can choose players for corruption at any time during the run of the protocol, and this kind of attack is powerful and realistic. In contrast, all previously presented threshold certificateless public key cryptosystems are proven secure against the more idealized static adversaries only. They choose and fix the subset of target players before running the protocol. We also prove security of this scheme in the random oracle model.展开更多
基金supported by a grant from the Center of Excellence in Information Assurance(CoEIA),King Saud University(KSU).
文摘Malware continues to pose a significant threat to cybersecurity,with new advanced infections that go beyond traditional detection.Limitations in existing systems include high false-positive rates,slow system response times,and inability to respond quickly to new malware forms.To overcome these challenges,this paper proposes OMD-RAS:Implementing Malware Detection in an Optimized Way through Real-Time and Adaptive Security as an extensive approach,hoping to get good results towards better malware threat detection and remediation.The significant steps in the model are data collection followed by comprehensive preprocessing consisting of feature engineering and normalization.Static analysis,along with dynamic analysis,is done to capture the whole spectrum of malware behavior for the feature extraction process.The extracted processed features are given with a continuous learning mechanism to the Extreme Learning Machine model of real-time detection.This OMD-RAS trains quickly and has great accuracy,providing elite,advanced real-time detection capabilities.This approach uses continuous learning to adapt to new threats—ensuring the effectiveness of detection even as strategies used by malware may change over time.The experimental results showed that OMD-RAS performs better than the traditional approaches.For instance,the OMD-RAS model has been able to achieve an accuracy of 96.23%and massively reduce the rate of false positives across all datasets while eliciting a consistently high rate of precision and recall.The model’s adaptive learning reflected enhancements on other performance measures-for example,Matthews Correlation Coefficients and Log Loss.
基金supported by Department of Information Technology,University of Tabuk,Tabuk,71491,Saudi Arabia.
文摘Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems.We demonstrate that,to overcome these challenges,for instance,the EdgeGuard-IoT framework,a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid,is needed on the edge to integrate Secure Federated Learning(SFL)and Adaptive Anomaly Detection(AAD).With ultra-reliable low latency communication(URLLC)of 6G,artificial intelligence-based network orchestration,and massive machine type communication(mMTC),EdgeGuard-IoT brings real-time,distributed intelligence on the edge,and mitigates risks in data transmission and enhances privacy.EdgeGuard-IoT,with a hierarchical federated learning framework,helps edge devices to collaboratively train models without revealing the sensitive grid data,which is crucial in the smart grid where real-time power anomaly detection and the decentralization of the energy management are a big deal.The hybrid AI models driven adaptive anomaly detection mechanism immediately raises the thumb if the grid stability and strength are negatively affected due to cyber threats,faults,and energy distribution,thereby keeping the grid stable with resilience.The proposed framework also adopts various security means within the blockchain and zero-trust authentication techniques to reduce the adversarial attack risks and model poisoning during federated learning.EdgeGuard-IoT shows superior detection accuracy,response time,and scalability performance at a much reduced communication overhead via extensive simulations and deployment in real-world case studies in smart grids.This research pioneers a 6G-driven federated intelligence model designed for secure,self-optimizing,and resilient Industry 5.0 ecosystems,paving the way for next-generation autonomous smart grids and industrial cyber-physical systems.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
文摘Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.
基金supported by the National Natural Science Fundation of China(61101073)
文摘Impressive advances in space technology are enabling complex missions, with potentially significant and long term impacts on human life and activities. In the vision of future space exploration, communication links among planets, satel ites, spacecrafts and crewed vehicles wil be designed according to a new paradigm, known as the disruption tolerant networking. In this scenario, space channel peculiarities impose a massive reengineering of many of the protocols usually adopted in terrestrial networks; among them, security solutions are to be deeply reviewed, and tailored to the specific space requirements. Security is to be provided not only to the payload data exchanged on the network, but also to the telecommands sent to a spacecraft, along possibly differentiated paths. Starting from the secure space telecommand design developed by the Consultative Committee for Space Data Systems as a response to agency-based requirements, an adaptive link layer security architecture is proposed to address some of the chal enges for future space networks. Based on the analysis of the communication environment and the error diffusion properties of the authentication algorithms, a suitable mechanism is proposed to classify frame retransmission requests on the basis of the originating event （error or security attack） and reduce the impact of security operations. An adaptive algorithm to optimize the space control protocol, based on estimates of the time varying space channel, is also presented. The simulation results clearly demonstrate that the proposed architecture is feasible and efficient, especially when facing malicious attacks against frame transmission.
基金This work was supported in part by the National Science Foundation,USA(ECCS-2018492,CNS-2006828,ECCS-2002897,and OIA-2040599).
文摘Communication-dependent and software-based distributed energy resources(DERs)are extensively integrated into modern microgrids,providing extensive benefits such as increased distributed controllability,scalability,and observability.However,malicious cyber-attackers can exploit various potential vulnerabilities.In this study,a programmable adaptive security scanning(PASS)approach is presented to protect DER inverters against various power-bot attacks.Specifically,three different types of attacks,namely controller manipulation,replay,and injection attacks,are considered.This approach employs both software-defined networking technique and a novel coordinated detection method capable of enabling programmable and scalable networked microgrids(NMs)in an ultra-resilient,time-saving,and autonomous manner.The coordinated detection method efficiently identifies the location and type of power-bot attacks without disrupting normal NM operations.Extensive simulation results validate the efficacy and practicality of the PASS for securing NMs.
基金Supported by the National Natural Science Foundation of China(61202458,61403109)the Natural Science Foundation of Heilongjiang Province of China(F2017021)and the Harbin Science and Technology Innovation Research Funds(2016RAQXJ036)
文摘Combining the principle of antibody concentration with the idea of biological evolution, this paper proposes an adaptive target detection algorithm for cloud service security based on Bio-Inspired Performance Evaluation Process Algebra(Bio-PEPA). The formal modelling of cloud services is formally modded by Bio-PEPA and the modules are transformed between cloud service internal structures and various components. Then, the security adaptive target detection algorithm of cloud service is divided into two processes, the short-term optimal action selection process which selects the current optimal detective action through the iterative operation of the expected function and the adaptive function, and the long-term detective strategy realized through the updates and eliminations of action planning table. The combination of the two processes reflects the self-adaptability of cloud service system to target detection. The simulating test detects three different kinds of security risks and then analyzes the relationship between the numbers of components with time in the service process. The performance of this method is compared with random detection method and three anomaly detection methods by the cloud service detection experiment. The detection time of this method is 50.1% of three kinds of detection methods and 86.3% of the random detection method. The service success rate is about 15% higher than that of random detection methods. The experimental results show that the algorithm has good time performance and high detection hit rate.
文摘Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the application of ABE. Most of existing ABE schemes support attribute revocation work under indirect revocation model such that all the users＇ private keys will be affected when the revo-cation events occur. Though some ABE schemes have realized revocation under direct revocation model such that the revocation list is embedded in the ciphertext and none of the users＇ private keys will be affected by revocation, they mostly focused on the user revocation that revokes the user＇s whole attributes, or they can only be proven to be selectively secure. In this paper, we first define a model of adaptively secure ABE supporting the at- tribute revocation under direct revocation model. Then we propose a Key-Policy ABE （KP-ABE） scheme and a Ciphertext-Policy ABE （CP-ABE） scheme on composite order bilinear groups. Finally, we prove our schemes to be adaptively secure by employing the methodology of dual system eno cryption.
文摘The Yellow River Basin (YRB) is not only an important ecological barrier in north China,but also an important agricultural production base and energy base in China,playing a very important role in China’s economic and social development and ecological security.Under the combined actions of climate change and human activities,a series of ecological and environmental problems have emerged in the YRB,including degradation of glaciers and frozen soil,shortage of water resources,land desertification,aggravated soil and water loss,frequent floods and droughts,and reducing biodiversity.Warmer and wetter climate over the upper reaches and warmer and drier one in the middle and lower reaches have profoundly affected the ecological security of the YRB.In the future,the temperature in the YRB will continue to rise,extreme events will increase and the climate pattern of drought and water shortage will not be changed fundamentally,which will make the basin face more severe ecological security risks.For the current ecological problems and future ecological security risk challenges,it is necessary and urgent to take adaptive measures to deal with climate change and protect the ecological environment.The measures mainly include:strengthening the scientific research on the impact of climate change and extreme events on the ecological environment of the YRB and improving the ability of climate change risk management;strengthening the water conservation and protection in the upper reaches,the management of desert and soil erosion in the middle reaches and the ecological protection of water resources and wetlands in the lower reaches in the YRB and;collaborating with multiple departments to jointly tackle the ecological security challenges brought by climate change.
基金the National Natural Science Foundation of China(Nos.60573032,60773092,90604036)
文摘To describe the design approaches of IND-CCA2 （adaptive chosen ciphertext attack） secure public key encryption schemes systematically, the gaps between different kinds of intractable problems and IND-CCA2 security are studied. This paper points out that the construction of IND-CCA2 secure schemes is essentially to bridge these gaps. These gaps are categorized, analyzed and measured. Finally the methods to bridge these gaps are described. This explains the existing design approaches and gives an intuition about the difficulty of designing IND-CCA2 secure public key encryption schemes based on different types of assumptions.
文摘Controversial climate change studies purport that predicted food insecurity and resource scarcity will intensify resource conflicts in developing nations. This belief is based on a prevalent assumption that African agricultural production systems are rigid and that their respective governments lack comprehensive adaptation ability. Therefore, I investigate whether and how effective post- drought adaptation activity is sustaining food production and livelihoods at Loitoktok district in Kenya. This study uses the theoretical three-step ecosystem service governance approach that analyzes both natural resources attributes and relational data. Results confirm a substantial decline in productivity and huge monetary losses in the agricultural sector of Loitoktok following the 2009 drought. Post-drought analysis reveals high diversification in crops and livestock that are drought-tolerant, fast maturing and high income generating such as camels, rabbits and dairy goats, horticultural and fruit production that sustain food security, income and local livelihoods. These reactive adaptation activities originate from an active public-private cooperation that promotes knowledge exchange among Loitoktok stakeholders. This cooperation is also seen in the efficient resource conflict resolution network. In conclusion, rural communities seem to be efficiently adapting to changing environmental conditions but require more financial and technical support from the government. Unfortunately, appraisal of national planned adaptation reveals effort-duplication that may divert much needed adaptation funds from being invested in research projects with multiple benefits to Kenyan food producers.
文摘The study was carried out to understand the food security situation and coping mechanisms due to an effect of climate change on food security of Badimalika Municipality of Bajura district in the far-western region;an acute food deficit district of Nepal.Literature review,household questionnaire survey to document primary data,stakeholders’consultation with field observations were the principle methods applied to explore the possible adaptation measures for securing food and livelihood of people.The research revealed that the district is food insecure for at least six to nine months of a year which is worsened by climate induced natural disasters:flood,landslides and drought.Sudden and unpredictable precipitation both in winter and monsoon has distorted the productions over the years.Considerable proportions of grazing land and forested area have been converted into farmland especially in the highlands.Migrating working class manpower to India to seek livelihoods is a menace to development in the place while seasonal migration in and outside the country is an interesting adaptive mechanism in the district.Drought resistant crop varieties such as Finger Millet(Elusine coracana),Foxtail Millet(Setaria italic L.),Wheat(Triticum aestivum),and Amaranth(Amaranthus sp.)are highly potential cereal crops that need to be promoted.Some humanitarian agencies with the support of GoN have been playing an important role in reducing the impact of food deficiency in the region.National Food Corporation District Office supplies the deficit quantity of food to the people.The government needs to make agriculture the highest priority with increased investment schemes to avert the looming food crisis with emphasis on further research based activities through understanding the impact of climate change on specific crops and respective technological interventions,incorporating local adaptation mechanisms for disasters and climate change.Slow-forming terraces,conservation tillage,crop diversification,selection and promotion of drought-resistant varieties of crops,ecological pest management,seed and grain storages etc.are some technological innovations to be considered for enhancing food security.
文摘The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.
基金Nourah bint Abdulrahman University for funding this project through the Researchers Supporting Project(PNURSP2025R319)Riyadh,Saudi Arabia and Prince Sultan University for covering the article processing charges(APC)associated with this publication.Special acknowledgement to Automated Systems&Soft Computing Lab(ASSCL),Prince Sultan University,Riyadh,Saudi Arabia.
文摘The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.
基金supported by National Key Research and Development Plan of China(No.2022YFB3103304).
文摘False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.
基金Project supported in part by the National Natural Science Foundation of China （Grant Nos 10372054 and 60575038） and the Science Foundation of Southern Yangtze University of China （Grant No 000408）.
文摘In this paper, a simple adaptive linear feedback control method is proposed for controlling the scaling factor between two coupled unified chaotic systems to a desired value, based on the invarianee principle of differential equations. Under this control strategy, one can arbitrarily select the scaling factor. Numerical simulations are given to support the effectiveness of the proposed method and show the robustness against noise. Furthermore, a secure communication scheme based on the adaptive projective synchronization of unified chaotic systems is presented and numerical simulation shows its feasibility.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010 (5400202199534A-0-5-ZN)
文摘Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilization of heterogeneous resources and anti-eavesdropping.However,edge-end collaboration-based multi-mode PIoT faces challenges of mutual contradiction in communication and security quality of service(QoS)guarantee,inadaptability of resource management,and multi-mode access conflict.We propose an Adaptive learning based delAysensitive and seCure Edge-End Collaboration algorithm(ACE_(2))to optimize multi-mode channel selection and split device power into artificial noise(AN)transmission and data transmission for secure data delivery.ACE_(2) can achieve multi-attribute QoS guarantee,adaptive resource management and security enhancement,and access conflict elimination with the combined power of deep actor-critic(DAC),“win or learn fast(WoLF)”mechanism,and edge-end collaboration.Simulations demonstrate its superior performance in queuing delay,energy consumption,secrecy capacity,and adaptability to differentiated low-carbon services.
基金Project supported by the National Natural Science Foundation of China （Grant No. 10572080）, Shanghai Rising-Star Program （Grant No.05QMX1422）, and Dawn Project of the Science Foundation of Shanghai Municipal Commission of Education （Grant No.05SG41 04YQHB089）
文摘In this paper, based on an adaptive chaos synchronization scheme, two methods of encoding-decoding message for secure communication are proposed. With the first method, message is directly added to the chaotic signal with parameter uncertainty. In the second method, multi-parameter modulation is used to simultaneously transmit more than one digital message （i.e., the multichannel digital communication） through just a single signal, which switches among various chaotic attractors that differ only subtly. In theory, such a treatment increases the difficulty for the intruder to directly intercept the information, and meanwhile the implementation cost decreases significantly. In addition, numerical results show the methods are robust against weak noise, which implies their practicability.
基金the National Basic Research Program(973)of China(No.2007CB311201)the National High Technology Research and Development Program(863) of China(Nos.2006AA01Z422,2007AA01Z456)
文摘This paper proposes an adaptively secure solution to certificateless distributed key encapsulation mechanism from pairings by using Canetti＇s adaptive secure key generation scheme based on discrete logarithm. The proposed scheme can withstand adaptive attackers that can choose players for corruption at any time during the run of the protocol, and this kind of attack is powerful and realistic. In contrast, all previously presented threshold certificateless public key cryptosystems are proven secure against the more idealized static adversaries only. They choose and fix the subset of target players before running the protocol. We also prove security of this scheme in the random oracle model.
