As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and use...As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effe...VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution.FromJuly to October 2020,onlinemonitoringwas conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity.Additionally,the PMF(positive matrix factorization)method was utilized to identify the VOCs sources.Results indicated that the TVOCs(total VOCs)concentration was(96.7±63.4μg/m^3),with alkanes exhibiting the highest concentration of(36.1±26.4μg/m^3),followed by OVOCs(16.4±14.4μg/m^3).The key active components were alkenes and aromatics,among which xylene,propylene,toluene,propionaldehyde,acetaldehyde,ethylene,and styrene played crucial roles as reactive species.The sources derived from PMF analysis encompassed vehicle emissions,solvent and coating sources,combustion sources,industrial emissions sources,as well as plant sources,the contribution of which were 37.80%,27.93%,16.57%,15.24%,and 2.46%,respectively.Hence,reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.展开更多
Thermodynamically stable and ultra-thin “phase” at the interface, known as complexions, can significantly improve the mechanical properties of nanolayered composites. However, the effect of complexions features (e.g...Thermodynamically stable and ultra-thin “phase” at the interface, known as complexions, can significantly improve the mechanical properties of nanolayered composites. However, the effect of complexions features (e.g., crystalline orientation, crystalline structure and amorphous composition) on the plastic deformation remains inadequately investigated, and the correlation with the plastic transmission and mechanical response has not been fully established. Here, using atomistic simulations, we elucidate the different complexions-dominated plastic transmission and mechanical response. Complexions can alter the preferred slip system of dislocation nucleation, depending on the Schmid factor and interface structure. After nucleation, the dislocation density exhibits an inverse correlation with the stress magnitude, because the number of dislocations influences the initiation of plastic deformation and determines the stress release. For crystalline complexions with different structures and orientations, the ability of dislocation transmission is mainly dependent on the continuity of the slip system. The plastic transmission can easily proceed and exhibits relatively low flow stress when the slip system is well-aligned. In the case of amorphous complexions with different compositions, compositional variations impact the atomic percentage of shear transformation zones after loading, resulting in different magnitudes of plastic deformation. When smaller plastic deformation is produced, less stress can be released contributing to higher flow stress. These findings reveal the role of the complexions on plasticity behavior and provide valuable insights for the design of nanolayered composites.展开更多
Due to the high flexibility of Unmanned Aerial Vehicles(UAVs),equipping Mobile Edge Computing(MEC)servers on UAVs can effectively and rapidly handle the high computing requirements of computation-intensive tasks.Howev...Due to the high flexibility of Unmanned Aerial Vehicles(UAVs),equipping Mobile Edge Computing(MEC)servers on UAVs can effectively and rapidly handle the high computing requirements of computation-intensive tasks.However,the Line-of-Sight(LoS)transmission between the UAV and ground users makes the offloading information be easily monitored.Therefore,this paper proposes a covert communication scheme against a flying warden in UAV-assisted MEC system.In the proposed scheme,the UAV server assists ground users in completing the computation of offloading tasks.To reduce the possibility of the flying warden detecting the transmission behavior of ground users to the UAV server,a ground jamming device sends jamming signals to the flying warden.The minimum computing capacity of the system is maximized by jointly optimizing ground users’resources and the UAV server’s trajectory under the constraint of system covertness.Due to the multivariable coupling,the optimization problem is non-convex.The optimization problem is first transformed into a tractable form,and then the optimizing solution is iteratively obtained using Successive Convex Approximation(SCA)and Block Coordinate Descent(BCD)algorithms.Numerical results show that,compared to the benchmark schemes,the proposed scheme effectively enhances the computing capacity of the system while meeting the system’s covertness requirements.展开更多
Timely and accurate diagnosis of skin diseases is crucial as conventional methods are time-consuming and prone to errors.Traditional trial-and-error approaches often aggregate multiple models without optimization by r...Timely and accurate diagnosis of skin diseases is crucial as conventional methods are time-consuming and prone to errors.Traditional trial-and-error approaches often aggregate multiple models without optimization by resulting in suboptimal performance.To address these challenges,we propose a novel Squid Game OptimizationDimension Reduction-based Ensemble(SGO-DRE)method for the precise diagnosis of skin diseases.Our approach begins by selecting pre-trained models named MobileNetV1,DenseNet201,and Xception for robust feature extraction.These models are enhanced with dimension reduction blocks to improve efficiency.To tackle the aggregation problem of various models,we leverage the Squid Game Optimization(SGO)algorithm,which iteratively searches for the optimal weightage set to assign the appropriate weightage to each individual model within the proposed weighted average aggregation ensemble approach.The proposed ensemble method effectively utilizes the strengths of each model.We evaluated the proposed method using an 8-class skin disease dataset,a 6-class MSLD dataset,and a 4-class MSID dataset,achieving accuracies of 98.71%,96.34%,and 93.46%,respectively.Additionally,we employed visual tools like Grad-CAM,ROC curves,and Precision-Recall curves to interpret the decision making of models and assess its performance.These evaluations ensure that the proposed method not only provides robust results but also enhances interpretability and reliability in clinical decision-making.展开更多
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.U21A20465,62302457,62402444,62172292)+4 种基金the Fundamental Research Funds of Zhejiang Sci-Tech University(Nos.23222092-Y,22222266-Y)the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ24F020008,LQ24F020012)the Foundation of State Key Laboratory of Public Big Data(No.[2022]417)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01119).
文摘As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
基金supported by the Natural Science Foundation of Hebei Province(Nos.D2019106042,D2020304038,and D2021106002)the National Natural Science Foundation of China(No.22276099)+1 种基金the State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex(No.2021080544)the Environmental Monitoring Research Foundation of Jiangsu Province(No.2211).
文摘VOCs(Volatile organic compounds)exert a vital role in ozone and secondary organic aerosol production,necessitating investigations into their concentration,chemical characteristics,and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution.FromJuly to October 2020,onlinemonitoringwas conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity.Additionally,the PMF(positive matrix factorization)method was utilized to identify the VOCs sources.Results indicated that the TVOCs(total VOCs)concentration was(96.7±63.4μg/m^3),with alkanes exhibiting the highest concentration of(36.1±26.4μg/m^3),followed by OVOCs(16.4±14.4μg/m^3).The key active components were alkenes and aromatics,among which xylene,propylene,toluene,propionaldehyde,acetaldehyde,ethylene,and styrene played crucial roles as reactive species.The sources derived from PMF analysis encompassed vehicle emissions,solvent and coating sources,combustion sources,industrial emissions sources,as well as plant sources,the contribution of which were 37.80%,27.93%,16.57%,15.24%,and 2.46%,respectively.Hence,reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels.
基金supported by the National Natural Science Foundation of China(Nos.U23A20543,52071124)the Natural Science Foundation of the Hebei Province(No.E2021202135).
文摘Thermodynamically stable and ultra-thin “phase” at the interface, known as complexions, can significantly improve the mechanical properties of nanolayered composites. However, the effect of complexions features (e.g., crystalline orientation, crystalline structure and amorphous composition) on the plastic deformation remains inadequately investigated, and the correlation with the plastic transmission and mechanical response has not been fully established. Here, using atomistic simulations, we elucidate the different complexions-dominated plastic transmission and mechanical response. Complexions can alter the preferred slip system of dislocation nucleation, depending on the Schmid factor and interface structure. After nucleation, the dislocation density exhibits an inverse correlation with the stress magnitude, because the number of dislocations influences the initiation of plastic deformation and determines the stress release. For crystalline complexions with different structures and orientations, the ability of dislocation transmission is mainly dependent on the continuity of the slip system. The plastic transmission can easily proceed and exhibits relatively low flow stress when the slip system is well-aligned. In the case of amorphous complexions with different compositions, compositional variations impact the atomic percentage of shear transformation zones after loading, resulting in different magnitudes of plastic deformation. When smaller plastic deformation is produced, less stress can be released contributing to higher flow stress. These findings reveal the role of the complexions on plasticity behavior and provide valuable insights for the design of nanolayered composites.
基金supported in part by the Zhejiang Provincial Natural Science Foundation of China(No.LR25F010003)in part by the National Natural Science Foundation of China(Nos.62271447,61871348 and 62471090)+1 种基金in part by the Natural Science Foundation of Sichuan Province of China(No.2023NSFSC047)in part by the Fundamental Research Funds for the Provincial Universities of Zhejiang,China(No.RF-C2023008).
文摘Due to the high flexibility of Unmanned Aerial Vehicles(UAVs),equipping Mobile Edge Computing(MEC)servers on UAVs can effectively and rapidly handle the high computing requirements of computation-intensive tasks.However,the Line-of-Sight(LoS)transmission between the UAV and ground users makes the offloading information be easily monitored.Therefore,this paper proposes a covert communication scheme against a flying warden in UAV-assisted MEC system.In the proposed scheme,the UAV server assists ground users in completing the computation of offloading tasks.To reduce the possibility of the flying warden detecting the transmission behavior of ground users to the UAV server,a ground jamming device sends jamming signals to the flying warden.The minimum computing capacity of the system is maximized by jointly optimizing ground users’resources and the UAV server’s trajectory under the constraint of system covertness.Due to the multivariable coupling,the optimization problem is non-convex.The optimization problem is first transformed into a tractable form,and then the optimizing solution is iteratively obtained using Successive Convex Approximation(SCA)and Block Coordinate Descent(BCD)algorithms.Numerical results show that,compared to the benchmark schemes,the proposed scheme effectively enhances the computing capacity of the system while meeting the system’s covertness requirements.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R749)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Timely and accurate diagnosis of skin diseases is crucial as conventional methods are time-consuming and prone to errors.Traditional trial-and-error approaches often aggregate multiple models without optimization by resulting in suboptimal performance.To address these challenges,we propose a novel Squid Game OptimizationDimension Reduction-based Ensemble(SGO-DRE)method for the precise diagnosis of skin diseases.Our approach begins by selecting pre-trained models named MobileNetV1,DenseNet201,and Xception for robust feature extraction.These models are enhanced with dimension reduction blocks to improve efficiency.To tackle the aggregation problem of various models,we leverage the Squid Game Optimization(SGO)algorithm,which iteratively searches for the optimal weightage set to assign the appropriate weightage to each individual model within the proposed weighted average aggregation ensemble approach.The proposed ensemble method effectively utilizes the strengths of each model.We evaluated the proposed method using an 8-class skin disease dataset,a 6-class MSLD dataset,and a 4-class MSID dataset,achieving accuracies of 98.71%,96.34%,and 93.46%,respectively.Additionally,we employed visual tools like Grad-CAM,ROC curves,and Precision-Recall curves to interpret the decision making of models and assess its performance.These evaluations ensure that the proposed method not only provides robust results but also enhances interpretability and reliability in clinical decision-making.
