Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,inclu...Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.展开更多
In this paper,by using the G_(m,1)~(1,1)-system,we study Darboux transformations for space-like isothermic surfaces in Minkowski space R~(m,1),where G_(m,1)~(1,1)=O(m+1,2)/O(m,1)×O(1,1).
We first establish a integral inequality for compact maximal space-like subman ifolds in pseudo-Riemannian manifolds Np(n+p). Then, we investigate compact space-like sub manifolds and hupersurfaces with parallel secon...We first establish a integral inequality for compact maximal space-like subman ifolds in pseudo-Riemannian manifolds Np(n+p). Then, we investigate compact space-like sub manifolds and hupersurfaces with parallel second fundamental form in Np(n+p) and some other ambient spaces. We obtain some distribution theorems for the square norm of the second fundamental form.展开更多
In this paper,we study the complete space-like submanifold Mn with constant scalar curvature R≤c in the de Sitter space Spn+p(c) and obtain a pinching condition for Mn to be totally umbilical ones.The result generali...In this paper,we study the complete space-like submanifold Mn with constant scalar curvature R≤c in the de Sitter space Spn+p(c) and obtain a pinching condition for Mn to be totally umbilical ones.The result generalizes that in [5,Main Theorem] to higher codimension and give a complement for n=2 there.展开更多
Abstract： This paper concerns space-like submanifolds in a pseudo-Riemannianspace-time Sp^m＋p∪→Ep^m＋p＋1 （P ≥ 1）, and proves that connected compact maximalsuace-like submanifolds in a pseudo-Riemannian spaceti...Abstract： This paper concerns space-like submanifolds in a pseudo-Riemannianspace-time Sp^m＋p∪→Ep^m＋p＋1 （P ≥ 1）, and proves that connected compact maximalsuace-like submanifolds in a pseudo-Riemannian spacetime Sp^m＋p∪→Ep^m＋p＋1 （P ≥ 1） must be totally umbilical, and also totally geodesic. Particularly, when p = 1, our result is just Montiel＇s in case of H = 0.展开更多
The purpose of this paper is to study complete space-like submanifolds with parallel mean curvature vector and flat normal bundle in a locally symmetric semi-defnite space satisfying some curvature conditions. We firs...The purpose of this paper is to study complete space-like submanifolds with parallel mean curvature vector and flat normal bundle in a locally symmetric semi-defnite space satisfying some curvature conditions. We first give an optimal estimate of the Laplacian of the squared norm of the second fundamental form for such submanifold. Furthermore, the totally umbilical submanifolds are characterized.展开更多
Based on the special theory of relativity in space-like continuum, the pre-sent author points that if there exist tachyons in nature, they should be neutral point-like particles with lepton appearance, which are very ...Based on the special theory of relativity in space-like continuum, the pre-sent author points that if there exist tachyons in nature, they should be neutral point-like particles with lepton appearance, which are very much like our early understanding about neutrinos before. The author also points that an alternative explanation for neutrino oscillations may be the conversion between mass-less neutrinos with different flavors expressed in different “lowest limited momentum” during their flight journey, which originates from that the argument in the squared sine function of the probability of neutrino oscillation may be less than zero, which is mathematical foresight and may not be ignored.展开更多
In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resou...Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.展开更多
DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become m...DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.展开更多
Bananas are highly perishable after harvest,and processing them into dried products is a crucial approach to reducing losses and adding their economic values.To address the inefficiency and prolonged duration of tradi...Bananas are highly perishable after harvest,and processing them into dried products is a crucial approach to reducing losses and adding their economic values.To address the inefficiency and prolonged duration of traditional hot air drying(HAD)and the quality inconsistency associated with single infrared drying(IRD),this study proposed a novel hot air-infrared combined drying(HAD-IRD)strategy.The effects of HAD,IRD,and HAD-IRD on the drying kinetics,color,rehydration capacity,moisture diffusion mechanism,and sensory quality of banana slices were systematically investigated.The parameters of the combined drying process were optimized using an L_(9)(3^(3))orthogonal experimental design.Results indicated that both IRD and HAD-IRD significantly reduced drying time compared to single HAD.While single IRD achieved a rapid drying rate,the lack of effective convective airflow led to potential case-hardening and unstable product quality.In contrast,the HAD-IRD strategy demonstrated a synergistic effect.The optimal parameters were determined as follows:hot air temperature of 70℃,infrared temperature of 60℃,and radiation distance of 16 cm.Under these optimized conditions,HAD-IRD reduced the total drying time by over 70%while simultaneously yielding products with superior color,higher sensory scores,and improved rehydration ratio.This study confirms that HAD-IRD is an efficient and high-quality drying method for banana slices,providing a reliable theoretical foundation and technical solution for the drying of thermosensitive fruits.展开更多
文摘Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.
文摘In this paper,by using the G_(m,1)~(1,1)-system,we study Darboux transformations for space-like isothermic surfaces in Minkowski space R~(m,1),where G_(m,1)~(1,1)=O(m+1,2)/O(m,1)×O(1,1).
文摘We first establish a integral inequality for compact maximal space-like subman ifolds in pseudo-Riemannian manifolds Np(n+p). Then, we investigate compact space-like sub manifolds and hupersurfaces with parallel second fundamental form in Np(n+p) and some other ambient spaces. We obtain some distribution theorems for the square norm of the second fundamental form.
文摘In this paper,we study the complete space-like submanifold Mn with constant scalar curvature R≤c in the de Sitter space Spn+p(c) and obtain a pinching condition for Mn to be totally umbilical ones.The result generalizes that in [5,Main Theorem] to higher codimension and give a complement for n=2 there.
文摘Abstract： This paper concerns space-like submanifolds in a pseudo-Riemannianspace-time Sp^m＋p∪→Ep^m＋p＋1 （P ≥ 1）, and proves that connected compact maximalsuace-like submanifolds in a pseudo-Riemannian spacetime Sp^m＋p∪→Ep^m＋p＋1 （P ≥ 1） must be totally umbilical, and also totally geodesic. Particularly, when p = 1, our result is just Montiel＇s in case of H = 0.
文摘The purpose of this paper is to study complete space-like submanifolds with parallel mean curvature vector and flat normal bundle in a locally symmetric semi-defnite space satisfying some curvature conditions. We first give an optimal estimate of the Laplacian of the squared norm of the second fundamental form for such submanifold. Furthermore, the totally umbilical submanifolds are characterized.
文摘Based on the special theory of relativity in space-like continuum, the pre-sent author points that if there exist tachyons in nature, they should be neutral point-like particles with lepton appearance, which are very much like our early understanding about neutrinos before. The author also points that an alternative explanation for neutrino oscillations may be the conversion between mass-less neutrinos with different flavors expressed in different “lowest limited momentum” during their flight journey, which originates from that the argument in the squared sine function of the probability of neutrino oscillation may be less than zero, which is mathematical foresight and may not be ignored.
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
文摘Next-generation 6G networks seek to provide ultra-reliable and low-latency communications,necessitating network designs that are intelligent and adaptable.Network slicing has developed as an effective option for resource separation and service-level differentiation inside virtualized infrastructures.Nonetheless,sustaining elevated Quality of Service(QoS)in dynamic,resource-limited systems poses significant hurdles.This study introduces an innovative packet-based proactive end-to-end(ETE)resource management system that facilitates network slicing with improved resilience and proactivity.To get around the drawbacks of conventional reactive systems,we develop a cost-efficient slice provisioning architecture that takes into account limits on radio,processing,and transmission resources.The optimization issue is non-convex,NP-hard,and requires online resolution in a dynamic setting.We offer a hybrid solution that integrates an advanced Deep Reinforcement Learning(DRL)methodology with an Improved Manta-Ray Foraging Optimization(ImpMRFO)algorithm.The ImpMRFO utilizes Chebyshev chaotic mapping for the formation of a varied starting population and incorporates Lévy flight-based stochastic movement to avert premature convergence,hence facilitating improved exploration-exploitation trade-offs.The DRL model perpetually acquires optimum provisioning strategies via agent-environment interactions,whereas the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.The DRL model perpetually acquires optimum provisioning methods via agent-environment interactions,while the ImpMRFO enhances policy performance for effective slice provisioning.The solution,developed in Python,is evaluated across several 6G slicing scenarios that include varied QoS profiles and traffic requirements.Experimental findings reveal that the proactive ETE system outperforms DRL models and non-resilient provisioning techniques.Our technique increases PSSRr,decreases average latency,and optimizes resource use.These results demonstrate that the hybrid architecture for robust,real-time,and scalable slice management in future 6G networks is feasible.
基金supported by the National Science and Technology Council,Taiwan with grant numbers NSTC 112-2221-E-992-045,112-2221-E-992-057-MY3,and 112-2622-8-992-009-TD1.
文摘DDoS attacks represent one of the most pervasive and evolving threats in cybersecurity,capable of crippling critical infrastructures and disrupting services globally.As networks continue to expand and threats become more sophisticated,there is an urgent need for Intrusion Detection Systems(IDS)capable of handling these challenges effectively.Traditional IDS models frequently have difficulties in detecting new or changing attack patterns since they heavily depend on existing characteristics.This paper presents a novel approach for detecting unknown Distributed Denial of Service(DDoS)attacks by integrating Sliced Iterative Normalizing Flows(SINF)into IDS.SINF utilizes the Sliced Wasserstein distance to repeatedly modify probability distributions,enabling better management of high-dimensional data when there are only a few samples available.The unique architecture of SINF ensures efficient density estimation and robust sample generation,enabling IDS to adapt dynamically to emerging threats without relying heavily on predefined signatures or extensive retraining.By incorporating Open-Set Recognition(OSR)techniques,this method improves the system’s ability to detect both known and unknown attacks while maintaining high detection performance.The experimental evaluation on CICIDS2017 and CICDDoS2019 datasets demonstrates that the proposed system achieves an accuracy of 99.85%for known attacks and an F1 score of 99.99%after incremental learning for unknown attacks.The results clearly demonstrate the system’s strong generalization capability across unseen attacks while maintaining the computational efficiency required for real-world deployment.
基金funded by the National Natural Science Foundation of China,grant number 52306124(received by Dan Huang),URL:https://mp.weixin.qq.com/s/HHNYjgYKAynqYR7ySxYwzQ(accessed on 01 January 2025)the Changsha Municipal Natural Science Foundation,grant number kq2402259(received by Shuai Huang),URL:http://kjj.changsha.gov.cn/zfxxgk/tzgg_27202/202501/t20250122_11726939.html(accessed on 01 January 2025)the Regional Joint Funds of the Natural Science Foundation of Hunan Province,grant num-ber 2025JJ70463(received by Shuai Huang),URL:https://kjt.hunan.gov.cn/kjt/xxgk/tzgg/tzgg_1/202502/t20250212_33585991.html(accessed on 01 January 2025).
文摘Bananas are highly perishable after harvest,and processing them into dried products is a crucial approach to reducing losses and adding their economic values.To address the inefficiency and prolonged duration of traditional hot air drying(HAD)and the quality inconsistency associated with single infrared drying(IRD),this study proposed a novel hot air-infrared combined drying(HAD-IRD)strategy.The effects of HAD,IRD,and HAD-IRD on the drying kinetics,color,rehydration capacity,moisture diffusion mechanism,and sensory quality of banana slices were systematically investigated.The parameters of the combined drying process were optimized using an L_(9)(3^(3))orthogonal experimental design.Results indicated that both IRD and HAD-IRD significantly reduced drying time compared to single HAD.While single IRD achieved a rapid drying rate,the lack of effective convective airflow led to potential case-hardening and unstable product quality.In contrast,the HAD-IRD strategy demonstrated a synergistic effect.The optimal parameters were determined as follows:hot air temperature of 70℃,infrared temperature of 60℃,and radiation distance of 16 cm.Under these optimized conditions,HAD-IRD reduced the total drying time by over 70%while simultaneously yielding products with superior color,higher sensory scores,and improved rehydration ratio.This study confirms that HAD-IRD is an efficient and high-quality drying method for banana slices,providing a reliable theoretical foundation and technical solution for the drying of thermosensitive fruits.
