Intrusion detection systems are increasingly using machine *** machine learning has shown excellent performance in identifying malicious traffic,it may increase the risk of privacy *** paper focuses on imple-menting a...
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Intrusion detection systems are increasingly using machine *** machine learning has shown excellent performance in identifying malicious traffic,it may increase the risk of privacy *** paper focuses on imple-menting a model stealing attack on intrusion detection *** model stealing attacks are hard to imple-ment in practical network environments,as they either need private data of the victim dataset or frequent access to the victim *** this paper,we propose a novel solution called Fast Model Stealing Attack(FMSA)to address the problem in the field of model stealing *** also highlight the risks of using ML-NIDS in network ***,meta-learning frameworks are introduced into the model stealing algorithm to clone the victim model in a black-box ***,the number of accesses to the target model is used as an optimization term,resulting in minimal queries to achieve model ***,adversarial training is used to simulate the data distribution of the target model and achieve the recovery of privacy *** experiments on multiple public datasets,compared to existing state-of-the-art algorithms,FMSA reduces the number of accesses to the target model and improves the accuracy of the clone model on the test dataset to 88.9%and the similarity with the target model to 90.1%.We can demonstrate the successful execution of model stealing attacks on the ML-NIDS system even with protective measures in place to limit the number of anomalous queries.
Despite the existence of plentiful photocatalyst heterojunctions,their separation efficiency and charge flow precision remain low on account of lacking interfacial ***,through a defect-induced heterojunction construct...
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Despite the existence of plentiful photocatalyst heterojunctions,their separation efficiency and charge flow precision remain low on account of lacking interfacial ***,through a defect-induced heterojunction constructing strategy,Ni4Mo alloys were in-situ grown on the unsaturated coordinated sulfur atoms of sulfur vacancies-rich ZCS(Sv-ZCS)via interfacial Ni-S covalent *** experimental and theoretical results reveal that these unsaturated sulfur atoms induced by sulfur vacancies vastly facilitate to anchor more Ni-Mo nanoparticles and form abundant Ni-S covalent bonds,meanwhile,these sulfur vacancies could form dual internal electric field(IEF)and work with Ni-S covalent bonds as“Electron Bridge”to further accelerate photoelectrons transfer,as well as promote the activation of water molecules and the desorption of hydrogen ***,the optimized Ni_(4)Mo/Sv-ZCS composite achieves an improved photocatalytic hydrogen evolution(PHE)rate of 94.69 mmol h^(-1)g^(-1)without an evident decrease after 6 cycles of photocatalytic tests,which is 21.2 and 1.94 times higher than those of Pt/ZCS and Ni_(4)Mo/ZCS,*** tactic opens a new way for optimizing Zn_(x)Cd_(1-x)S-based heterojunctions by constructing sulfur vacancies and covalent bonds as“Electron Bridge”to enhance the activity of PHE.
Self-supervised learning is attracting significant attention from researchers in the point cloud processing field. However, due to the natural sparsity and irregularity of point clouds, effectively extracting discrimi...
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Self-supervised learning is attracting significant attention from researchers in the point cloud processing field. However, due to the natural sparsity and irregularity of point clouds, effectively extracting discriminative and transferable features for efficient training on downstream tasks remains an unsolved challenge. Consequently, we propose PointSmile, a reconstruction-free self-supervised learning paradigm by maximizing curriculum mutual information(CMI) across the replicas of point cloud objects. From the perspective of how-and-what-to-learn, PointSmile is designed to imitate human curriculum learning, i.e.,starting with easier topics in a curriculum and gradually progressing to learning more complex topics in the curriculum. To solve “how-to-learn”, we introduce curriculum data augmentation(CDA) of point *** encourages PointSmile to follow a learning path that starts from learning easy data samples and progresses to learning hard data samples, such that the latent space can be dynamically affected to create better embeddings. To solve “what-to-learn”, we propose maximizing both feature-and class-wise CMI to better extract discriminative features of point clouds. Unlike most existing methods, PointSmile does not require a pretext task or cross-modal data to yield rich latent representations; additionally, it can be easily transferred to various backbones. We demonstrate the effectiveness and robustness of PointSmile in downstream tasks such as object classification and segmentation. The study results show that PointSmile outperforms existing self-supervised methods and compares favorably with popular fully supervised methods on various standard architectures. The code is available at https://***/theaalee/PointSmile.
This paper presents a three-dimensional (3D) guidance law for homing missiles to intercept maneuvering targets, while ensuring a desired final approach angle and satisfying field-of-view (FOV) constraints. First, a li...
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Copper alloy spring materials are widely used in electromechanical components for carrying mechanical load and current load. The mechanical characteristics of such materials are closely related to the reliability and ...
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A key strategy for designing environmental barrier coatings is to incorporate multiple rare-earth(RE)components intoβ-andγ-RE_(2)Si_(2)O_(7)to achieve multifunctional performance ***,the polymorphic phase presents s...
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A key strategy for designing environmental barrier coatings is to incorporate multiple rare-earth(RE)components intoβ-andγ-RE_(2)Si_(2)O_(7)to achieve multifunctional performance ***,the polymorphic phase presents significant challenges for the design of multicomponent RE disilicates.
This study investigates the optimization configuration problem of control moment gyroscopes for flexible vibration suppression of large space ***,the structural dynamic model of an unconstrained plate-like flexible sp...
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This study investigates the optimization configuration problem of control moment gyroscopes for flexible vibration suppression of large space ***,the structural dynamic model of an unconstrained plate-like flexible spacecraft with control moment gyroscopes is established using the Lagrangian method and the finite element ***,an optimization problem is established with the positions of control moment gyroscope array as variables and the linear quadratic index of mechanical energy during vibration process as the objective ***,an improved gray wolf optimizer is used to solve the optimization *** optimization results show that the control moment gyroscopes should be primarily placed on the corners of the spacecraft in a symmetrical ***,the priority of control moment gyroscope installation positions was studied using topological *** results indicate that the control moment gyroscopes should be primarily installed on the corners,followed by the central positions,and then gradually expanded outward.
Graph Neural Networks (GNNs) have gained increasing popularity for graph anomaly detection tasks in recent years. However, existing research has revealed a significant issue: they learn node representations through th...
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CRISPR-Cas systems and IS200/IS605 transposon-associated TnpBs have been utilized for the development of genome editing *** bioinformatics analysis and biochemical experiments,here we present a new family of RNA-guide...
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CRISPR-Cas systems and IS200/IS605 transposon-associated TnpBs have been utilized for the development of genome editing *** bioinformatics analysis and biochemical experiments,here we present a new family of RNA-guided DNA *** bioinformatics analysis initially identifies the stable co-occurrence of conserved RAGATH-18-derived RNAs(reRNAs)and their upstream IS607 TnpBs with an average length of 390 amino ***607 TnpBs form programmable DNases through interaction with *** discover the robust dsDNA interference activity of IS607 TnpB systems in bacteria and human *** characterization of the Firmicutes bacteria IS607 TnpB system(ISFba1 TnpB)reveals that its dsDNA cleavage activity is remarkably sensitive to single mismatches between the guide and target sequences in human *** findings demonstrate that a length of 20 nt in the guide sequence of reRNA achieves the highest DNA cleavage activity for ISFba1 TnpB.A cryo-EM structure of the ISFba1 TnpB effector protein bound by its cognate RAGATH-18 motif-containing reRNA and a dsDNA target reveals the mechanisms underlying reRNA recognition by ISFba1 TnpB,reRNA-guided dsDNA targeting,and the sensitivity of the ISFba1 TnpB system to base mismatches between the guide and target ***,this study identifies the IS607 TnpB family of compact and specific RNA-guided DNases with great potential for application in gene editing.
Biomass carbon and small redox biomolecules are attractive materials for green,sustainable energy storage devices owing to their environmentally friendly,low-cost,scalable,and novel ***,most devices manufactured using...
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Biomass carbon and small redox biomolecules are attractive materials for green,sustainable energy storage devices owing to their environmentally friendly,low-cost,scalable,and novel ***,most devices manufactured using these materials have low specific capacitance,poor cycle stability,short lifetime,complexity,and low precision of device ***,we report the directed self-assembly of mononuclear anthraquinone(MAQ)derivatives and porous lignin-based graphene oxide(PLGO)into a renewable colloidal gel through noncovalent *** self-assembled gel electrode materials exhibited high capacitance(484.8 F g^(−1) at a current density of 1 A g^(−1))and could be further printed as flexible micro-supercapacitors(FMSCs)with arbitrary patterns and a relatively high resolution on specific *** FMSCs exhibited excellent areal capacitance(43.6 mF cm^(−2)),energy and power densities(6.1μWh cm^(−2) and 50μW cm^(−2),respectively),and cycle stability(>10,000 cycles).Furthermore,the printed FMSCs and integrated FMSC arrays exhibited remarkable flexibility while maintaining a stable *** proposed approach can be applied to other quinone biomolecules and biomass-based carbon *** study provides a basis for fabricating green and sustainable energy storage device architectures with high capacitance,long-term cycling,high scalability,and high precision.
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