Early attack detection is essential to ensure the security of complex networks,especially those in critical *** is particularly crucial in networks with multi-stage attacks,where multiple nodes are connected to extern...
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Early attack detection is essential to ensure the security of complex networks,especially those in critical *** is particularly crucial in networks with multi-stage attacks,where multiple nodes are connected to external sources,through which attacks could enter and quickly spread to other network *** attack graphs(BAGs)are powerful models for security risk assessment and mitigation in complex networks,which provide the probabilistic model of attackers’behavior and attack progression in the *** attack detection techniques developed for BAGs rely on the assumption that network compromises will be detected through routine monitoring,which is unrealistic given the ever-growing complexity of *** paper derives the optimal minimum mean square error(MMSE)attack detection and monitoring policy for the most general form of *** exploiting the structure of BAGs and their partial and imperfect monitoring capacity,the proposed detection policy achieves the MMSE optimality possible only for linear-Gaussian state space models using Kalman *** adaptive resource monitoring policy is also introduced for monitoring nodes if the expected predictive error exceeds a user-defined *** and efficient matrix-form computations of the proposed policies are provided,and their high performance is demonstrated in terms of the accuracy of attack detection and the most efficient use of available resources using synthetic Bayesian attack graphs with different topologies.
Resonant operation, exploiting high quality-factor planar inductors, has recently enabled gigahertz (GHz) applications for large-area electronics (LAE), providing a new technology platform for large-scale and flexible...
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This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)*** steganography,a technique of embedding hidden information in digital photographs,should ideally ac...
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This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)*** steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least *** contemporary methods of steganography are at best a compromise between these *** this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic *** approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret *** approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale *** ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual *** evaporation is introduced through iterations to avoid stagnation in solution *** levels of pheromone are modified to reinforce successful pixel *** results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of *** approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.
Six-phase motors are becoming more popular because of their advantages such as lower torque ripple, better power distribution per phase, higher efficiency, and fault-tolerant capability compared to the three-phase one...
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The fast growth in Internet-of-Vehicles(IoV)applications is rendering energy efficiency management of vehicular networks a highly important *** of the existing models are failing to handle the demand for energy conser...
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The fast growth in Internet-of-Vehicles(IoV)applications is rendering energy efficiency management of vehicular networks a highly important *** of the existing models are failing to handle the demand for energy conservation in large-scale heterogeneous *** on Large Energy-Aware Fog(LEAF)computing,this paper proposes a new model to overcome energy-inefficient vehicular networks by simulating large-scale network *** main inspiration for this work is the ever-growing demand for energy efficiency in IoV-most particularly with the volume of generated data and connected *** proposed LEAF model enables researchers to perform simulations of thousands of streaming applications over distributed and heterogeneous *** the possible reasons is that it provides a realistic simulation environment in which compute nodes can dynamically join and leave,while different kinds of networking protocols-wired and wireless-can also be *** novelty of this work is threefold:for the first time,the LEAF model integrates online decision-making algorithms for energy-aware task placement and routing strategies that leverage power usage traces with efficiency optimization in *** existing fog computing simulators,data flows and power consumption are modeled as parameterizable mathematical equations in LEAF to ensure scalability and ease of analysis across a wide range of devices and *** results of evaluation show that LEAF can cover up to 98.75%of the distance,with devices ranging between 1 and 1000,showing significant energy-saving potential through A wide-area network(WAN)usage *** findings indicate great promise for fog computing in the future-in particular,models like LEAF for planning energy-efficient IoV infrastructures.
Total shoulder arthroplasty is a standard restorative procedure practiced by orthopedists to diagnose shoulder arthritis in which a prosthesis replaces the whole joint or a part of the *** is often challenging for doc...
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Total shoulder arthroplasty is a standard restorative procedure practiced by orthopedists to diagnose shoulder arthritis in which a prosthesis replaces the whole joint or a part of the *** is often challenging for doctors to identify the exact model and manufacturer of the prosthesis when it is *** paper proposes a transfer learning-based class imbalance-aware prosthesis detection method to detect the implant’s manufacturer automatically from shoulder X-ray *** framework of the method proposes a novel training approach and a new set of batch-normalization,dropout,and fully convolutional layers in the head *** employs cyclical learning rates and weighting-based loss calculation *** modifications aid in faster convergence,avoid local-minima stagnation,and remove the training bias caused by imbalanced *** proposed method is evaluated using seven well-known pre-trained models of VGGNet,ResNet,and DenseNet *** is performed on a shoulder implant benchmark dataset consisting of 597 shoulder X-ray *** proposed method improves the classification performance of all pre-trained models by 10–12%.The DenseNet-201-based variant has achieved the highest classification accuracy of 89.5%,which is 10%higher than existing ***,to validate and generalize the proposed method,the existing baseline dataset is supplemented to six classes,including samples of two more implant *** results have shown average accuracy of 86.7%for the extended dataset and show the preeminence of the proposed method.
Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems (IDS). Data labeling difficulties, incorrect conclusions, and vulnerability to malicious data i...
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Abstract: The line-start permanent magnet synchronous motor (LSPMSM) is a combination of an induction motor and a permanent magnet (PM) motor. In this motor, due to the presence of a magnet and the resulting braking t...
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Topology is usually perceived intrinsically immutable for a given *** argue that optical topologies do not immediately enjoy such ***'optical skyrmions'as an example,we show that they will exhibit varying text...
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Topology is usually perceived intrinsically immutable for a given *** argue that optical topologies do not immediately enjoy such ***'optical skyrmions'as an example,we show that they will exhibit varying textures and topological invariants(skyrmion numbers),depending on how to construct the skyrmion vector when projecting from real to parameter *** demonstrate the fragility of optical skyrmions under a ubiquitous scenario-simple reflection off an optical *** topology is not without benefit,but it must not be assumed.
VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeV...
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VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.
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