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Scientific Elegance in NIDS: Unveiling Cardinality Reduction, Box-Cox Transformation, and ADASYN for Enhanced Intrusion Detection

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Computers, Materials & Continua 2024年第6期79卷 3897-3912页

作者： Amerah Alabrah Department of information systems College of Computer and information Sciences King Saud UniversityRiyadh11451Saudi Arabia

The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’private *** intruders actively seek such private data either for sale or other inappropriate ***,national and international organizations have country-level and company-level private information that could be accessed by different network ***,the need for a Network Intruder Detection System(NIDS)becomes essential for protecting these networks and *** the evolution of NIDS,Artificial Intelligence(AI)assisted tools and methods have been widely adopted to provide effective ***,the development of NIDS still faces challenges at the dataset and machine learning levels,such as large deviations in numeric features,the presence of numerous irrelevant categorical features resulting in reduced cardinality,and class imbalance in multiclass-level *** address these challenges and offer a unified solution to NIDS development,this study proposes a novel framework that preprocesses datasets and applies a box-cox transformation to linearly transform the numeric features and bring them into closer *** reduction was applied to categorical features through the binning ***,the class imbalance dataset was addressed using the adaptive synthetic sampling data generation ***,the preprocessed,refined,and oversampled feature set was divided into training and test sets with an 80–20 ratio,and two experiments were *** Experiment 1,the binary classification was executed using four machine learning classifiers,with the extra trees classifier achieving the highest accuracy of 97.23%and an AUC of *** Experiment 2,multiclass classification was performed,and the extra trees classifier emerged as the most effective,achieving an accuracy of 81.27%and an AUC of *** results were evaluated based on training,testing,and total time,and a com

关键词： Adaptive synthetic sampling class imbalance features cardinality network security over sampling

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A high-speed true random number generator based on Ag/SiNx/n-Si memristor

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Frontiers of physics 2024年第1期19卷 241-250页

作者： Xiaobing Yan Zixuan Zhang Zhiyuan Guan Ziliang Fang Yinxing Zhang Jianhui Zhao Jiameng Sun Xu Han Jiangzhen Niu Lulu Wang Xiaotong Jia Yiduo Shao Zhen Zhao Zhenqiang Guo Bing Bai Institute of Life Science and Green Development Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei ProvinceCollege of Electron and Information EngineeringHebei UniversityBaoding 071002China

The intrinsic variability of memristor switching behavior can be used as a natural source of randomness,this variability is valuable for safe applications in hardware,such as the true random number generator(TRNG).However,the speed of TRNG is still be further ***,we propose a reliable Ag/SiNx/n-Si volatile memristor,which exhibits a typical threshold switching device with stable repeat ability and fast switching *** volatile-memristor-based TRNG is combined with nonlinear feedback shift register(NFSR)to form a new type of high-speed dual output ***,the bit generation rate reaches a high speed of 112 kb/*** addition,this new TRNG passed all 15 National Institute of Standards and Technology(NIST)randomness tests without post-processing steps,proving its performance as a hardware security *** work shows that the SiNx-based volatile memristor can realize TRNG and has great potential in hardware network security.

关键词： volatile memristor true random number generator(TRNG) delay time threshold switching device

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Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

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Chinese Physics B 2024年第2期33卷 298-304页

作者：蓝若明刘雪峰李天平白成杰 School of Physics and Electronics Shandong Normal UniversityJinan 250014China Key laboratory of Electronics and information Technology for Space systems National Space Science CenterChinese Academy of SciencesBeijing 100190China

We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed *** method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution *** the characteristics of the human retina system,the resolution distribution follows the principle of gradually *** system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a *** system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.

关键词： spectrometer compressed sensing adaptive gradient multiscale resolution fast measurement

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and information Engineering Jiangsu UniversityZhenjiang 212013China State Key laboratory for Turbulence and Complex systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key laboratory of Multimodal Artificial Intelligence systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng laboratory Shenzhen 518000China State Key laboratory for Management and Control of Complex systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Real-time tracking of fast-moving object in occlusion scene

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Journal of systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key laboratory of systems Control and information Processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

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Computers, Materials & Continua 2024年第3期78卷 3469-3487页

作者： Sureka Sivavelu Venkatesh Palanisamy School of Computer Science Engineering and information systems Vellore Institute of TechnologyVellore632014India

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two sta

关键词： Software defect prediction feature selection nonparametric statistical Torgerson-Gower scaling technique quadratic censored regressive convolution deep neural network softstep activation function nelder-mead method

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2P3FL:A Novel Approach for Privacy Preserving in Financial Sectors Using Flower Federated Learning

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 2035-2051页

作者： Sandeep Dasari Rajesh Kaluri School of Computer Science Engineering and information systems Vellore Institute of TechnologyVellore632014India

The increasing data pool in finance sectors forces machine learning(ML)to step into new *** data has significant financial implications and is *** users data from several organizations for various banking services may result in various intrusions and privacy *** a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global ***,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of *** address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global *** improves the privacy of the local *** analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)***,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and *** experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.

关键词： Federated learning FedAvg FedProx flower framework privacy preservation financial sectors

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Continuous advantage learning for minimum-time trajectory planning of autonomous vehicles

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Science China(information Sciences) 2024年第7期67卷 285-294页

作者： Zhuo LI Weiran WU Jialin WANG Gang WANG Jian SUN School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center China Academy of Launch Vehicle Technology Intelligent Game and Decision Laboratory

This paper investigates the minimum-time trajectory planning problem of an autonomous vehicle. To deal with unknown and uncertain dynamics of the vehicle, the trajectory planning problem is modeled as a Markov decision process with a continuous action space. To solve it, we propose a continuous advantage learning(CAL) algorithm based on the advantage-value equation, and adopt a stochastic policy in the form of multivariate Gaussian distribution to encourage exploration. A shared actor-critic architecture is designed to simultaneously approximate the stochastic policy and the value function, which greatly reduces the computation burden compared to general actor-critic methods. Moreover, the shared actor-critic is updated with a loss function built as mean square consistency error of the advantage-value equation, and the update step is performed several times at each time step to improve data efficiency. Simulations validate the effectiveness of the proposed CAL algorithm and its better performance than the soft actor-critic algorithm.

关键词： trajectory planning continuous advantage learning stochastic policy shared actor-critic

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SAT-Based Automatic Searching for Differential and Linear Trails: Applying to CRAX

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Chinese Journal of Electronics 2024年第1期33卷 72-79页

作者： Yiyi HAN Caibing WANG Zhongfeng NIU Lei HU State Key laboratory of information Security Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences

Boolean satisfiability problem(SAT) is now widely applied in differential cryptanalysis and linear cryptanalysis for various cipher *** generated many excellent results for some ciphers,for example,*** this research,we study the differential and linear propagations through the operations of addition,rotation and XOR(ARX),and construct the SAT *** apply the models to CRAX to search differential trails and linear trails *** this sense,our contnbution can be broadly divided into two *** give the bounds for differential and linear cryptanalysis of Alzette both up to 12 steps,by which we present a 3-round differential attack and a 3-round linear attack for *** construct a 4-round key-recovery attack for CRAX with time complexity289times of 4-round encryption and data complexity 225.

关键词： Ciphers Encryption Complexity theory Time complexity

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Mutual aid instead of mutual restraint:interactive probing for topological charge and phase of a vortex beam of large aberrations

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Photonics Research 2024年第1期12卷 172-182页

作者： SHENGYANG WU BENLI YU LEI ZHANG Key laboratory of Opto-electronic information Acquisition and Manipulation Ministry of EducationAnhui UniversityHefei 230601China information Materials and Intelligent Sensing laboratory of Anhui Province Anhui UniversityHefei 230601China

An imperfect propagation environment or optical system would introduce wavefront aberrations to vortex *** phase aberrations and orbital angular momentum in a vortex beam are proved to be mutually restrictive in parameter *** make traditional topological charge(TC)probing methods ineffective while the phase singularity makes phase retrieval difficult due to the aliasing between the wrapped phase jump and the vortex phase *** interactive probing method is proposed to make measurements of the aberrated phase and orbital angular momentum in a vortex beam assist rather than hinder each *** phase unwrapping is liberated from the phase singularity by an annular shearing interference technique while the TC value is determined by a Moirétechnique immune to *** and experimental results proving the method effective are *** is of great significance to judge the characteristics of vortex beams passing through nonideal environments and optical systems.

关键词： vortex topological beam

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