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An Improved Northern Goshawk Optimization Algorithm for Feature Selection

Journal of Bionic Engineering 2024年第4期21卷 2034-2072页

作者： Rongxiang Xie Shaobo Li Fengbin Wu State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China

Feature Selection(FS)is an important data management technique that aims to minimize redundant information in a *** work proposes DENGO,an improved version of the Northern Goshawk Optimization(NGO),to address the FS *** NGO is an efficient swarm-based algorithm that takes its inspiration from the predatory actions of the northern *** order to overcome the disadvantages that NGO is prone to local optimum trap,slow convergence speed and low convergence accuracy,two strategies are introduced in the original NGO to boost the effectiveness of ***,a learning strategy is proposed where search members learn by learning from the information gaps of other members of the population to enhance the algorithm's global search ability while improving the population ***,a hybrid differential strategy is proposed to improve the capability of the algorithm to escape from the trap of the local optimum by perturbing the individuals to improve convergence accuracy and *** prove the effectiveness of the suggested DENGO,it is measured against eleven advanced algorithms on the CEC2015 and CEC2017 benchmark functions,and the obtained results demonstrate that the DENGO has a stronger global exploration capability with higher convergence performance and ***,the proposed DENGO is used for FS,and the 29 benchmark datasets from the UCL database prove that the DENGO-based FS method equipped with higher classification accuracy and stability compared with eight other popular FS methods,and therefore,DENGO is considered to be one of the most prospective FS ***'s code can be obtained at https://***/matlabcentral/fileexchange/158811-project1.

关键词： Northern goshawk optimization Learning strategy Hybrid differential strategy Numerical optimization Feature selection

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Enhancing Adversarial Example Transferability via Regularized Constrained Feature Layer

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Computers, Materials & Continua 2025年第4期83卷 157-175页

作者： Xiaoyin Yi Long Chen Jiacheng Huang Ning Yu Qian Huang School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Chongqing Key Laboratory of Public Big Data Security Technology Chongqing401420China School of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Cyberspace Big Data Intelligent Security Ministry of EducationChongqing400065China Artificial Intelligence and Big Data College Chongqing Polytechnic University of Electronic TechnologyChongqing401331China

Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior *** is achieved by leveraging the property of adversarial *** is,when generated from a surrogate model,they retain their features if applied to other models due to their good ***,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source ***,when attempting black-box transfer attacks on different target models,their effectiveness is *** solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency *** are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial ***,a regularized loss function is used to enhance the black-box transferability between different target *** proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.

关键词： Adversarial examples black-box transferability regularized constrained transfer-based adversarial attacks

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Blockchain and signcryption enabled asynchronous federated learning framework in fog computing

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Digital Communications and Networks 2025年第2期11卷 442-454页

作者： Zhou Zhou Youliang Tian Jinbo Xiong Changgen Peng Jing Li Nan Yang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal UniversityFuzhou 350117China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic TechnologyGuilin 541004China

Federated learning combines with fog computing to transform data sharing into model sharing,which solves the issues of data isolation and privacy disclosure in fog ***,existing studies focus on centralized single-layer aggregation federated learning architecture,which lack the consideration of cross-domain and asynchronous robustness of federated learning,and rarely integrate verification mechanisms from the perspective of *** address the above challenges,we propose a Blockchain and Signcryption enabled Asynchronous Federated Learning(BSAFL)framework based on dual aggregation for cross-domain *** particular,we first design two types of signcryption schemes to secure the interaction and access control of collaborative learning between ***,we construct a differential privacy approach that adaptively adjusts privacy budgets to ensure data privacy and local models'availability of intra-domain ***,we propose an asynchronous aggregation solution that incorporates consensus verification and elastic participation using ***,security analysis demonstrates the security and privacy effectiveness of BSAFL,and the evaluation on real datasets further validates the high model accuracy and performance of BSAFL.

关键词： Blockchain Signcryption Federated learning Asynchronous Fog computing

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CSNet:A Count-Supervised Network via Multiscale MLP-Mixer for Wheat Ear Counting

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植物表型组学（英文） 2024年第4期6卷 995-1009页

作者： Yaoxi Li Xingcai Wu Qi Wang Zhixun Pei Kejun Zhao Panfeng Chen Gefei Hao State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationGuiyang 550025China

Wheat is the most widely grown crop in the world,and its yield is closely related to global food *** number of ears is important for wheat breeding and yield ***,automated wheat ear counting techniques are essential for breeding high-yield varieties and increasing grain ***,all existing methods require position-level annotation for training,implying that a large amount of labor is required for annotation,limiting the application and development of deep learning technology in the agricultural *** address this problem,we propose a count-supervised multiscale perceptive wheat counting network(CSNet,count-supervised network),which aims to achieve accurate counting of wheat ears using quantity *** particular,in the absence of location information,CSNet adopts MLP-Mixer to construct a multiscale perception module with a global receptive field that implements the learning of small target attention maps between wheat ear *** conduct comparative experiments on a publicly available global wheat head detection dataset,showing that the proposed count-supervised strategy outperforms existing position-supervised methods in terms of mean absolute error(MAE)and root mean square error(RMSE).This superior performance indicates that the proposed approach has a positive impact on improving ear counts and reducing labeling costs,demonstrating its great potential for agricultural counting *** code is available at .

关键词： network counting csnet mlp-mixer multiscale supervised wheat

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Physics-Constrained Robustness Enhancement for Tree Ensembles Applied in Smart Grid

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Computers, Materials & Continua 2024年第8期80卷 3001-3019页

作者： Zhibo Yang Xiaohan Huang Bingdong Wang Bin Hu Zhenyong Zhang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China

With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and ***,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their *** address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree *** algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical *** our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical *** results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.

关键词： Tree ensemble robustness enhancement adversarial attack smart grid

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Einocchio: Efficiently Outsourcing Polynomial Computation with Verifiable Computation and Optimized Newton Interpolation

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IEEE Transactions on Information Forensics and security 2025年 20卷 1981-1992页

作者： Pei, Xintao Chen, Yuling Long, Yangyang Sang, Haiwei Luo, Yun Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China

Cloud computing, as a promising service platform, has gained significant popularity in addressing emerging data privacy issues in applications such as machine learning and data mining. Researchers have proposed the verifiable computing that allows the cloud users to delegate their computation tasks to the cloud server. Then, the cloud server computes the cryptographic proofs that verify the correctness of the results, a process that is generally faster ompared to local manual computation. However, performing computation tasks or verifying the correctness of encrypted data, such as multivariate polynomial functions, remains a significant challenge. To solve this problem, we propose Einocchio: A verifiable computation scheme that combines the efficient Pinocchio system with homomorphic encryption, which allows the public verification of the computational results on the server side while ensuring data confidentiality and the results. Compared with the existing solutions, Einocchio does not reveal the client's input. Furthermore, we extrapolate Einocchio by optimizing the Pinocchio's quadratic arithmetic program component using a differential optimization method, which reduces the computational workload owing to the conversion from quadratic to linear complexity, thereby increasing the efficiency of the quadratic arithmetic program preprocessing stage. security analysis demonstrates that Einocchio achieves IND-CPA security. Finally, the performance evaluation confirmed its effectiveness and suitability for cloud computing environments. Compared to the corresponding scheme based on Newton interpolation, Einocchio achieves a threefold greater computational efficiency, with the generation of interpolation polynomials for 50 data inputs occurring in a mere 0.31 ms, while simultaneously reducing the number of computations. © 2005-2012 IEEE.

关键词： Cloud platforms

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Blockchain-Based key Management Scheme Using Rational Secret Sharing

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Computers, Materials & Continua 2024年第4期79卷 307-328页

作者： Xingfan Zhao Changgen Peng Weijie Tan Kun Niu State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Guizhou Big Data Academy Guizhou UniversityGuiyang550025China

Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a research focus for blockchain private key *** security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset *** threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public *** design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public *** proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart *** to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.

关键词： Blockchain smart contract rational secret sharing key management

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Achieving dynamic privacy measurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT

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Digital Communications and Networks 2024年第2期10卷 380-388页

作者： Renwan Bi Mingfeng Zhao Zuobin Ying Youliang Tian Jinbo Xiong Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber SecurityFujian Normal UniversityFuzhou350117China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin541004China Faculty of Data Science City University of Macao999078MacaoChina State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China

With the maturity and development of 5G field,Mobile Edge CrowdSensing(MECS),as an intelligent data collection paradigm,provides a broad prospect for various applications in ***,sensing users as data uploaders lack a balance between data benefits and privacy threats,leading to conservative data uploads and low revenue or excessive uploads and privacy *** solve this problem,a Dynamic Privacy Measurement and Protection(DPMP)framework is proposed based on differential privacy and reinforcement ***,a DPM model is designed to quantify the amount of data privacy,and a calculation method for personalized privacy threshold of different users is also ***,a Dynamic Private sensing data Selection(DPS)algorithm is proposed to help sensing users maximize data benefits within their privacy ***,theoretical analysis and ample experiment results show that DPMP framework is effective and efficient to achieve a balance between data benefits and sensing user privacy protection,in particular,the proposed DPMP framework has 63%and 23%higher training efficiency and data benefits,respectively,compared to the Monte Carlo algorithm.

关键词： Mobile edge crowdsensing Dynamic privacy measurement Personalized privacy threshold Privacy protection Reinforcement learning

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Towards Adapting CLIP for Gaze Object Prediction

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Proceedings of the ACM on Human-Computer Interaction 2024年第ISS期8卷 155-164页

作者： Chen, Dazhi Gou, Gang State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang China

This paper aims to investigate the problem of gaze object prediction in single images. We propose an application-friendly network based on CLIP for gaze object prediction. To avoid domain bias, we utilize a shallow feature adapter that transfers pre-trained features to target-oriented ones. Secondly, we introduce a pooling attention block to exploit the joint representation of multimodal elements, reducing gaze point deviation. Additionally, we introduce a loss that measures the prediction quality by comparing the distribution difference between the model's predictions heatmaps and the ground truth. Extensive experiments demonstrate the superior performance of our model compared to previous models. We will provide the method code at: https://***/fadaishaitaiyang/***. © 2024 Copyright is held by the owner/author(s). publication rights licensed to ACM.

关键词： Prediction models

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Production of higher excited quarkonium pair at the super Z factory

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Chinese Physics C 2024年第7期48卷 45-54页

作者：廖其力蒋军 Chongqing College of Mobile Telecommunications Chongqing 401520China Chongqing Key Laboratory of Public Big Data Security Technology Chongqing 401520China School of Physics Shandong UniversityJinan 250100China

The heavy constituent quark pair of the heavy quarkonium is produced perturbatively and subsequently undergoes hadronization into the bound state *** production of the heavy quarkonium is essential to testing our understanding of quantum chromodynamics(QCD)in both perturbative and non-perturbative *** electron-positron collider will provide a suitable platform for the precise study of the heavy *** higher excited heavy quarkonium may contribute significantly to the ground states,which should be considered for sound *** study the production rates of the higher excited states quarkonium pair in■at the future Z factory under the non-relativistic QCD(NRQCD)framework,where the■represents the color-singlet states■The differential angle distribution of cross sections■is *** also discuss the uncertainties of cross sections caused by the varying quark masses and the renormalization scaleμ.We show that significant numbers of events for pairs of higher excited state quarkonia can be generated at the super Z factory.

关键词： Z boson decays pair of higher excited quarkonia NRQCD D0I:10.1088/1674-1137/ad3c2e

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