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Endogenous Security Formal Definition,Innovation Mechanisms,and Experiment Research in Industrial Internet

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Tsinghua science and Technology 2024年第2期29卷 492-505页

作者： Hongsong Chen Xintong Han Yiying Zhang school of Computer and communication engineering University of Science and Technology BeijingBeijing 100083China

With the rapid development of information technologies,industrial Internet has become more open,and security issues have become more *** endogenous security mechanism can achieve the autonomous immune mechanism without prior ***,endogenous security lacks a scientific and formal definition in industrial ***,firstly we give a formal definition of endogenous security in industrial Internet and propose a new industrial Internet endogenous security architecture with cost ***,the endogenous security innovation mechanism is clearly ***,an improved clone selection algorithm based on federated learning is ***,we analyze the threat model of the industrial Internet identity authentication scenario,and propose cross-domain authentication mechanism based on endogenous key and zero-knowledge *** conduct identity authentication experiments based on two types of blockchains and compare their experimental *** on the experimental analysis,Ethereum alliance blockchain can be used to provide the identity resolution services on the industrial *** of Things Application(IOTA)public blockchain can be used for data aggregation analysis of Internet of Things(IoT)edge ***,we propose three core challenges and solutions of endogenous security in industrial Internet and give future development directions.

关键词： industrial Internet endogenous security architecture federated learning blockchain

Multi-Scale Fusion Model Based on Gated Recurrent Unit for Enhancing Prediction Accuracy of State-of-Charge in Battery Energy Storage Systems

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 405-414页

作者： Hao Liu Fengwei Liang Tianyu Hu Jichao Hong Huimin Ma school of Computer and communication engineering University of Science and Technology BeijingBeijingChina school of Mechanical engineering University of Science and Technology BeijingBeijingChina IEEE

Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric *** overcome the imbalance of existing methods between multi-scale feature fusion and global feature extraction,this paper introduces a novel multi-scale fusion(MSF)model based on gated recurrent unit(GRU),which is specifically designed for complex multi-step SOC prediction in practical *** correlation analysis is first employed to identify SOC-related *** parameters are then input into a multi-layer GRU for point-wise feature ***,the parameters undergo patching before entering a dual-stage multi-layer GRU,thus enabling the model to capture nuanced information across varying time ***,by means of adaptive weight fusion and a fully connected network,multi-step SOC predictions are *** extensive validation over multiple days,it is illustrated that the proposed model achieves an absolute error of less than 1.5%in real-time SOC prediction.

关键词： Electric vehicle battery energy storage system(BESS) state-of-charge(SOC)prediction gated recurrent unit(GRU) multi-scale fusion(MSF).

Scale effect removal and range migration correction for hypersonic target coherent detection

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Journal of Systems engineering and Electronics 2024年第1期35卷 14-23页

作者： WU Shang SUN Zhi JIANG Xingtao ZHANG Haonan DENG Jiangyun LI Xiaolong CUI Guolong school of Information and communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar ***,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual ***,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration *** eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation *** to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation *** last,this paper gives several simulations to assess the viability of ScLRT.

关键词： hypersonic target detection coherent integration(CI) scale effect(SE)removal range migration(RM)correction scaled location rotation transform(ScLRT)

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence Technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng Kaili.Jiang Zhixing Zhou Yuxin Zhao Kailun Tian Haixin Yan Bin Tang school of Information and communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic *** methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative *** paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse *** results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

Graph Signal Reconstruction from Low-Resolution Multi-Bit Observations

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Chinese Journal of Electronics 2024年第1期33卷 153-160页

作者： Zhaoting LIU Chen YU Yafeng WANG Shuchen LIU school of communication engineering Hangzhou Dianzi University

Low hardware cost and power consumption in information transmission, processing and storage is an urgent demand for many big data problems, in which the high-dimensional data often be modelled as graph *** paper considers the problem of recovering a smooth graph signal by using its low-resolution multi-bit quantized observations. The underlying problem is formulated as a regularized maximum-likelihood optimization and is solved via an expectation maximization scheme. With this scheme, the multi-bit graph signal recovery(MB-GSR) is efficiently implemented by using the quantized observations collected from random subsets of graph nodes. The simulation results show that increasing the sampling resolution to 2 or 3 bits per sample leads to a considerable performance improvement, while the energy consumption and implementation costs remain much lower compared to the implementation of high resolution sampling.

关键词： Quantization (signal) Costs Power demand Simulation Energy resolution Signal sampling Signal reconstruction

Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

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Computers, Materials & Continua 2024年第5期79卷 2813-2831页

作者： Zheng Yang Ke Gu Yiming Zuo school of Computer and communication engineering Changsha University of Science and TechnologyChangsha410114China

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

关键词： Federated learning Byzantine attacks backdoor triggers

VKFQ:A Verifiable Keyword Frequency Query Framework with Local Differential Privacy in Blockchain

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Computers, Materials & Continua 2024年第3期78卷 4205-4223页

作者： Youlin Ji Bo Yin Ke Gu school of Computer and communication engineering Changsha University of Science and TechnologyChangsha410114China

With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with secure data *** this paper,we study verifiable keyword frequency(KF)queries with local differential privacy in *** the numerical and the keyword attributes are present in data objects;the latter are sensitive and require privacy ***,prior studies in blockchain have the problem of trilemma in privacy protection and are unable to handle KF *** propose an efficient framework that protects data owners’privacy on keyword attributes while enabling quick and verifiable query processing for KF *** framework computes an estimate of a keyword’s frequency and is efficient in query time and verification object(VO)size.A utility-optimized local differential privacy technique is used for privacy *** data owner adds noise locally into data based on local differential privacy so that the attacker cannot infer the owner of the keywords while keeping the difference in the probability distribution of the KF within the privacy *** propose the VB-cm tree as the authenticated data structure(ADS).The VB-cm tree combines the Verkle tree and the Count-Min sketch(CM-sketch)to lower the VO size and query *** VB-cm tree uses the vector commitment to verify the query *** fixed-size CM-sketch,which summarizes the frequency of multiple keywords,is used to estimate the KF via hashing *** conduct an extensive evaluation of the proposed *** experimental results show that compared to theMerkle B+tree,the query time is reduced by 52.38%,and the VO size is reduced by more than one order of magnitude.

关键词： Security data sharing blockchain data query privacy protection

Rethinking attribute localization for zero-shot learning

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science China(Information sciences) 2024年第7期67卷 184-196页

作者： Shuhuang CHEN Shiming CHEN Guo-Sen XIE Xiangbo SHU Xinge YOU Xuelong LI school of Electronic Information and communication Huazhong University of Science and Technology school of Computer science and engineering Nanjing University of Science and Technology school of Artificial Intelligence Optics and Electronics Northwestern Polytechnical University

Recent advancements in attribute localization have showcased its potential in discovering the intrinsic semantic knowledge for visual feature representations, thereby facilitating significant visual-semantic interactions essential for zero-shot learning(ZSL). However, the majority of existing attribute localization methods heavily rely on classification constraints, resulting in accurate localization of only a few attributes while neglecting the rest important attributes associated with other classes. This limitation hinders the discovery of the intrinsic semantic relationships between attributes and visual features across all *** address this problem, we propose a novel attribute localization refinement(ALR) module designed to enhance the model's ability to accurately localize all attributes. Essentially, we enhance weak discriminant attributes by grouping them and introduce weighted attribute regression to standardize the mapping values of semantic attributes. This module can be flexibly combined with existing attribute localization *** experiments show that when combined with the ALR module, the localization errors in existing methods are corrected, and state-of-the-art classification performance is achieved.

关键词： zero-shot learning attention mechanism attribute localization image classification

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

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China communications 2024年第1期21卷 148-162页

作者： Yizhe Zhao Yanliang Wu Jie Hu Kun Yang school of Information and communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower *** this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)*** joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless *** the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)*** results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

关键词： energy harvesting modulation(EHM) integrated data and energy transfer(IDET) performance analysis wireless data transfer(WDT) wireless energy transfer(WET)