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industrial control Anomaly Detection Based on Distributed Linear Deep Learning

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Computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research center of industrial Internet security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

SOPA-GA-CNN: Synchronous optimisation of parameters and architectures by genetic algorithms with convolutional neural network blocks for securing industrial Internet-of-Things

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IET Cyber-Systems and Robotics 2023年第1期5卷 51-66页

作者： Jia-Cheng Huang Guo-Qiang Zeng Guang-Gang Geng Jian Weng Kang-Di Lu College of Cyber security and the National Joint Engineering Research center of Network security Detection and Protection Technology Jinan UniversityGuangzhouChina National-Local Joint Engineering Research center of Digitalize Electrical Design Technology Wenzhou UniversityWenzhouChina National Laboratory of industrial control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhouChina

In recent years,deep learning has been applied to a variety of scenarios in industrial Internet of Things(IIoT),including enhancing the security of ***,the existing deep learning methods utilised in IIoT security are manually designed by heavily relying on the experience of the *** authors have made the first contribution concerning the joint optimisation of neural architecture search and hyper-parameters optimisation for securing IIoT.A novel automated deep learning method called synchronous optimisation of parameters and architectures by GA with CNN blocks(SOPA-GA-CNN)is proposed to synchronously optimise the hyperparameters and block-based architectures in convolutional neural networks(CNNs)by genetic algorithms(GA)for the intrusion detection issue of *** efficient hybrid encoding strategy and the corresponding GA-based evolutionary operations are designed to characterise and evolve both the hyperparameters,including batch size,learning rate,weight optimiser and weight regularisation,and the architectures,such as the block-based network topology and the parameters of each CNN *** experimental results on five intrusion detection datasets in IIoT,including secure water treatment,water distribution,Gas Pipeline,Botnet in Internet of Things and Power System Attack Dataset,have demonstrated the superiority of the proposed SOPA-GA-CNN to the state-of-the-art manually designed models and neuron-evolutionary methods in terms of accuracy,precision,recall,F1-score,and the number of parameters of the deep learning models.

关键词： cyber-systems deep learning deep neural network Internet of things swarm intelligence

Ultrasonic enhancement of persulfate oxidation system governs emerging pollutants decontamination

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Green Energy & Environment 2024年第11期9卷 1666-1678页

作者： Yanpan Li Yanbo Zhou Yi Zhou National Engineering Research center of industrial Wastewater Detoxication and Resource Recovery State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical ProcessEast China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Engineering Research center for Multi-media Environmental Catalysis and Resource Utilization East China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Institute of Pollution control and Ecological security Shanghai200092China

Emerging contaminants (ECs) are widely present in aquatic environments, posing potential risks to both ecosystems and human health. Theultrasound-assisted persulfate oxidation process has attracted considerable attention in the degradation of ECs due to its ability to generate bothsulfate radicals and cavitation effects, enhancing degradation effects. In this paper, the principle of ultrasonic synergistic Fenton-like oxidationsystem for degrading organic pollutants was reviewed, divided into homogeneous system, non-homogeneous system, and single-atom system toexplore the synergistic effect of ultrasound-enhanced persulfate technology in three aspects, and the effects of environmental factors such asultrasonic frequency and power, system pH, temperature, and initial oxidant concentration on the system's decontamination performance werediscussed. Finally, future research on ultrasonically activated persulfate technology is summarized and prospected.

关键词： Ultrasound Persulfate Emerging contaminants Reaction mechanism Synergistic effects

Electroreduction of hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a back propagation neural network

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Frontiers of Environmental Science & Engineering 2023年第8期17卷 69-79页

作者： Xinwan Zhang Guangyuan Meng Jinwen Hu Wanzi Xiao Tong Li Lehua Zhang Peng Chen National Engineering Laboratory for industrial Wastewater Treatment School of Resources and Environmental EngineeringEast China University of Science and TechnologyShanghai 200237China Continuing Education center Bozhou UniversityBozhou 236800China State Environmental Protection Key Laboratory of Environmental Risk Assessment and control on Chemical Process East China University of Science and TechnologyShanghai 200237China Shanghai Institute of Pollution control and Ecological security Shanghai 200092China

Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI),but shortcomings are tedious preparation and short ***,porous titanium available in the market was studied as a flow-through electrode for Cr(VI)*** addition,the intelligent prediction of electrolytic performance based on a back propagation neural network(BPNN)was *** studies revealed that Cr(VI)electroreduction was a diffusion-controlled *** of the flow-through mode achieved a high limiting diffusion current as a result of enhanced mass transfer and favorable *** of Cr(VI)in the flow-through system was 1.95 times higher than in a parallel-plate electrode *** the influent(initial pH 2.0 and 106 mg/L Cr(VI))was treated at 5.0 V and a flux of 51 L/(h·m2),a reduction efficiency of~99.9%was obtained without cyclic electrolysis *** served as the supporting electrolyte and pH regulator,as reactive CrSO72−species were formed as a result of feeding HSO4−.Cr(III)was confirmed as the final product due to the sequential three-electron transport or disproportionation of the *** developed BPNN model achieved good prediction accuracy with respect to Cr(VI)electroreduction with a high correlation coefficient(R2=0.943).Additionally,the electroreduction efficiencies for various operating inputs were predicted based on the BPNN model,which demonstrates the evolutionary role of intelligent systems in future electrochemical technologies.

关键词： Flow-through electrode Hexavalent chromium Heavy metals Neural network Artificial intelligence

Efficient photocatalytic NADH regeneration with Rh-loaded Z-scheme mediator-free system

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Chinese Chemical Letters 2024年第2期35卷 496-500页

作者： Yi Zhou Yiling He Ming Gao Ningkai Ding Juying Lei Yanbo Zhou State Environmental Protection Key Laboratory of Environmental Risk Assessment and control on Chemical Process East China University of Science and TechnologyShanghai 200237China National Engineering Research center of industrial Wastewater Detoxication and Resource Recovery East China University of Science and TechnologyShanghai 200237China Shanghai Engineering Research center for Multi-media Environmental Catalysis and Resource Utilization East China University of Science and TechnologyShanghai 200237China Shanghai Institute of Pollution control and Ecological security Shanghai 200092China

Nicotinamide adenine dinucleotide(NADH)regeneration is necessary for the sustainable application of enzymatic *** Rh-based complex[Cp^(*)Rh(bpy)(H)]+has been widely used as an important mediator in NADH regeneration systems,but it is limited by complexity and high ***,a Z-scheme was constructed by loading Rh onto carbon nitride nanosheets/carbon nitride quantum dots(CN-CNQD).The resultant catalyst achieved a high yield of NADH in a mediator-free(M-free)system of 0.283 mmol L^(−1) g^(−1) min^(−1),which is 5.29 times that of pure *** enzyme introduction experiments confirmed that the enzyme active product 1,4-NADH could reach 34.21%selectivity in the M-free *** research revealed that the heterojunction between CNs and CNQDs improved the NADH regeneration activity in the traditional M-involved system,while Rh loading was proved to optimize the yield and selectivity of 1,4-NADH in M-free *** immobilized Rh shows more competitiveness than[Cp^(*)Rh(bpy)(H)]^(+).This study contributes to the construction of an M-free system for further application in greener,lower-cost enzymatic processes.

关键词： Photocatalysis NADH regeneration Mediator-free Carbon nitride Z-scheme

A Material Identification Approach Based on Wi-Fi Signal

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Computers, Materials & Continua 2021年第12期69卷 3383-3397页

作者： Chao Li Fan Li Wei Du Lihua Yin Bin Wang Chonghua Wang Tianjie Luo Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510700China PCL Research center of Cyberspace security Peng Cheng LaboratoryShenzhen518052China Department of Computer Science and Computer Engineering University of ArkansasFayetteville72701USA College of Electrical Engineering Zhejiang UniversityHangzhou310058China China industrial control Systems Cyber Emergency Response Team Beijing100040China

Material identification is a technology that can help to identify the type of target *** approaches depend on expensive instruments,complicated pre-treatments and professional *** is difficult to find a substantial yet effective material identification method to meet the daily use *** this paper,we introduce a Wi-Fi-signal based material identification approach by measuring the amplitude ratio and phase difference as the key features in the material classifier,which can significantly reduce the cost and guarantee a high level *** practical measurement of WiFi based material identification,these two features are commonly interrupted by the software/hardware noise of the channel state information(CSI).To eliminate the inherent noise of CSI,we design a denoising method based on the antenna array of the commercial off-the-shelf(COTS)Wi-Fi *** that,the amplitude ratios and phase differences can be more stably utilized to classify the *** implement our system and evaluate its ability to identify materials in indoor *** result shows that our system can identify 10 commonly seen liquids with an average accuracy of 98.8%.It can also identify similar liquids with an overall accuracy higher than 95%,such as various concentrations of salt water.

关键词： Internet of Things Wi-Fi signal channel state information material identification noise elimination

An Improved YOLOv5s-Based Smoke Detection System for Outdoor Parking Lots

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Computers, Materials & Continua 2024年第8期80卷 3333-3349页

作者： Ruobing Zuo Xiaohan Huang Xuguo Jiao Zhenyong Zhang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China School of Information and control Engineering Qingdao University of TechnologyQingdao266520China State Key Laboratory of industrial control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China Key Laboratory of Computing Power Network and Information security Ministry of EducationQilu University of Technology(Shandong Academy of Sciences)Jinan250353China Text Computing&Cognitive Intelligence Engineering Research center of National Education Ministry Guizhou UniversityGuiyang550025China

In the rapidly evolving urban landscape,outdoor parking lots have become an indispensable part of the city’s transportation *** growth of parking lots has raised the likelihood of spontaneous vehicle combus-tion,a significant safety hazard,making smoke detection an essential preventative ***,the complex environment of outdoor parking lots presents additional challenges for smoke detection,which necessitates the development of more advanced and reliable smoke detection *** paper addresses this concern and presents a novel smoke detection technique designed for the demanding environment of outdoor parking ***,we develop a novel dataset to fill the gap,as there is a lack of publicly available *** dataset encompasses a wide range of smoke and fire scenarios,enhanced with data augmentation to ensure robustness against diverse outdoor ***,we utilize an optimized YOLOv5s model,integrated with the Squeeze-and-Excitation Network(SENet)attention mechanism,to significantly improve detection accuracy while maintaining real-time processing ***,this paper implements an outdoor smoke detection system that is capable of accurately localizing and alerting in real time,enhancing the effectiveness and reliability of emergency *** show that the system has a high accuracy in terms of detecting smoke incidents in outdoor scenarios.

关键词： YOLOv5s smoke detection deep learning SENet

Higher N_(2)O production in sequencing batch reactors compared to continuous stirred tank reactors:effect of feast-famine cycles

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Frontiers of Environmental Science & Engineering 2023年第4期17卷 143-154页

作者： Xinjie Yan Xunyu Shen Jipeng Wang Jinlong Zhuang Yu Wang Jinchi Yao Hong Liu Yongdi Liu James P.Shapleigh Wei Li National Engineering Research center of industrial Wastewater Detoxication and Resource Recovery East China University of Science and TechnologyShanghai 200237China State Environmental Protection Key Laboratory of Environmental Risk Assessment and control on Chemical Process School of Resources and Environmental EngineeringEast China University of Science and TechnologyShanghai 200237China School of Environmental and Safety Engineering Changzhou UniversityChangzhou 213164China Shanghai Huayi Group Co.Ltd. Shanghai 201108China Shanghai Institute of Pollution control and Ecological security Shanghai 200237China Department of Microbiology Cornell UniversityIthacaNY 14850USA

Nitrous oxide(N_(2)O)is a potent greenhouse gas that can be emitted during the biological treatment of *** this study,a comparison of the long-term performance characteristics and N_(2)O production of sequencing batch reactors(SBR)and continuous stirred tank reactors(CSTR)during nitrite-based denitrification was *** was found that both reactors had NO_(2)^(-)-N removal efficiencies over 99.9%,but the N_(2)O-N emissions from the SBR reached~2.3%of the removal nitrite-N load,while in the CSTR it never exceeded 0.1%.High frequency sampling during one operation cycle of the SBR demonstrated that the N_(2)O accumulation ratio was~0.1%during the feast period,increased to~1.9%in the first five hours of the famine period,and then gradually reached~2.3%at the end of *** experiments showed that limiting extracellular electron donor is required for N_(2)O accumulation in cells from the SBR-famine period and that cells from the CSTR do not accumulate N_(2)O when either nitrite or carbon is *** notable difference in the two reactor communities was the high level of accumulation of intracellular granules,most likely polyhydroxybutyrate(PHB),in cells during the feast period in the *** assembly and binning found that one genome(PRO1),which is a Thauera,accounted for over half the metagenomic reads in both *** shifts in gene regulation nor community composition explained the observed differences in reactor performance suggesting some post-transcriptional regulation obligatorily linked to antecedent conditions underly increased N_(2)O production in the SBR.

关键词： Denitrifying N_(2)O mitigation SBR CSTR Meta-omics PHB

Detection of Stealthy False Data Injection Attacks Against Cyber-Physical Systems:A Stochastic Coding Scheme

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Journal of Systems Science & Complexity 2022年第5期35卷 1668-1684页

作者： GUO Haibin PANG Zhonghua SUN Jian LI Jun State Key Lab of Intelligent control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongging Innovation center Chongqing 401120China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China China industrial control Systems Cyber Emergency Response Team Beijing 100040China

This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive *** detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI *** order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller *** this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an *** design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection *** minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.

关键词： Attack detection cyber-physical systems(CPSs) stealthy FDI attacks stochastic coding