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Jointly beam stealing attackers detection and localization without training:an image processing viewpoint

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Frontiers of Computer Science 2023年第3期17卷 145-160页

作者： Yaoqi YANG Xianglin WEI Renhui XU Weizheng WANG Laixian PENG Yangang WANG College of Communication Engineer Army Engineering University of PLANanjing 210000China The 63rd Research Institute National University of Defense TechnologyNanjing 210007China Department of Computer Science City University of Hong KongHong Kong 999077China

Recently revealed beam stealing attacks could greatly threaten the security and privacy of IEEE 802.11ad communications.The premise to restore normal network service is detecting and locating beam stealing attackers without their cooperation.Current consistency-based methods are only valid for one single attacker and are parametersensitive.From the viewpoint of image processing,this paper proposes an algorithm to jointly detect and locate multiple beam stealing attackers based on RSSI(Received Signal Strength Indicator)map without the training process involved in deep learning-based solutions.Firstly,an RSSI map is constructed based on interpolating the raw RSSI data for enabling high-resolution localization while reducing monitoring cost.Secondly,three image processing steps,including edge detection and segmentation,are conducted on the constructed RSSI map to detect and locate multiple attackers without any prior knowledge about the attackers.To evaluate our proposal’s performance,a series of experiments are conducted based on the collected data.Experimental results have shown that in typical parameter settings,our algorithm’s positioning error does not exceed 0.41 m with a detection rate no less than 91%.

关键词： beam-stealing attacks detection localization image processing

CuInS2/ZnS QDs-based fluorescent probe for detection of Cu2+

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Progress in Natural Science:Materials International 2023年第4期33卷 495-500页

作者： Haiyan Kang Hongchao Geng Sisi Shi Zhongxian Song Yuting Dong Xiaole Yan Chaohai Wang Yanli Mao Qingyun Cai Henan Province Key Laboratory of Water Pollution Control and Rehabilitation Technology Henan University of Urban Construction State Key Laboratory of Chemo/Biosensing and Chemometrics College of Chemistry and Chemical Engineering Hunan University

High concentrations of Cu2+exceeding what the required level for the cellular process can changes the properties of protein, affects the normal function of the body, but also affect the body’s metabolism, so that the body’s immunity appears to decline. detection of Cu2+is important for the environmental monitoring. Here, a fluorescence probe that uses heavy metal-free and properties-superior CuInS2/ZnS was proposed for detection of Cu2+. The fluorescence intensity of CuInS2/ZnS quantum dots(QDs) decreased obviously after Cu2+were added,and the intensity with the concentration of Cu2+showed excellent linear relation within the scope of 0–50 μM, the LOD down to 0.45 μM, a possible detection mechanism was analyzed. The QDs was further applied to the detection of Cu2+in drinking water, manifesting the foreground of the current strategy.

关键词： Cu2+ CuInS2/ZnS QDs detection Fluorescence probe

Efficacy of ctDNA methylation combined with traditional detection modality to detect liver cancer among high-risk patients:A multicenter diagnostic trial

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Chinese Journal of Cancer Research 2023年第1期35卷 58-65页

作者： Maomao Cao Jufang Shi Changfa Xia He Li Wei Cai Xianyun Qi Chunyun Dai Wanqing Chen Office of Cancer Screening National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Prevention and Control of Chronic Noncommunicable Diseases Binhai County Center for Disease Control and PreventionBinhai 224521China Chronic Noncommunicable Diseases Prevention and Treatment Department Yingdong District Center for Disease Control and PreventionFuyang 236142China Department for Chronic Noncommunicable Diseases Control Sheyang Center for Disease Control and PreventionSheyang 224300China

Objective:Circulating tumor DNA(ctDNA)and alpha-fetoprotein(AFP)plus ultrasound(US)have been considered to have high diagnostic accuracy for cancer detection,however,the efficacy of ctDNA methylation combined with the traditional detection modality of liver cancer has not been tested in a Chinese independent cohort.Methods:The high-risk individuals aged between 35 and 70 years who were diagnosed with liver cirrhosis or had moderate and severe fatty liver were eligible for inclusion.All participants were invited to receive a traditional examination[referring to AFP plus US],and ctDNA methylation,respectively.The sensitivity and specificity of different diagnostic tools were calculated.The logistic regression model was applied to estimate the area under the curve(AUC),which was further validated by 10-fold internal cross-validation.Results:A total of 1,205 individuals were recruited in our study,and 39 participants were diagnosed with liver cancer.The sensitivity of AFP,US,US plus AFP,and the combination of US,AFP,and ctDNA methylation was33.33%,56.41%,66.67%,and 87.18%,respectively.The corresponding specificity of AFP,US,US plus AFP,and the combination of all modalities was 98.20%,99.31%,97.68%,and 97.68%,respectively.The AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 65.77%,77.86%,82.18%,and92.43%,respectively.The internally validated AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 67.57%,83.26%,86.54%,and 93.35%,respectively.Conclusions:The ctDNA methylation is a good complementary to AFP and US for the detection of liver cancer.

关键词： Liver cancer detection ctDNA methylation diagnostic performance

A lightweight DDoS detection scheme under SDN context

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Cybersecurity 2023年第1期6卷 75-89页

作者： Kun Jia Chaoge Liu Qixu Liu Junnan Wang Jiazhi Liu Feng Liu State Key Laboratory of Information Security Institute of Information EngineeringBeijingChina School of Cyber Security University of Chinese Acad emy of SciencesBeijing 100049China The Sixth Research Offce Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China

Software-defined networking(SDN),a novel network paradigm,separates the control plane and data plane into dif-ferent network equipment to realize the flexible control of network traffic.Its excellent programmability and global view present many new opportunities.DDoS detection under the SDN context is an important and challenging research field.Some previous works attempted to collect and analyze statistics related to flows,usually recorded in switches,to address DDoS threats.In contrast,other works applied machine learning-based solutions to identify DDos and achieved promising results.Generally,most previous works need to periodically request flow rules or packets to obtain flow statistics or features to detect stealthy exceptions.Nevertheless,the request for flow rules is very time-consuming and CPU-consuming;moreover may congest the communication channel between the controller and the switches.Therefore,we present FORT,a lightweight DDoS detection scheme,which spreads the rule-based detection algorithm at edge switches and determines whether to start it by periodically retrieving the ports state.A time-series algorithm,ARIMA,is utilized to determine the port statistics adaptively,and an SVM algorithm is applied to detect whether a DDoS attack does occur.Representative experiments demonstrate that FORT can significantly reduce the controller load and provide a reliable detection accuracy.Referring to the false alarm rate of 1.24%in the comparison scheme,the false alarm rate of this scheme is only 0.039%,which significantly reduces the probability of false alarm.Besides,by introducing the alarm mechanism,this scheme can reduce the load of the southbound chan-nel by more than 60%in the normal state.

关键词： DDoS Port monitoring Flow rule Software defined network MiniNet RYU controller detection

Image copy-move forgery passive detection based on improved PCNN and self-selected sub-images

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Frontiers of Computer Science 2022年第4期16卷 131-146页

作者： Guoshuai Zhou Xiuxia Tian Aoying Zhou School of Computer Science and Technology ShangHai University of Electric PowerShanghai200090China School of Data Science and Engineering East China Normal UniversityShanghai200062China

Image forgery detection remains a challenging problem.For the most common copy-move forgery detection,the robustness and accuracy of existing methods can still be further improved.To the best of our knowledge,we are the first to propose an image copy-move forgery passive detection method by combining the improved pulse coupled neural network(PCNN)and the self-selected sub-images.Our method has the following steps:First,contour detection is performed on the input color image,and bounding boxes are drawn to frame the contours to form suspected forgery sub-images.Second,by improving PCNN to perform feature extraction of sub-images,the feature invariance of rotation,scaling,noise adding,and so on can be achieved.Finally,the dual feature matching is used to match the features and locate the forgery regions.What’s more,the self-selected sub-images can quickly obtain suspected forgery sub-images and lessen the workload of feature extraction,and the improved PCNN can extract image features with high robustness.Through experiments on the standard image forgery datasets CoMoFoD and CASIA,it is effectively verified that the robustness score and accuracy of proposed method are much higher than the current best method,which is a more efficient image copy-move forgery passive detection method.

关键词： image copy-move forgery passive detection self-selected sub-images pulse coupled neural network(PCNN) dual feature matching

Fluorescence detection of phosphate in an aqueous environment by an aluminum-based metal-organic framework with amido functionalized ligands

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Frontiers of Environmental Science & Engineering 2022年第12期16卷 111-120页

作者： Peng Li Lingqian Dong Han Jin Jingren Yang Yonghui Tu Chao Wang Yiliang He School of Environmental Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China China-UK Low Carbon College Shanghai Jiao Tong UniversityShanghai200240China Department of Instrument Science and Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai200240China

The on-site monitoring of phosphate is important for environmental management.Conventional phosphate detection methods are not appropriate to on-site monitoring owing to the use of complicated detection procedures,and the consequent high cost and maintenance requirements of the detection apparatus.Here,a highly sensitive fluorescence-based method for phosphate detection with a wide detection range was developed based on a luminescent aluminum-based metal-organic framework(Al-MOF).The Al-MOF was prepared by introducing amine functional groups to conventional MIL to enhance phosphate binding,and exhibited excellent fluorescence properties that originated from the ligand-to-metal charge transfer(LMCT).The detection limit was as low as 3.25µmol/L(0.10 mg/L)and the detection range was as wide as 3–350µmol/L(0.10–10.85 mg/L).Moreover,Al-MOF displayed specific recognition toward phosphate over most anions and metal cations,even for a high concentration of the co-existent ions.The mechanism of phosphate detection was analyzed through the characterization of the combination of Al-MOF and phosphate,and the results indicated the high affinity between Al-O and phosphate inhibited that the LMCT process and recovered the intrinsic fluorescence of NH2−H2BDC.The recovery of the developed detection method reached a satisfactory range of 85.1%–111.0%,and the feasibility of on-site phosphate detection was verified using a prototype sensor for tap water and lake water samples.It was demonstrated that the prepared Al-MOF is highly promising for on-site detection of phosphate in an aqueous environment.

关键词： Fluorescence Metal-organic framework Phosphate detection Al-MOF

Nanostructure enabled extracellular vesicles separation and detection

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Nanotechnology and Precision Engineering 2023年第4期6卷 98-120页

作者： Xinyuan He Wei Wei Xuexin Duan State Key Laboratory of Precision Measuring Technology and Instruments Tianjin UniversityTianjin 300072China Department of Chemistry School of ScienceTianjin UniversityTianjin 300072China

Extracellular vesicles(EVs)have recently attracted significant research attention owing to their important biological functions,including cell-to-cell communication.EVs are a type of membrane vesicles that are secreted into the extracellular space by most types of cells.Several biological biomolecules found in EVs,such as proteins,microRNA,and DNA,are closely related to the pathogenesis of human malignancies,making EVs valuable biomarkers for disease diagnosis,treatment,and prognosis.Therefore,EV separation and detection are prerequisites for providing important information for clinical research.Conventional separation methods suffer from low levels of purity,as well as the need for cumbersome and prolonged operations.Moreover,detection methods require trained operators and present challenges such as high operational expenses and low sensitivity and specificity.In the past decade,platforms for EV separation and detection based on nanostructures have emerged.This article reviews recent advances in nanostructure-based EV separation and detection techniques.First,nanostructures based on membranes,nanowires,nanoscale deterministic lateral displacement,and surface modification are presented.Second,high-throughput separation of EVs based on nanostructures combined with acoustic and electric fields is described.Third,techniques combining nanostructures with immunofluorescence,surface plasmon resonance,surface-enhanced Raman scattering,electrochemical detection,or piezoelectric sensors for high-precision EV analysis are summarized.Finally,the potential of nanostructures to detect individual EVs is explored,with the aim of providing insights into the further development of nanostructure-based EV separation and detection techniques.

关键词： Nanostructure Extracellular vesicle Separation detection Individual

PE-EDD:An efficient peer-effect-based financial fraud detection approach in publicly traded China firms

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 469-480页

作者： Hui Xia Hui Ma Ping Cheng School of accounting Chongqing University of TechnologyChongqingChina Chongqing Rural Commercial Bank ChongqingChina

Financial fraud arises from the exaggeration of business interests,and an accurate detection or prediction is a useful tool for both corporate management and capital market systems.A collection of computer technologies has been made on this problem so far,and one of the most important solutions is unsupervised learning algorithms.Among them,most approaches work by analysing the internal relations in financial data and finding a new description of non-fraud firms.However,current studies focus a lot on the geometry attribute of financial data,while overlooking the obvious behaviour patterns and peer effects among firms.This has limited the accuracy of representation and furthermore the detection performance.In this work,a very general class of functions is allowed to represent firms,constraining them by peer effects between firms and presenting an error-distribution-based financial fraud firm detection approach.Experimental results have shown great performance of the proposed approach.

关键词： detection financial fraud NMF peer effect

Is every microorganism detected in the intensive care unit a nosocomial infection?Isn’t prevention more important than detection?

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World Journal of Clinical Cases 2022年第20期10卷 7184-7186页

作者： Fatma Yildirim Irem Karaman Mehmet Yildirim Department of Pulmonary Disease and Critical Care Medicine Pulmonary Intensive Care UnitUniversity of Health SciencesDışkapıYıldırım Beyazıt Training and Research HospitalAnkara 06110Turkey School of Medicine Bahcesehir UniversityIstanbul 34740Turkey Department of Internal Medicine Internal Medicine Intensive Care UnitUniversity of Health SciencesDışkapıYıldırım Beyazıt Training and Research HospitalAnkara 06110Turkey

The present letter to the editor is related to the study entitled“Multidrug-resistant organisms in intensive care units and logistic analysis of risk factors.”Not every microorganism grown in samples taken from critically ill patients can be considered as an infectious agent.Accurate and adequate information about nosocomial infections is essential in introducing effective prevention programs in hospitals.Therefore,the development and implementation of care bundles for frequently used medical devices and invasive treatment devices(e.g.,intravenous catheters and invasive ventilation),adequate staffing not only for physicians,nurses,and other medical staff but also for housekeeping staff,and infection surveillance and motivational feedback are key points of infection prevention in the intensive care unit.

关键词： Critical care Prevention Intensive care unit Nosocomial infection detection