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2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Isozaki, Yasunori Yoshizawa, Shinya Fujimoto, Yu Ishii, Hideaki Ono, Isao Onoda, Takashi Hayashi, Yasuhiro Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Tokyo Japan Waseda Univ Dept Elect Engn & Biosci Tokyo Japan Cent Res Inst Elect Power Ind Syst Engn Res Lab Tokyo Japan

ISBN: (纸本)9781479949342

In this paper, we consider the impact of cyber attacks on voltage regulation in distribution systems. We employ a centralized control scheme which utilizes voltage measurements from sectionizing switches equipped with sensors for connecting distributed generation. Through detailed case studies by simulations, it is demonstrated that if measurements are falsified by an attacker, voltage violation can occur in the system. However, by equipping the control with a detection algorithm, we verify that the damage can be limited especially when the number of attacked sensors is small. Further discussion is provided on how to enhance the security level of the proposed algorithm.

关键词： distributed power generation power distribution control power grids voltage control voltage measurement attacked sensors centralized control scheme cyber attacks detection algorithm distributed generation distribution power grids distribution systems security level voltage measurements voltage regulation voltage violation Centralized control Conferences detection algorithms Security Sensors Voltage control Voltage measurement Voltage regulation voltage measurement detection algorithms distributed power generation INTEGRATED SHIP CONTROL Security level power distribution control Information warfare dispensing system Power grids Sensors

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The Optimal Application of the algorithms of detection and Data Mining in Honeynet

The Optimal Application of the Algorithms of Detection and D...

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IITA International Conference on Control, Automation and Systems Engineering

作者： Dong Nanping Zhou Guanling Wang Yuping Beijing Union Univ Coll Automat Beijing Peoples R China

ISBN: (纸本)9780769537283

This paper puts forward a technical scheme which properly arranges IDS and optimally applies the algorithms of detection and data mining to the Honeynet environment based on a project of building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the misuse detection rules are updated dynamically with the combination of data-mining algorithm RIPPER. The design makes the classical and mature algorithms of anomaly detection, misuse detection and RIPPER data mining display their technical characteristics and advantages to the largest extent in the project and enable the honeynet to protect the internal control network as expected.

关键词： data mining detection algorithm honeynet optimal design active defense

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High-sensitivity explosives detection using dual-excitation-wavelength resonance-Raman detector

High-sensitivity explosives detection using dual-excitation-...

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SPIE Defense, Security + Sensing Symposium / 15th Annual Meeting on Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing

作者： Yellampalle, Balakishore McCormick, William Wu, Hai-Shan Sluch, Mikhail Martin, Robert Ice, Robert Lemoff, Brian E. WVHTC Fdn Adv Technol Grp Fairmont WV 26554 USA

ISBN: (纸本)9781628410105

A key challenge for standoff explosive sensors is to distinguish explosives, with high confidence, from a myriad of unknown background materials that may have interfering spectral peaks. To meet this challenge a sensor needs to exhibit high specificity and high sensitivity in detection at low signal-to-noise ratio levels. We had proposed a Dual-Excitation-Wavelength Resonance-Raman Detector (DEWRRED) to address this need. In our previous work, we discussed various components designed at WVHTCF for a DEWRRED sensor. In this work, we show a completely assembled laboratory prototype of a DEWRRED sensor and utilize it to detect explosives from two standoff distances. The sensor system includes two novel, compact CW deep-Ultraviolet (DUV) lasers, a compact dual-band high throughput DUV spectrometer, and a highly-sensitive detection algorithm. We choose DUV excitation because Raman intensities from explosive traces are enhanced and fluorescence and solar background are not present. The DEWRRED technique exploits the excitation wavelength dependence of Raman signal strength, arising from complex interplay of resonant enhancement, self-absorption and laser penetration depth. We show measurements from >10 explosives/pre-cursor materials at different standoff distances. The sensor showed high sensitivity in explosive detection even when the signal-to-noise ratio was close to one (similar to 1.6). We measured receiver-operating-characteristics, which show a clear benefit in using the dual-excitation-wavelength technique as compared to a single-excitation-wavelength technique. Our measurements also show improved specificity using the amplitude variation information in the dual-excitation spectra.

关键词： Deep Ultra Violet Resonance Raman Spectroscopy Dual Excitation Wavelengths Explosive detection detection algorithm

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Atrial Fibrillation detection using Time-Varying Coherence Function and Shannon Entropy

Atrial Fibrillation Detection using Time-Varying Coherence F...

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33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Lee, J. McManus, D. Chon, K. Worcester Polytech Inst Dept Biomed Engn Worcester MA 01609 USA Univ Massachusetts Med Ctr Dept Med & Quantitat Hlth Sci Cardiol Div Worcester MA 01605 USA

ISBN: (纸本)9781424441228

We introduce a novel method for automatic detection of Atrial Fibrillation (AF) using time-varying coherence functions (TVCF) and Shannon Entropy (SE). The TVCF is estimated by the multiplication of two time-varying transfer functions (TVTFs). Two TVTFs are obtained using two adjacent data segments with one data segment as the input signal and the other data segment as the output to produce the first TVTF;the second TVTF is produced by reversing the input and output signals. The detection algorithm was tested on RR interval time series derived from two databases: the MIT-BIH Atrial Fibrillation (AF) and the MIT-BIH normal sinus rhythm (NSR). The MIT-BIH database contains a variety of short and long AF beats from 25 subjects and the MIT-BIH NSR database consists of only normal sinus rhythms from 18 subjects. Using the receiver operating characteristic curves from the combination of TVCF and SE, we obtained the accuracy of 97.49%, sensitivity of 97.41% and specificity of 97.54% for the MIT-BIH AF database. Furthermore, the specificity of the MIT-BIH NSR database was 100%.

关键词： Accuracy Atrial fibrillation Coherence Databases MIT-BIH atrial fibrillation RR interval time series Reactive power Rhythm Shannon entropy Time frequency analysis atrial fibrillation detection detection algorithm electrocardiography entropy medical disord

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Heartbeat Estimation and Respiratory Arrhythmia detection Using 24 GHz Radar Signals 22

Heartbeat Estimation and Respiratory Arrhythmia Detection Us...

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IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

作者： Tchameni, Michelle R. Luecken, Volker Schroeder, Udo Diewald, Andreas R. Univ Appl Sci Lab Radar Technol & Opt Syst Trier Germany IEE SA Basics & Math Models Bissen Luxembourg

ISBN: (纸本)9798350387032;9798350387025

In this paper, we propose a novel non-contact method for monitoring vital signs, with a focus on heartbeat estimation using radar signals. Our approach utilizes a cross-correlation method based on a template function to isolate cardiac information from phase-extracted radar signals recorded during breathing. By accurately identifying heartbeat peaks over time, our method demonstrates the potential of radar technology for real-time vital sign monitoring in healthcare applications. Experiments conducted with a 24 GHz FMCW radar system, compared with synchronized ECG data, highlight the efficiency of our approach. Beyond showcasing non-contact cardiac monitoring, our method also sheds light on respiratory arrhythmia, providing valuable insights into the complex dynamics of cardiac and respiratory patterns.

关键词： FMCW radar time measurement vital signs monitoring cross correlation detection algorithm

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Improved YOLOv5s Network for Multi-scale safety Helmet detection 11

Improved YOLOv5s Network for Multi-scale safety Helmet Detec...

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11th International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Zhao, Lin Zhang, Dalong Liu, Yifa Guo, Junli Shi, Zhanhao Zhengzhou Univ Inst Cyberspace Secur Zhengzhou Peoples R China Shandong Agr & Engn Univ Inst Informat Sci & Engn Jinan Peoples R China

ISBN: (纸本)9781665469890

A safety helmet detection model has been developed based on the original YOLOv5 network model, which addresses the problems of low accuracy and poor robustness for small targets in complex natural environments. Firstly, we add the layer to detect small targets, resulting in the shallow detection scale, which makes the model better able to detect small objects. Secondly, introducing the transformer self-attention module in the backbone network, which can extract global features with rich semantic information, improves the detection performance. Thirdly, The Ghost module demands fewer parameters and less computational complexity for features to be generated, reducing the pressure to learn model parameters. Finally, the loss function EIoU Loss is applied to improve the detection accuracy and accelerate the convergence of the model. Experimental results show that the average accuracy means (MAP), accuracy rates (P), and recall rates (R) of the improved algorithm are increased by 1.2%, 0.4%, and 0.2%, respectively while reducing the model size, which proves that the algorithm is more effective than the original algorithm at detecting safety helmets.

关键词： safety helmet small targets YOLOv5 algorithm detection algorithm

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Wild Flame detection Using Weight Adaptive Particle Filter from Monocular Video

Wild Flame Detection Using Weight Adaptive Particle Filter f...

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International Conference on Smart Innovations in Communications and Computational Sciences (ICSICCS)

作者： Cai, Bo Xiong, Lu Zhao, Jianhui Wuhan Univ Sch Comp Wuhan 430072 Hubei Peoples R China Wuhan Univ Informat Ctr Wuhan 430072 Hubei Peoples R China

ISBN: (纸本)9789811089718;9789811089701

Wild flame detection from monocular video is an important step for monitoring of fire disaster. Flame region is complex and keeps varying, thus difficult to be tracked automatically. A weight adaptive particle filter algorithm is proposed in this paper to obtain flame detection with higher accuracy. The particle filter method considers color feature model, edge feature model, and texture feature model and then fuses them into a multi-feature model. During which related adaptive weighting parameters are defined and used for the features. For each particle corresponding to target region being tracked, the proportion of fire pixels in the area is computed with Gaussian mixture model, and then it is used as an additional adaptive parameter for the related particle. The presented algorithm has been tested with real video clips, and experimental results have proved the efficiency of the novel detection method.

关键词： Wildfire detection algorithm Particle filter method Weight adaptive

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Fast Traffic Anomalies detection Using SNMP MIB Correlation Analysis

Fast Traffic Anomalies Detection Using SNMP MIB Correlation ...

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11th International Conference on Advanced Communication Technology

作者： Lee, Dong Cheul Park, Byungjoo Kim, Ki Eung Lee, Jae Jin Network Technology Laboratory KT

ISBN: (纸本)9788955191387

Internet Service Providers(ISPs) should detect and control abnormal traffic fast for stable network management. One of the ways to detect traffic anomalies fast is shortening traffic collecting cycle. However, performance degradation is inevitable if a centralized traffic collection server gathers all traffic data from equipments in a large ISP. This paper presents an enhanced traffic collection algorithm that can gather traffic data frequently without degrading the performance by analyzing SNMP MIB objects' correlation. The algorithm estimates the values of interface group objects by using ip group objects, thus, it reduces the number of collections. We evaluated this algorithm on KORNET backbone network. The performance degradation was not found on the experiment, and the accuracy of the algorithm was fairly good.

关键词： Traffic anomalies detection algorithm SNMP MIB correlation

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Novel ventricular tachyarrhythmia detection enhancement detects undertreated life-threatening arrhythmias

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HEART RHYTHM O2 2022年第1期3卷 70-78页

作者： Wilkoff, Bruce L. Sterns, Laurence D. Katcher, Michael S. Upadhyay, Gaurav Seizer, Peter Kang, Chaoyi Rhude, Jennifer Davis, Kevin J. Fischer, Avi Cleveland Clin Robert & Suzanne Tomsich Sydell & Arnold Miller Family Heart Vasc & Thorac Dept Cardiovasc Med Cleveland OH 44106 USA Royal Jubilee Hosp Div Cardiol Victoria BC Canada Massachusetts Gen Brigham Salem Hosp Salem MA USA Univ Chicago Med Pritzker Sch Med Ctr Arrythmia Care Chicago IL 60637 USA Ostalbklinikum Aalen Dept Cardiol & Angiol Aalen Germany Abbott Sylmar CA USA

BACKGROUND Ventricular tachyarrhythmias (VTA) with low and varying signal amplitudes and morphologies may not be successfully identified utilizing traditional implantable cardioverter-defibrillator algorithms. OBJECTIVE Develop and validate a novel algorithm (VF Therapy Assurance, VFTA) to improve detection and timely delivery of high-voltage therapy (HVT) for these arrhythmias. METHODS Arrhythmia detection was simulated on recorded VTA electrograms (EGMs) utilizing Abbott's *** database. EGMs where an HVT occurred only when VFTA was enabled, or where VFTA provided an HVT > 30 seconds earlier than without VFTA, were readjudicated with physician review. As VFTA never prevents detection or therapy, EGMs where VFTA did not activate or alter HVT were not adjudicated. RESULTS Among 564,353 recorded VTA EGMs from 20,000 devices, VFTA altered HVT in 105 EGMs from 67 devices. Physician adjudication determined that 81.9% (86/105) of these EGMs were true undertreated VTA episodes and would have received appropriate HVT with VFTA enabled. Furthermore, 65% of the episodes (56/86) were ventricular fibrillation, were polymorphic, did not selfterminate during the recording window, or were not amenable antitachycardia pacing. Of those, 87.5% (49/56) would not have elicited HVT without VFTA. Overall, VFTA provided new or earlier appropriate HVT in 0.27% (53/20,000) of devices with an increase in inappropriate HVT in 0.07% (14/20,000) devices. CONCLUSION The VFTA algorithm successfully identifies VTA missed by traditional detection algorithms, owing to undersensed ventricular signals resulting in the rate falling below the programmed detection rate. The use of VFTA increases the likelihood of delivering life-saving HVT.

关键词： detection algorithm Implantable cardioverter-defibrillator High-voltage therapy Undersensing Ventricular tachyarrhythmia

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Design and Implementation of an SNMP-Based Traffic Flooding Attack detection System

Design and Implementation of an SNMP-Based Traffic Flooding ...

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11th Asia-Pacific Network Operations and Management Symposium

作者： Park, Jun-Sang Kim, Myung-Sup Korea Univ Dept Comp & Informat Sci Seoul South Korea

ISBN: (纸本)9783540886228

Recently, as traffic flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion detection Systems (IDSs) focus on detail analysis of packet data, which results ill late detection and a high system burden to cope with high-speed network traffic. In this paper we propose an SNMP-based lightweight and fast detection algorithm for traffic flooding attacks, which minimizes the processing and network overhead of the detection system. minimizes the detection time, and provides high detection rate.

关键词： Traffic Flooding Attack DoS/DDoS SNMP MIB detection algorithm detection Time detection System

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