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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

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DDoS-as-a-Smokescreen: Leveraging Netflow Concurrency and Segmentation for Faster Detection 3

DDoS-as-a-Smokescreen: Leveraging Netflow Concurrency and Se...

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3rd EEE international conference on Trust, Privacy and Security in Intelligent systems and Applications (TPS-ISA)

作者： Ricks, Brian Tague, Patrick Thuraisingham, Bhavani Univ Texas Dallas Comp Sci Dept Richardson TX 75083 USA Carnegie Mellon Univ ECE Dept Moffett Field CA USA

ISBN: (纸本)9781665416238

In the ever evolving Internet threat landscape, distributed Denial-of-Service (DDoS) attacks remain a popular means to invoke service disruption. DDoS attacks, however, have evolved to become a tool of deceit, providing a smokescreen or distraction while some other underlying attack takes place, such as data exfiltration. Knowing the intent of a DDoS, and detecting underlying attacks which may be present concurrently with it, is a challenging problem. An entity whose network is under a DDoS attack may not have the support personnel to both actively fight a DDoS and try to mitigate underlying attacks. Therefore, any system that can detect such underlying attacks should do so only with a high degree of confidence. Previous work utilizing flow aggregation techniques with multiclass anomaly detection showed promise in both DDoS detection and detecting underlying attacks ongoing during an active DDoS attack. In this work, we head in the opposite direction, utilizing flow segmentation and concurrent flow feature aggregation, with the primary goal of greatly reduced detection times of both DDoS and underlying attacks. Using the same multi-class anomaly detection approach, we show greatly improved detection times with promising detection performance.

关键词： DDoS distributed denial-of-service smokescreen DDoS-as-a-smokescreen DaaSS anomaly detection intrusion detection concurrent flow segmented flow netflow underlying attack

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Design of Wireless sensor Network Programming Tutorial Module (WSNmesh32) 3

Design of Wireless Sensor Network Programming Tutorial Modul...

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3rd international Symposium on Material and Electrical Engineering conference, ISMEE 2021

作者： Anggraeni, Siska Somantri, Yoyo Wahyudin, Didin Education University of Education Indonesia Department of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9781665423625

The use of Internet of Things technology may have a significant impact on changes in online learning systems in the situation of the COVID-19 pandemic. Learners need a laboratory to use and master the necessary tools or components. However, this is difficult to do in a pandemic situation. The use of remote laboratories can overcome the limitations of practicum media, which is an obstacle for students in learning. This research discusses the creation of WSNMesh32 programming tutorial modules as microcontrollers using Wi-Fi-mesh network topology that can be used in sensor and Microcontroller Practicum courses. This research aims to find out the feasibility and perception of learners towards the WSNMesh32 Programming Tutorial Module as a learning medium in pandemic times. The method used is a quantitative method with the ADDIE model (Analyse, Design, Develop, Implement, Evaluation). Participants consisted of 31 students of the Electrical Engineering Education study program of the Industrial Electronics division 2018. The study was conducted online in light of the ongoing COVID-19 pandemic situation. The feasibility test of the module is carried out by leading discussions and reviews with experts on the material to be presented. Respondents gave a positive response to the module. The results provide the conclusion that the sensor programming tutorial module that has been produced is suitable for use as a tutorial module in sensor and microcontroller practicum courses and can be used in learning in a pandemic situation © 2021 ieee.

关键词： Wireless sensor networks

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Assessment of the Influence of the Color Temperature of Radiation Sources on the Quality of Digital Images Obtained in Mines

Assessment of the Influence of the Color Temperature of Radi...

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Informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Ekaterina V. Zaytseva Alina A. Kochneva Evgeny V. Katuntsov Maria R. Kiba Oksana M. Romakina Department of Informatics and Computer Technologies St. Petersburg Mining University St. Petersburg Russia Department of Information and Communication Technologies ITMO University St. Petersburg Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

This paper considers the application of the least-squares method to calculate polynomial approximation coefficients for the relative spectral sensitivity curves of “light-signal” matrices. The obtained coefficients were used to calculate the radiation utilization factors for the color components R, G, and B. The obtained results showed the interdependence between the color temperature of the radiation sources and the quality of the digital images formed. The calculations were performed for industrial video cameras of SSP-MVCA series. It is intended to use the results obtained to design lighting systems for mines and mine workings. Directions for further research in the field of technical vision in the mining industry are indicated, concerning quantitative indicators of the quality of imaging devices and shooting conditions, such as illumination and sensitivity. An analysis of video cameras main characteristics was carried out, taking into account the peculiarities of filming in the production process and the selection conditions of the optimal mode of the video camera operation. The dependencies for calculating the quantitative characteristics of video cameras for video surveillance in mines have been clarified.

关键词： Sensitivity Digital images Lighting Production Cameras Video surveillance sensor systems sensors Personnel Color temperature

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Breeze-Driven Triboelectric-Electromagnetic Hybrid Generator for Wind Energy Harvesting and Application in Smart Weather Station

Breeze-Driven Triboelectric-Electromagnetic Hybrid Generator...

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Clean Energy Storage and Power Engineering (CESPE), international conference on

作者： Peng Luo Yuchen Wang Chensong Liu Liang Liu Chao Li State Grid Digital Technology Holding Co. LTD. Beijing China

ISBN: (数字)9798331511708

ISBN: (纸本)9798331511715

In distributed energy, wind turbines usually suffer from low harvesting capacity or high cut-in wind speed due to their structures. To tackle this issue, we propose a breeze-driven triboelectric-electromagnetic hybrid generator (BD-TEHG) that can efficiently harvest energy even at low wind speeds. By integrating the low-frequency adaptability of triboelectric nanogenerators (TENGs) with the high-frequency efficiency of electromagnetic generators (EMGs), the BD-TEHG achieves optimized energy conversion across varying wind conditions. By using lightweight rotor materials and a unique wind scoop design, the generator can start at a wind speed as low as 2 m/s, ensuring effective operation in low-wind conditions. Experimental data confirm that the BD-TEHG can generate significant power, providing a consistent and reliable energy source for environmental sensors. By addressing the intermittency of renewable energy sources, reducing reliance on power grids, and minimizing battery replacement needs, this innovation provides a sustainable and efficient solution. The BD-TEHG advances the application of resilient energy systems in environmental monitoring and smart technologies, contributing to the broader utilization of wind energy under challenging conditions.

关键词： Wind energy Wind speed Nanogenerators Generators Hybrid power systems Electromyography Reliability Triboelectricity Intelligent sensors sensor arrays

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NeuroSpectrum Deep Learning Architecture for Automated Spectrum Analysis Resource Optimization

NeuroSpectrum Deep Learning Architecture for Automated Spect...

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Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： K. Tamilselvan T. Senthil B. Buvaneswari Santhiya S Mukesh Soni Department of Information Technology AVS Engineering College Salem India Department of Computer Science and Engineering Sreenivasa Institute of Technology and Management Studies chittoor India Department of Information Technology Panimalar Engineering College Chennai India Department of Computer science and Engineering Excel Engineering College Namakkal India Department of Division of Research and Development Lovely Professional University Phagwara India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Reducing the availability of spectrum, as well as the nature of allocating channels in the present wireless telecommunication networks, is one of the critical issues facing modern wireless technology. Such spectrum sensing methods may not be highly flexible or efficient in environments where the radio spectrum undergoes frequent changes. This work proposes an improved deep learning spectrum sensing model based on CNN with reinforcement learning. The proposed system design calls for a pioneering dual mechanism, incorporating both spectrum analysis and a resource allocation learning model. The framework achieved remarkable performance metrics: 96 The spectrum sensing method achieved a 3% occurrence rate, a 94.8% precision rate for resource allocation, and a 92.7% efficiency in dynamic spectrum use. In the present investigation, we have employed it for different topologies and got 45% improvement in spectrum efficiency and 87% less interference than the conventional techniques. The work challenges deep learning-based spectrum sensing as well as management and indicates that they are prepared for the following generation of the wireless communication network.

关键词： Deep learning Wireless sensor networks Wireless networks Transfer learning Training data sensors Resource management Optimization Spectral analysis Radio spectrum management

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Smart-Hop: Low-Latency Multi-hop Networking for LoRa

Smart-Hop: Low-Latency Multi-hop Networking for LoRa

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international conference on distributed computing in sensor systems (DCOSS)

作者： Absar-Ul-Haque Ahmar Wouter Joosen Danny Hughes imec-DistriNet Computer Science KU Leuven Belgium

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

Low Power Wide Area Networks (LPWANs) provide the Internet of Things (IoT) with energy-efficient, low cost, and long-range networking. LoRaWAN is one of the most widely deployed and studied LPWAN technologies due to its license-free operation and open standard, which has enabled 3rd parties to deploy millions of networks worldwide. LoRa allows transmission range and speed to be traded off by configuring the Spreading Factor (SF) setting. By tuning this parameter, the performance envelope of the network can be configured to favor a higher speed or longer range. While the SF of LoRA provides a simple and elegant means to tailor performance, at the highest spreading factor, maximum throughput drops to a few bits per second, dramatically increasing data extraction times. In this paper, we address this problem by proposing Smart-Hop, a novel multi-hop MAC layer protocol for LoRa which implements low-overhead routing. In contrast to prior work, Smart-Hop exploits the variable range afforded by different SFs to eliminate much of the complexity and overhead of traditional multi-hop mesh networking. Smart-Hop reduces the number of end-devices operating at high SFs while implementing low overhead routing in order to reduce data extraction times. These improvements are achieved while preserving the maximum range offered by LoRa in its highest SF configuration.

关键词： Wireless sensor networks Spread spectrum communication Routing Throughput sensor systems Internet of Things Data mining

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Real-Time Video Streaming using CeforeSim: Simulator to the Real World 40

Real-Time Video Streaming using CeforeSim: Simulator to the ...

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40th ieee international conference on distributed computing systems (ICDCS)

作者： Hayamizu, Yusaku Matsuzono, Kazuhisa Asaeda, Hitoshi Natl Inst Informat & Commun Technol NICT Koganei Tokyo Japan

ISBN: (纸本)9781728170022

Applications of Information-Centric Networking (ICN) technology to future internet of things (IoT) and distributed edge/fog computing are widely discussed in various research committees. In this paper, we demonstrate a real-time video streaming scenario using CeforeSim, an NS-3 based ICN simulator. CeforeSim is based on Cefore, an open-source implementation of ICN, which is compliant with the CCNx packet format standardized by the IRTF ICN Research Group (ICNRG). The virtual interfaces provisioned in CeforeSim expedite seamless interaction between the simulated nodes and physical nodes that run the Cefore applications, thereby affording performance evaluations in various scenarios, such as handover of mobile nodes, large-scale sensor networks, and distributed edge/fog computing with the real environments.

关键词： Information-Centric Networking Content-Centric Networking Cefore Simulator NS-3 Video Streaming

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Vehicle-Mounted Millimeter-Wave Radar Vital Signs Detection and Early Warning Control System

Vehicle-Mounted Millimeter-Wave Radar Vital Signs Detection ...

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Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Wenshan Li Hunan Institute of Traffic Engineering Hengyang Hunan China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Traditional methods of monitoring vital signs in vehicles often fall short when it comes to response time, especially in fast-moving situations. To tackle this, our paper introduces a groundbreaking solution: leveraging millimeter-wave radar technology to monitor vital signs in real time within the vehicle, providing timely alerts when necessary. This approach not only enhances the accuracy of readings but also ensures a swift response that is crucial during vehicle operation. By tapping into the unique abilities of millimeter-wave radar to detect subtle human signs, we propose a novel method that processes radar signals to monitor vital signs like heart rate and respiratory rate. This technique is highly effective in meeting the stringent demands of real-time accuracy and speed, especially while driving. Our system includes three main components: radar sensors, a signal processing unit, and an early-warning control module, working together seamlessly to ensure optimal monitoring. The radar sensor continuously transmits and receives millimeter-wave signals, allowing it to track vital signs without interruption. A specially designed feature extraction algorithm filters out noise and extracts critical information, including heart and respiratory rates. Then, advanced algorithms analyze this data in real time, spotting any abnormalities and triggering alerts through the control module. What sets this system apart is its rigorous testing under various vehicle speeds and environmental conditions, confirming its stability, reliability, and fast response times. In real-world applications, the system responds to a high heart rate in 3.7 to 4.0 seconds and to a rapid breathing rate in 4.1 to 4.3 seconds. This millimeter-wave radar-based system offers a fresh approach to vehicle safety, combining practicality with promising future potential.

关键词： Heart rate Accuracy Signal processing algorithms Millimeter wave radar Real-time systems Stability analysis sensor systems sensors Time factors Monitoring

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Brain sight: a novel system for substituting vision sensor

Brain sight: a novel system for substituting vision sensor

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The 3rd international conference on distributed Sensing and Intelligent systems (ICDSIS 2022)

作者： N. Y. Elsaeed M. M. Alshaarawy A. E. S. Esmaiel S. E. D. Elmahdy O. Abdelhameed M. M. Fakhry N. A. Ogabih N. M. Ali R. El-Deeb Software Engineering Department Faculty of Computers and Information Mansoura University Mansoura 35516 Egypt Computer Science Department Faculty of Computers and Information Mansoura University Mansoura 35516 Egypt

In a world where nearly everything we do depends on sight; it is ever more challenging for the unsighted to cope with it and lead a normal life without being reliant on the presence of a companion. Finding a mechanism to convey visual information to the brain is the most difficult part of the research as well as the development of efficient sensory replacement and augmentation systems. In this paper, we aim to propose Brain Sight as an innovative system to help blind people identifying and discovering things in front of them using vibro-tactile display for vision sensory substitution. Brain Sight is a wearable vest-like fabric containing small vibration motors that displays pulses to map the seen images on the Lower-back of the visually impaired. A deep labeling segmentation and edge detection techniques are applied to the captured image after preprocessing. A simple prototype is implemented and tested with volunteers. Thanks to neuroplasticity and the cognitive cortex inside humans' brain, the implemented vest showed promising results. Without the need for intensive training, Brain Sight enables blind to recognize different shapes and numbers.

关键词： brain computer vision edge detection handicapped aids haptic interfaces image sensors neurophysiology

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ATARAXIS: A Deep Learning Approach for Hardwareless In-Vehicle Presence Detection 3

ATARAXIS: A Deep Learning Approach for Hardwareless In-Vehic...

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3rd ieee international conference on Cognitive Machine Intelligence (ieee CogMI)

作者： Oplenskedal, Magnus Taherkordi, Amir Tam, Peter Hem Norwegian Univ Sci & Technol NTNU Trondheim Norway Univ Oslo Oslo Norway

ISBN: (纸本)9781665416214

Accurately detecting the mobile contexts of public transport vehicles and their passengers is a key requirement of intelligent context-aware services in such systems. A prominent example is in-vehicle presence detection which can be used to provide various services such as automated ticketing, dynamic vehicle distribution, and live route optimization. To use such services in practice, in-vehicle presence detection needs to be close to infallible. However, most existing solutions in this field suffer from low spatiotemporal accuracy. To address this challenge, we introduce ATARAXIS in this paper-an approach to hardwareless in-vehicle presence detection. In particular, we develop a deep convolutional neural network that can be trained to detect, if a user is inside a public transportation vehicle such as a tram, subway, or bus, from the raw sensor events generated by the sensors in a single ordinary smartphone. We show that this information can be used to infer the in-vehicle presence of users over time when combined with other sources such as the GPS trace of the user and that of the public transport vehicles. ATARAXIS has the capability to distinguish between the four user modes: driving a car, riding a bike, walking, and using public transport with an accuracy of 98.69%. This is higher than the accuracy of existing techniques for transport mode detection. We also made experiments on the battery consumption and CPU overhead. The results show that ATARAXIS incurs a negligible computational overhead and power consumption on smartphones, even though we base our approach on sensor data collection and a deep learning model.

关键词： Mobile Context In-Vehicle Presence Detection Transport Mode Detection sensor Event Streams Analysis Deep Learning Intelligent Transportation

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