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

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A Transnational Multi-cloud distributed Monitoring Data Integration System 6

A Transnational Multi-cloud Distributed Monitoring Data Inte...

引用

6th ieee international conference on Computer and Communications, ICCC 2020

作者： Lu, Ming Nie, Zhiyuan Feng, Yatong University of Chinese Academy of Sciences Cloud Database Service BT/IT Lenovo Beijing China Beijing Lenovo Litsoft Co. Ltd. Beijing China

ISBN: (纸本)9781728186351

The complexity of many IT services and facilities has been continuously increasing, and the complexity of related monitoring systems and the difficulty of managing it are also growing rapidly. The integration and analysis of the time-series data acquired from monitoring systems are based on intelligent operation and maintenance. Due to the complex deployment of IT service and its infrastructure, as well as the large scale and high frequency of monitored indicators, the monitoring service and the integration of monitored data are further complicated. In the meantime, monitoring data is featured by low-value density, large volume, high requirements for real-time performance and reliability, complex process of transforming the time series data, which brings great challenges for the existing data integration systems. This paper proposes a distributed monitoring data integration system. The system achieves the efficient and reliable integration of time series monitoring data through a lightweight distributed architecture. Different methods of distributed scheduling are adopted by the system to achieve the elastic scaling of integrated computing power and adjust the load capacities of upstream and downstream time-series databases. The effectiveness of the designed system is verified in a data integration scenario from Prometheus/VictoriaMetrics to InfluxDB. © 2020 ieee.

关键词： Data integration

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Robust sensor Fusion Algorithms Against Voice Command Attacks in Autonomous Vehicles

Robust Sensor Fusion Algorithms Against Voice Command Attack...

引用

ieee international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Jiwei Guan Xi Zheng Chen Wang Yipeng Zhou Alireza Jolfaei Macquarie University Sydney Australia CSIRO Data61 SydneyAustralia

ISBN: (纸本)9781665416597

With recent advances in autonomous driving, voice control systems have become increasingly adopted as human-vehicle interaction methods. This technology enables drivers to use voice commands to control the vehicle and will be soon available in Advanced Driver Assistance systems (ADAS). Prior work has shown that Siri, Alexa and Cortana, are highly vulnerable to inaudible command attacks. This could be extended to ADAS in real-world applications and such an inaudible command threat is difficult to detect due to microphone nonlinearities. In this paper, we aim to develop a more practical solution by using camera views to defend against inaudible command attacks where ADAS are capable of detecting their environment via multi-sensors. To this end, we propose a novel multimodal deep learning classification system to defend against inaudible command attacks. Our experimental results confirm the feasibility of the proposed defense methods and the best classification accuracy reaches 89.2%. Code is available at https://***/ITSEG-MQ/sensor-Fusion-Against-VoiceCommand-Attacks.

关键词： Visualization Ultrasonic imaging Virtual assistants sensor fusion Cameras Reliability engineering Robustness

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Ocular-Net: Lite-Residual Encoder Decoder Network for Accurate Ocular Regions Segmentation in Various sensor Images

Ocular-Net: Lite-Residual Encoder Decoder Network for Accura...

引用

ieee international conference on Big Data and Smart computing (BigComp)

作者： Naqvi, Rizwan Ali Lee, Sang-Woong Loh, Woong-Kee Sejong Univ Dept Intelligent Mechatron Engn Seoul South Korea Gachon Univ Dept Software Seongnam South Korea

ISBN: (纸本)9781728160344

Ocular regions such as iris and sclera yield high accuracy in user's biometrics as well as liveness detection systems. The primary purpose for ocular recognition system is the accurate segmentation of the regions of interest that plays the key role in retaining the accuracy and restraining the errors in the whole system. However, accurate ocular regions segmentation in the images in a physical environment is very challenging owing to the images with low resolution, occlusion, blur, ghost effect, unusual glint, and off-angles. Deep learning algorithms with a convolutional neural network (CNN) has achieved promising results for ocular regions segmentation. However, previous CNN-based methods are unable to find the true boundary of ocular regions in non-ideal situations, which results in reduced reliability and accuracy. To overcome these challenges, we present OcularNet, a deep learning-based lite-residual encoder-decoder network to determine the accurate ocular regions such as iris and sclera. In this way, the true ocular regions can be segmented with the transfer of high-frequency information using residual skip connections. Additionally, the proposed Ocular-Net does not enhance performance on the cost of increasing depth, complexity or number of parameters, in fact, it has much fewer parameters than the previous state-of-the-art methods. We performed comprehensive experiments and obtained optimum performance on iris and sclera datasets.

关键词： ocular biometrics segmentation convolutional neural networks (CNN) deep learning iris sclera

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Parallelization Applied to the Synthesis Methodology and Operation of Complex systems Based on the Analysis and Modelling of their Physical and Chemical Processes 1

Parallelization Applied to the Synthesis Methodology and Ope...

引用

1st international conference on Problems of Informatics, Electronics, and Radio Engineering (PIERE)

作者： Starostin, Igor E. Khalyutin, Sergey P. Altoukhov, Alexei, V Davidov, Albert O. Moscow State Tech Univ Civil Aviat Elect Technol & Aviat Elect Equipment Moscow Russia Moscow State Tech Univ Civil Aviat Moscow Russia Lomonosov Moscow State Univ Moscow Russia

ISBN: (纸本)9781728189901

Authors of the article draw their attention to the study of methodological decomposition and parallelization applied for the tasks of synthesis and operation of complex physical and chemical systems in order to develop a horizontally scalable distributed information system. This system relies on algorithms rooted in a unified approach to the description and modelling of variable physical and chemical processes in the systems under investigation. Then the results of process modelling are applied to synthesize this system model. This model in its turn is used for the tasks of synthesis and operation of studied complex systems. In terms of user interface, the information system of this kind is expandable over various practical domains associated with complex physical and chemical systems (power engineering, chemical technology, cellular biology, meteorology, etc.).

关键词： Synthesis and system operation distributed computing

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Proceedings of PYHPC 2020: 9th Workshop on Python for High-Performance and Scientific computing, Held in conjunction with SC 2020: The international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of PYHPC 2020: 9th Workshop on Python for High-P...

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9th ieee/ACM Workshop on Python for High-Performance and Scientific computing, PYHPC 2020

ISBN: (纸本)9780738110868

The proceedings contain 6 papers. The topics discussed include: accelerating microstructural analytics with Dask for volumetric x-ray images;enabling system wide shared memory for performance improvement in PyCOMPSs applications;experiences in developing a distributed agent-based modeling toolkit with python;data engineering for HPC with python;python workflows on HPC systems;and distributed asynchronous array computing with the jetlag environment.

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Development of a Technique for Detecting distributed Denial-of-Service Attacks in Security systems of Wireless sensor Network 15

Development of a Technique for Detecting Distributed Denial-...

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15th ieee international Scientific and Technical conference on Computer Sciences and Information Technologies, CSIT 2020

作者： Belej, Olexander Lviv Polytechnic National University Department of Computer-Aided Design Lviv Ukraine

ISBN: (纸本)9781728174433

A distributed denial of service attack is a major security challenge in modern communications networks. In this article, we propose models that capture all the key performance indicators of synchronized denial of service protection mechanisms. As a result of the conducted researches, it is found out that thanks to the method of delay detection it is possible to recognize semi-open connections that are caused by synchronous flood and other attacks at an early stage. The study provides a mechanism for assessing the feasibility of introducing and changing the security system of a wireless sensor network. The proposed methodology will allow you to compare the mechanisms of combating denial of service for synchronized failures and choose the optimal protection settings in real-time. © 2020 ieee.

关键词： Wireless sensor networks

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MLIA: modulated LED illumination-based adversarial attack on traffic sign recognition system for autonomous vehicle

MLIA: modulated LED illumination-based adversarial attack on...

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ieee international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Yixuan Shen Yu Cheng Yini Lin Sicheng Long Canjian Jiang Danjie Li Siyuan Dai You Jiang Junbin Fang Zoe Lin Jiang Siu-Ming Yiu Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Guangzhou China Guangdong Provincial Engineering Technology Research Center on VLC Guangzhou China Guangzhou Municipal Key Laboratory of Engineering Technology on VLC Guangzhou China Department of Optoelectronic Engineering Jinan University Guangzhou China Harbin Institute of Technology Shenzhen China Department of Computer Science The University of Hong Kong Hong Kong China

Traffic sign recognition (TSR) system is essential for autonomous vehicle and is vulnerable to security threats from adversarial attacks. The existing adversarial attacks for TSR are invasive and suffer from poor concealment and high computational complexity, and thus have low feasibility in real-world scenarios. This paper proposes a non-invasive modulated LED illumination-based adversarial attack scheme. By generating luminance flashes imperceptible to human eyes through fast intensity modulation of lighting such as LED streetlights and exploiting the rolling shutter mechanism of CMOS sensors of in-vehicle imaging system, the proposed attack scheme can successfully perform adversarial attacks on TSR system by implanting luminance information perturbations into the images acquired by autonomous vehicle and thus poisoning the image data fed into TSR system. Depending on the modulation frequency and pattern of LED illumination, the proposed attack scheme enables denial of service (DoS) attack that leads to traffic sign detection failure and escape attack that leads to traffic sign misclassification, with the advantages of superior concealment, low computational complexity and high practical feasibility. Experiments are conducted with two benchmark datasets (GTSDB and GTSRB) and two state-of-the-art models of TSR detection and TSR classification, YOLOv5m and Sill-Net respectively, in both the digital and physical world. Experimental results show that the proposed DoS attack on the TSR detection model (YOLOv5m) can reach the success rate of 90.00% and the proposed escape attack on the TSR classification model (Sill-Net) can achieve the success rate of 35.00%.

关键词： Computational modeling Lighting Benchmark testing Light emitting diodes sensor systems sensors Security

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LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on sensor Data Streams in Meshed Edge Networks

LOS: Local-Optimistic Scheduling of Periodic Model Training ...

引用

Autonomic computing and Self-Organizing systems (ACSOS),international conference on

作者： Soeren Becker Florian Schmidt Lauritz Thamsen Ana Juan Ferrer Odej Kao Technische Universität Berlin Germany Universitat Oberta de Catalunya Spain

Anomaly detection is increasingly important to handle the amount of sensor data in Edge and Fog environments, Smart Cities, as well as in Industry 4.0. To ensure good results, the utilized ML models need to be updated periodically to adapt to seasonal changes and concept drifts in the sensor data. Although the increasing resource availability at the edge can allow for in-situ execution of model training directly on the devices, it is still often offloaded to fog devices or the cloud. In this paper, we propose Local-Optimistic Scheduling (LOS), a method for executing periodic ML model training jobs in close proximity to the data sources, without overloading lightweight edge devices. Training jobs are offloaded to nearby neighbor nodes as necessary and the resource consumption is optimized to meet the training period while still ensuring enough resources for further training executions. This scheduling is accomplished in a decentralized, collaborative and opportunistic manner, without full knowledge of the infrastructure and workload. We evaluated our method in an edge computing testbed on real-world datasets. The experimental results show that LOS places the training executions close to the input sensor streams, decreases the deviation between training time and training period by up to 40% and increases the amount of successfully scheduled training jobs compared to an in-situ execution.

关键词： Training Adaptation models Job shop scheduling Smart cities Processor scheduling Image edge detection Collaboration

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Load balancing in heterogeneous distributed systems using singleton model 6

Load balancing in heterogeneous distributed systems using si...

引用

6th international conference on Parallel, distributed and Grid computing, PDGC 2020

作者： Saini, Nikhil Rabari, Jeet Padole, Mamta C. Solanki, Vaibhav Department of Computer Science and Engineering IIT Bombay Mumbai India Department of Computer Science and Engineering NIT Calicut Calicut India Department of Computer Science and Engineering The Maharaja Sayajirao University Baroda India

ISBN: (纸本)9781728171326

Load balancing is the process of improving the performance of the system by sharing of workload among the processors. The workload of a machine means the total processing time it requires to execute all the tasks assigned to it. Load balancing is one of the important factors to heighten the working performance of the cloud service provider. The benefits of distributing the workload include increased resource utilization ratio which further leads to enhancing the overall performance thereby achieving maximum client satisfaction. In this paper, we are demonstrating the use of the singleton model for load balancing. © 2020 ieee.

关键词： Balancing

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Handling Inherent Delays in Virtual IoT Gateways 15

Handling Inherent Delays in Virtual IoT Gateways

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15th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Hazra, Saptarshi Duquennoy, Simon Voigt, Thiemo Wang, Peng Lu, Chenguang Cederholm, Daniel RISE SICS Stockholm Sweden KTH Stockholm Sweden Ericsson Res Stockholm Sweden

ISBN: (纸本)9781728105703

Massive deployment of diverse ultra-low power wireless devices in different application areas has given rise to a plethora of heterogeneous architectures and communication protocols. It is challenging to provide convergent access to these miscellaneous collections of communicating devices. In this paper, we propose VGATE, an edge-based virtualized IoT gateway for bringing these devices together in a single framework using SDRs as technology-agnostic radioheads. SDR platforms, however, suffer from large unpredictable delays. We design a GNU Radio-based ieee 802.15.4 experimental setup using LimeSDR, where the data path is time-stamped at various points of interest to get a comprehensive understanding of the characteristics of the delays. Our analysis shows that GNU Radio processing and LimeSDR buffering delays are the major delays. We decrease the LimeSDR buffering delay by decreasing the USB transfer size but show that this comes at the cost of increased processing overhead. We modify the USB transfer packet size to investigate which USB transfer size provides the best balance between buffering delay and processing overhead across two different host computers. Our experiments show that for the best measured configuration the mean and jitter of latency decreases by 37% and 40% respectively for the host computer with higher processing resources. We also show that the throughput is not affected by these modifications.

关键词： Software Radio Edge computing Internet of Things RAN Virtualization ieee 802.15.4

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