2023 IEEE International Conference on Edge Computing and Communications (EDGE)最新文献_第5页

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00057

J. Sándor, Roland Nagy, L. Buttyán

{"title":"PATRIoTA: A Similarity-based IoT Malware Detection Method Robust Against Adversarial Samples","authors":"J. Sándor, Roland Nagy, L. Buttyán","doi":"10.1109/EDGE60047.2023.00057","DOIUrl":"https://doi.org/10.1109/EDGE60047.2023.00057","url":null,"abstract":"Detecting malware targeting IoT devices has became an important challenge with the recent emergence of IoT botnets. Gateways at the edge between the Internet and IoT devices deployed in the field are particularly well-positioned for the task of malware detection, as malware typically spreads over the Internet and resource-constrained field devices may not have the means to protect themselves. Hence, we believe that, among other things, edge intelligence should also include effective and efficient IoT malware detection. A recently proposed similarity-based IoT malware detection method, called SIMBIoTA, would be suitable in this context, but its robustness against adversarial malware samples has been shown to be rather weak. In this paper, we propose PATRIoTA, a similarity-based IoT malware detection method inspired by SIMBIoTA, but being significantly more robust than SIMBIoTA is. We describe the operation of PATRIoTA, and compare its malware detection performance and robustness against adversarial samples to that of SIMBIoTA. We show that PATRIoTA outperforms SIMBIoTA with respect to both measures.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133093746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Dynamic and Collaborative Deep Inference Framework for Human Motion Analysis in Telemedicine 远程医疗中人体运动分析的动态协同深度推理框架

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00043

Michele Boldo, D. Carra, D. Quaglia, N. Bombieri

引用次数: 0

Copyright Page 版权页

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/edge60047.2023.00003

引用次数: 0

Offload Shaping for Wearable Cognitive Assistance 可穿戴式认知辅助的卸载整形

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00037

Roger Iyengar, Q. Dong, Chanh Nguyen, P. Pillai, M. Satyanarayanan

引用次数: 0

NEOS: Non-intrusive Edge Observability stack based on Zero Trust security model for Ubiquitous Computing 基于零信任安全模型的无侵入性边缘可观察性堆栈

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00023

Abhijit Kumar, Tauseef Ahmed, Konica Saini, J. Kumar

{"title":"NEOS: Non-intrusive Edge Observability stack based on Zero Trust security model for Ubiquitous Computing","authors":"Abhijit Kumar, Tauseef Ahmed, Konica Saini, J. Kumar","doi":"10.1109/EDGE60047.2023.00023","DOIUrl":"https://doi.org/10.1109/EDGE60047.2023.00023","url":null,"abstract":"The Edge computing paradigm has emerged as the new industrial norm for creating distributed applications. These distributed applications need to target high reliability and scalability to meet the goals and requirements of the users. Achieving this definitely requires a real time observability stack to closely observe, track, debug and improve the application. In this paper we introduce the Non-Intrusive Edge Observability Stack(NEOS) that simplifies the process of collecting, analyzing, and visualizing telemetry data. It reduces the amount of code instrumentation needed to collect telemetry data up to 80% and offers extensive configuration capabilities within the subcomponents of the process. It offers a set of user-friendly abstractions and easy-to-use APIs, which minimizes the effort needed for manual instrumentation of application code. NEOS leverages popular open-source tools such as OpenTelemetry, Grafana, Prometheus, Jaeger, and Loki, for the collecting and visualizing of telemetry data. Furthermore, NEOS implements security based on the zero-trust model, which means that we assume that no user or system can be trusted by default. The security of every connection establised in NEOS employs mutual Transport Layer Security (mTLS) to prevent unauthorized access and safeguard sensitive data. Experiments were conducted to assess the efficiency of the stack by comparing the time and effort needed to instrument code with and without the stack. The outcomes showed a considerable reduction in instrumentation code. NEOS can be used by product managers, engineering and operation team for system and application health monitoring, real-time business insights, and debugging system.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124991333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Domain modeling for scenario sensing and edge decision-making 面向场景感知和边缘决策的领域建模

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00028

Haoran Shi, Shijun Liu, Li Pan

{"title":"Domain modeling for scenario sensing and edge decision-making","authors":"Haoran Shi, Shijun Liu, Li Pan","doi":"10.1109/EDGE60047.2023.00028","DOIUrl":"https://doi.org/10.1109/EDGE60047.2023.00028","url":null,"abstract":"The introduction of numerous edge computing nodes allows application systems to sense and make decisions in real-time but also brings new challenges. The diversity of application scenarios and the complexity of application processes can be effectively addressed through modeling. This paper proposes a modeling approach for manufacturing scenario sensing and edge decision-making. Firstly, an abstract meta-model (SMM) is defined, which provides a unified description of the resources and processes in the scenario and the interaction between the scenario and the edge. Based on the meta-model, an application scenario model (ASM) can be constructed for a specific scenario to support edge data feedback and decision-making for abnormal events. In addition, the model is constructed in a scenario modeling tool and validated in a simulated manufacturing production line, that is, whether the models can provide effective support for decision-making of abnormal events. The results demonstrate that mapping normalized models into codes at the edge computing nodes can improve the accuracy and real-time performance of decision-making.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127047564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey of Faults and Fault-Injection Techniques in Edge Computing Systems 边缘计算系统故障与故障注入技术综述

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-07-01 DOI: 10.1109/EDGE60047.2023.00021

M. Pourreza, P. Narasimhan

引用次数: 0

When Edge Meets FaaS: Opportunities and Challenges 当边缘遇到FaaS:机遇和挑战

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-06-29 DOI: 10.1109/EDGE60047.2023.00016

Runyu Jin, Qirui Yang, Mingde Zhao

引用次数: 0

Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices 准确校准NVIDIA Jetson设备上的内部功率传感器的功率测量

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-06-19 DOI: 10.1109/EDGE60047.2023.00034

N. Shalavi, A. Khoshsirat, M. Stellini, A. Zanella, Michele Rossi

{"title":"Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices","authors":"N. Shalavi, A. Khoshsirat, M. Stellini, A. Zanella, Michele Rossi","doi":"10.1109/EDGE60047.2023.00034","DOIUrl":"https://doi.org/10.1109/EDGE60047.2023.00034","url":null,"abstract":"Power efficiency is a crucial consideration for embedded systems design, particularly in the field of edge computing and IoT devices. This study aims to calibrate the power measurements obtained from the built-in sensors of NVIDIA Jetson devices, facilitating the collection of reliable and precise power consumption data in real-time. To achieve this goal, accurate power readings are obtained using external hardware, and a regression model is proposed to map the sensor measurements to the true power values. Our results provide insights into the accuracy and reliability of the built-in power sensors for various Jetson edge boards and highlight the importance of calibrating their internal power readings. In detail, internal sensors underestimate the actual power by up to 50% in most cases, but this calibration reduces the error to within ±3%. By making the internal sensor data usable for precise online assessment of power and energy figures, the regression models presented in this paper have practical applications, for both practitioners and researchers, in accurately designing energy-efficient and autonomous edge services.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"53 37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Onboard Object Detection for Augmented Reality: Enhancing Head-Mounted Display with YOLOv8 实时机载目标检测增强现实:增强头戴式显示器与YOLOv8

2023 IEEE International Conference on Edge Computing and Communications (EDGE) Pub Date : 2023-06-06 DOI: 10.1109/EDGE60047.2023.00059

Mikolaj Lysakowski, Kamil Zywanowski, Adam Banaszczyk, Michał R. Nowicki, Piotr Skrzypczy'nski, S. Tadeja

引用次数: 2