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Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation最新文献

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IoT System Vulnerability Analysis and Network Hardening with Shortest Attack Trace in a Weighted Attack Graph 加权攻击图中攻击轨迹最短的物联网系统漏洞分析与网络加固
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582326
Yinxin Wan, Xuanli Lin, Abdulhakim Sabur, A. Chang, Kuai Xu, G. Xue
{"title":"IoT System Vulnerability Analysis and Network Hardening with Shortest Attack Trace in a Weighted Attack Graph","authors":"Yinxin Wan, Xuanli Lin, Abdulhakim Sabur, A. Chang, Kuai Xu, G. Xue","doi":"10.1145/3576842.3582326","DOIUrl":"https://doi.org/10.1145/3576842.3582326","url":null,"abstract":"In recent years, Internet of Things (IoT) devices have been extensively deployed in edge networks, including smart homes and offices. Despite the exciting opportunities afforded by the advancements in the IoT, it also introduces new attack vectors and vulnerabilities in the system. Existing studies have shown that the attack graph is an effective model for performing system-level analysis of IoT security. In this paper, we study IoT system vulnerability analysis and network hardening. We first extend the concept of attack graph to weighted attack graph and design a novel algorithm for computing a shortest attack trace in a weighted attack graph. We then formulate the network hardening problem. We prove that this problem is NP-hard, and then design an exact algorithm and a heuristic algorithm to solve it. Extensive experiments on 9 synthetic IoT systems and 2 real-world smart home IoT testbeds demonstrate that our shortest attack trace algorithm is robust and fast, and our heuristic network hardening algorithm is efficient in producing near optimal results compared to the exact algorithm.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123556261","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
MOHAWK: Mobility and Heterogeneity-Aware Dynamic Community Selection for Hierarchical Federated Learning MOHAWK:层次联邦学习的移动性和异构感知动态社区选择
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582378
Allen-Jasmin Farcas, Myungjin Lee, R. Kompella, Hugo Latapie, G. de Veciana, R. Marculescu
{"title":"MOHAWK: Mobility and Heterogeneity-Aware Dynamic Community Selection for Hierarchical Federated Learning","authors":"Allen-Jasmin Farcas, Myungjin Lee, R. Kompella, Hugo Latapie, G. de Veciana, R. Marculescu","doi":"10.1145/3576842.3582378","DOIUrl":"https://doi.org/10.1145/3576842.3582378","url":null,"abstract":"The recent developments in Federated Learning (FL) focus on optimizing the learning process for data, hardware, and model heterogeneity. However, most approaches assume all devices are stationary, charging, and always connected to the Wi-Fi when training on local data. We argue that when real devices move around, the FL process is negatively impacted and the device energy spent for communication is increased. To mitigate such effects, we propose a dynamic community selection algorithm which improves the communication energy efficiency and two new aggregation strategies that boost the learning performance in Hierarchical FL (HFL). For real mobility traces, we show that compared to state-of-the-art HFL solutions, our approach is scalable, achieves better accuracy on multiple datasets, converges up to 3.88 × faster, and is significantly more energy efficient for both IID and non-IID scenarios.1","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129898393","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
Poster Abstract: An IoT Mesh Network for a Smart Refrigeration Monitoring System 摘要:用于智能制冷监控系统的物联网网状网络
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589174
Kyle Morman, David Dexter, Aaron M. Costin, J. Mcnair
{"title":"Poster Abstract: An IoT Mesh Network for a Smart Refrigeration Monitoring System","authors":"Kyle Morman, David Dexter, Aaron M. Costin, J. Mcnair","doi":"10.1145/3576842.3589174","DOIUrl":"https://doi.org/10.1145/3576842.3589174","url":null,"abstract":"A major challenge of the next decade is food scarcity and food waste. Smart automation refrigeration systems have emerged, but the devices, methods and outcomes vary significantly. In this work, a smart refrigerator IoT infrastructure is built to investigate system reliability and consistency across heterogeneous data collection devices. The system uses IP-based communications, wireless sensor data, cloud storage and processing, controller actuation, and an mobile app. A temperature report case study provides preliminary results.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126221334","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
Practical Cryptographic Forensic Tools for Lightweight Internet of Things and Cold Storage Systems 轻量级物联网和冷存储系统的实用加密取证工具
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3582376
Saif E. Nouma, A. Yavuz
{"title":"Practical Cryptographic Forensic Tools for Lightweight Internet of Things and Cold Storage Systems","authors":"Saif E. Nouma, A. Yavuz","doi":"10.1145/3576842.3582376","DOIUrl":"https://doi.org/10.1145/3576842.3582376","url":null,"abstract":"Internet of Things (IoT) and Storage-as-a-Service (STaaS) continuum permit cost-effective maintenance of security-sensitive information collected by IoT devices over cloud systems. It is necessary to guarantee the security of sensitive data in IoT-STaaS applications. Especially, log entries trace critical events in computer systems and play a vital role in the trustworthiness of IoT-STaaS. An ideal log protection tool must be scalable and lightweight for vast quantities of resource-limited IoT devices while permitting efficient and public verification at STaaS. However, the existing cryptographic logging schemes either incur significant computation/signature overhead to the logger or extreme storage and verification costs to the cloud. There is a critical need for a cryptographic forensic log tool that respects the efficiency requirements of the IoT-STaaS continuum. In this paper, we created novel digital signatures for logs called Optimal Signatures for secure Logging (), which are the first (to the best of our knowledge) to offer both small-constant signature and public key sizes with near-optimal signing and batch verification via various granularities. We introduce new design features such as one-time randomness management, flexible aggregation along with various optimizations to attain these seemingly conflicting properties simultaneously. Our experiments show that offers 50 × faster verification (for 235 entries) than the most compact alternative with equal signature sizes, while also being several magnitudes of more compact than its most logger efficient counterparts. These properties make an ideal choice for the IoT-STaaS, wherein lightweight logging and efficient batch verification of massive-size logs are vital for the IoT edge and cold storage servers, respectively.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116124378","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: 1
Optimizing Neural Network Efficiency with Hybrid Magnitude-Based and Node Pruning for Energy-efficient Computing in IoT 基于混合量和节点修剪的物联网节能计算神经网络效率优化
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589175
M. Helal Uddin, S. Baidya
{"title":"Optimizing Neural Network Efficiency with Hybrid Magnitude-Based and Node Pruning for Energy-efficient Computing in IoT","authors":"M. Helal Uddin, S. Baidya","doi":"10.1145/3576842.3589175","DOIUrl":"https://doi.org/10.1145/3576842.3589175","url":null,"abstract":"The Deep Neural Networks (DNN) are computationally intensive in terms of processing, energy and memory which becomes a bottleneck to run these models on edge devices. This research study provides a technique for pruning the neural networks to enhance the performance of deep learning models in IoT devices. The proposed method combines magnitude-based pruning, which merges insignificant weights based on their magnitude, with node pruning, which eliminates insignificant nodes based on their contribution to the network. The hybrid pruning technique is designed to be energy-efficient, reducing the computational overhead of deep learning models while maintaining their accuracy. The experimental results demonstrate that the proposed method can achieve significant reductions in model size and energy consumption with minimal loss in accuracy. The technique has the potential to enable the deployment of deep learning models on resource constrained IoT devices.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126322323","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
Poster Abstract: Obstruction-Free Physiological Motion Sensing in NextG Networks with Intelligent Reflective Surfaces 摘要:具有智能反射表面的NextG网络中的无障碍物生理运动传感
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589171
D. Landika, Saige Dacuycuy, Yao Zheng
{"title":"Poster Abstract: Obstruction-Free Physiological Motion Sensing in NextG Networks with Intelligent Reflective Surfaces","authors":"D. Landika, Saige Dacuycuy, Yao Zheng","doi":"10.1145/3576842.3589171","DOIUrl":"https://doi.org/10.1145/3576842.3589171","url":null,"abstract":"This poster abstract shows the possibilities of incorporating an Intelligent Reflective Surface (IRS) that operates at the 3.5 GHz band in order to enhance signal coverage and perform obstruction-free physiological motion sensing. At an operating frequency of 3.5 GHz, the IRS redirects an incoming signal at normal incidence to 34°. A testbed is developed that allows us to test the quality of periodic motion (i.e. simulate breathing). The transmit horn is pointed at a metallic target that is oscillating at 0.2 Hz, where the target scatters the transmitted signal. The scattered signal will reach the IRS, which then redirects the signal to the receive horn. The setup was tested for three possible cases, with an IRS, a copper plate, and an absorber as the target. The merits of implementing an IRS in physiological sensing are discussed and evaluated.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117062006","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
Poster Abstract: O-RAN Signaling Optimizations for Improved IoT Handover Performance in 5G Networks 摘要:改进5G网络中物联网切换性能的O-RAN信令优化
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589165
Eduardo Lichtenfels Riccio, P. K. Mangipudi, J. Mcnair
{"title":"Poster Abstract: O-RAN Signaling Optimizations for Improved IoT Handover Performance in 5G Networks","authors":"Eduardo Lichtenfels Riccio, P. K. Mangipudi, J. Mcnair","doi":"10.1145/3576842.3589165","DOIUrl":"https://doi.org/10.1145/3576842.3589165","url":null,"abstract":"IoT systems require a wireless infrastructure that supports 5G devices, including handovers between heterogeneous and/or small cell radio access networks. These networks are subject to increased radio link failures and loss of IoT network function. 3GPP new radio (NR) applications include multihoming, i.e., simultaneously connecting devices, and handover, i.e., changing the point of access to the network. This work leverages the open radio access network (O-RAN) alliance, which specifies a new open architecture with intelligent controllers, to improve handover management. A new feedback-based time-to-trigger (TTT) handover mechanism is introduced. Improved throughput and reduced radio link failures over other techniques were achieved.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132802583","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: 2
Poster Abstract: Towards Distributed Machine Learning for Data Acquisition in Wireless Sensor Networks 摘要:面向无线传感器网络数据采集的分布式机器学习
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589158
Tayyaba Zainab, J. Karstens, O. Landsiedel
{"title":"Poster Abstract: Towards Distributed Machine Learning for Data Acquisition in Wireless Sensor Networks","authors":"Tayyaba Zainab, J. Karstens, O. Landsiedel","doi":"10.1145/3576842.3589158","DOIUrl":"https://doi.org/10.1145/3576842.3589158","url":null,"abstract":"Wireless sensor networks (WSNs) use low-cost sensors to monitor various environments, offering accurate and continuous surveillance. WSNs face a significant challenge in managing their limited energy resources due to communication overhead. To address this issue, we present a novel approach that leverages Neural Network (NN) models to predict data and reduce communication in WSNs. Our solution incorporates NN models on both the sensor and the cloud, enabling predictions to be made at the local level. The sensor sends data to the cloud only when the model is no longer able to predict accurately, cloud then fine-tunes the model based on the received data and sends updated weights of the NN to the sensor, reducing the need for communicating each sensed value to the cloud.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134051965","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
Demo Abstract: Collaborative Real-Time Scheduling (CRTS) Algorithm for AGV Transportation System within a CPS Architecture 摘要:基于CPS架构的AGV运输系统协同实时调度算法
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589177
Himansu Shaw, A. Cheng
{"title":"Demo Abstract: Collaborative Real-Time Scheduling (CRTS) Algorithm for AGV Transportation System within a CPS Architecture","authors":"Himansu Shaw, A. Cheng","doi":"10.1145/3576842.3589177","DOIUrl":"https://doi.org/10.1145/3576842.3589177","url":null,"abstract":"The use of Autonomous Guided Vehicles (AGVs) is important in smart factories to enhance manufacturing operations. However, current AGV scheduling algorithms are inadequate and not connected to real-time data on manufacturing needs, leading to underutilized AGVs and missed delivery deadlines. The lack of algorithms that ensure timely delivery of materials results in idle time of AGVs and material shortages. We present a collaborative real-time scheduling (CRTS) algorithm for AGVs in smart factories. The algorithm not only ensures timely delivery of materials to processing units but also predicts the minimum number of AGVs required. The algorithm is designed to operate within a cyber-physical system architecture, where AGVs and processing units exchange data via a wireless network. The simulation results on the Node-Red platform show that the algorithm is efficient and adequate to meet real-time delivery requirements, with an average AGV utilization of over 92%.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132084416","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
Demo Abstract: A Hardware Prototype Targeting Federated Learning with User Mobility and Device Heterogeneity 摘要:针对用户移动性和设备异构的联邦学习的硬件原型
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation Pub Date : 2023-05-09 DOI: 10.1145/3576842.3589160
Allen-Jasmin Farcas, R. Marculescu
{"title":"Demo Abstract: A Hardware Prototype Targeting Federated Learning with User Mobility and Device Heterogeneity","authors":"Allen-Jasmin Farcas, R. Marculescu","doi":"10.1145/3576842.3589160","DOIUrl":"https://doi.org/10.1145/3576842.3589160","url":null,"abstract":"This paper presents a new hardware prototype to explore how centralized and hierarchical federated learning systems are impacted by real-world devices distribution, availability, and heterogeneity. Our results show considerable learning performance degradation and wasted energy during training when users mobility is accounted for. Hence, we provide a prototype that can be used as a design exploration tool to better design, calibrate and evaluate FL systems for real-world deployment.","PeriodicalId":266438,"journal":{"name":"Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363429","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
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