Moysis Symeonides, Demetris Trihinas, G. Pallis, M. Dikaiakos
{"title":"Demo: Emulating 5G-Ready Mobile IoT Services","authors":"Moysis Symeonides, Demetris Trihinas, G. Pallis, M. Dikaiakos","doi":"10.1109/iotdi54339.2022.00026","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00026","url":null,"abstract":"The majority of IoT devices disseminate harvested data through the internet for analysis by cloud services. However, emerging applications, such as autonomous vehicle navigation, are impacted by the Round-Trip-Time between the IoTs and cloud. 5G networks and edge computing promise shorter RTTs by bringing compute and network resources closer to IoT. Network slicing is a key enabler for 5G networks, dividing a physical network among a variety of services under their individual needs. However, the design of a network slice impacts the performance of the mobile IoT applications with owners puzzled among the numerous slice configurations and options. For instance, the placement of network access points and available compute nodes, the wireless protocols, and the midhaul and backhaul QoS are crucial factors impacting service performance with the mobility of entities constituting this issue even more daunting.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116244486","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}
{"title":"Poster Abstract: Explainable Sensor Data-Driven Anomaly Detection in Internet of Things Systems","authors":"Moaz Tajammal Hussain, Charith Perera","doi":"10.1109/iotdi54339.2022.00021","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00021","url":null,"abstract":"Deep learning or black-box models are widely used for anomaly detection in Internet of Things (IoT) data streams. We propose a technique to explain the output of a deep learning model used to detect anomalies in an IoT based industrial process. The proposed technique employs dual surrogate models to deliver black box model explanation. We have also developed an interactive dashboard to give further insights into the detected anomaly. The dashboard integrates our proposed deep learning explanation technique with historical logs to explain the detected anomaly for personas with different backgrounds.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128060731","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}
{"title":"Demo Abstract: PARROT: Privacy by Design Tool for Internet of Things","authors":"Nada Alhirabi, O. Rana, Charith Perera","doi":"10.1109/iotdi54339.2022.00023","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00023","url":null,"abstract":"The design process for applications that make use of Internet of Things (IoT) can be more complex than for desktop, mobile or web-based platforms. IoT applications typically collect and analyse personal data categorised as sensitive. These data may be subject to a higher degree of protection under data privacy laws. We present PARROT (PrivAcy by design tool foR inteRnet Of Things) – an interactive IoT application design tool for privacy-aware IoT applications. PARROT enables developers to consider privacy compliance during the design process and provides real-time feedback on potential privacy concerns that may need to be considered. From a privacy compliance perspective, PARROT incorporates privacy-specific design features into the IoT application from the beginning rather than retrospectively.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131098004","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}
{"title":"Hardware based identification for Intelligent Electronic Devices","authors":"Girish Vaidya, T. Prabhakar","doi":"10.1109/iotdi54339.2022.00018","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00018","url":null,"abstract":"Modern power grid infrastructure utilises Intelligent Electronic Devices (IEDs) for sensing and control of the grid. IEDs continuously sense power related parameters through a multi-channel simultaneous sampling Analog to Digital Converter (ADC). The dependence on IEDs for the reliable operation of the grid mandates that these devices are irrefutably identified. In this work, we generate an IED identifier based on its innate properties. Our proposed approach is in-situ, non-invasive and does not require any special hardware. Through our evaluation over six weeks, we demonstrate the Repeatability, Uniqueness, Randomness and Real-time property of the identifier. Our evaluation results show that the repeatability of identifiers is 99.5% and together they could uniquely identify a few million devices. Furthermore, we also demonstrate a method to fingerprint Electro-magnetic relays (EMR), another essential component used inside IEDs. Defective EMRs, along with replacement from a different family can be identified.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126538341","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}
{"title":"RAScatter: Achieving Energy-Efficient Backscatter Readers via AI-Assisted Power Adaptation","authors":"Kai Huang, Ruirong Chen, Wei Gao","doi":"10.1109/iotdi54339.2022.00016","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00016","url":null,"abstract":"Backscatter communication reduces the batteryless device's power consumption at the cost of extra RF energy transmitted from backscatter readers. Such extra cost results in extremely low energy efficiency at readers, but is ignored by existing systems that always use the highest transmit RF power for maximum goodput. Instead, we envision that the maximum goodput is unnecessary in many practical scenarios, allowing adaptation of transmit RF power to the required goodput. In this paper, we present RAScatter, a new backscatter system of precise, adaptive and lightweight power adaptation towards energy-efficient backscatter readers. RAScatter learns the entangled correlation between backscatter channel conditions, transmit RF power and goodput by designing a modular neural network, which decomposes the complex learning task into multiple related but simplified subtasks. This decomposition avoids redundancy in neural networks and eliminates any confusion in training due to insufficient training data in low-speed backscatter systems. Experiment results over commodity batteryless tags show that RAScatter improves the energy efficiency at backscatter readers by 3.5× and reduces the readers' power consumption in backscatter communication by up to 80%.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127589934","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}
{"title":"Welcome from the IoTDI 2022 Organizers","authors":"","doi":"10.1109/iotdi54339.2022.00006","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00006","url":null,"abstract":"","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133354491","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}
Ziwei Liu, Linzhong Xu, Feng Lin, Zhangsen Wang, Kui Ren
{"title":"CTJammer: A Cross-Technology Reactive Jammer towards Unlicensed LTE","authors":"Ziwei Liu, Linzhong Xu, Feng Lin, Zhangsen Wang, Kui Ren","doi":"10.1109/iotdi54339.2022.00013","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00013","url":null,"abstract":"Unlicensed LTE extends LTE into the unlicensed spectrum to relieve the burden of the rapidly growing mobile data traffic demand. The sharing usage of the unlicensed spectrum by unlicensed LTE and WiFi has drawn great attention in academia and industry. Previous work mainly focuses on the coexistence of those different technologies with the assumption that all the devices are benign. But we find that the usage of the unlicensed spectrum by unlicensed LTE may bring about more new problems if some devices are compromised. This paper first reveals that a low-cost COTS WiFi device can be used to attack unlicensed LTE devices, which is a cross-technology attack. The attacker can use the commercial WiFi device to conduct a smart and stealthy reactive jamming attack towards unlicensed LTE devices and block their wireless communication. To turn a commercial WiFi device into a cross-technology reactive jammer, we flexibly leverage WiFi chipsets to detect unlicensed LTE signals and combine multiple considerations to satisfy the real-time demand of reactive jamming. We implement a prototype jammer with a low-cost WiFi router, i.e., CTJammer, and our extensive experiments show that CTJammer can greatly jam the traffic of unlicensed LTE.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122782816","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}
{"title":"Poster Abstract: Feasibility on Detecting Door Slamming towards Monitoring Early Signs of Domestic Violence","authors":"O. Morgan, Hakan Kayan, Charith Perera","doi":"10.1109/iotdi54339.2022.00022","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00022","url":null,"abstract":"By using low-cost microcontrollers and TinyML, we investigate the feasibility of detecting potential early warning signs of domestic violence and other anti-social behaviors within the home. We created a machine learning model to determine if a door was closed aggressively by analyzing audio data and feeding this into a convolutional neural network to classify the sample. Under test conditions, with no background noise, an accuracy of 88.89% was achieved, declining to 87.50% when assorted background noises were mixed in at a relative volume of 0.5 times that of the sample. The model is then deployed on an Arduino Nano BLE 33 Sense attached to the door, and only begins sampling once an acceleration greater than a predefined threshold acceleration is detected. The predictions made by the model can then be sent via BLE to another device, such as a smartphone of Raspberry Pi.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128566690","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}
Sezana Fahmida, V. P. Modekurthy, Dali Ismail, Aakriti Jain, Abusayeed Saifullah
{"title":"Real-Time Communication over LoRa Networks","authors":"Sezana Fahmida, V. P. Modekurthy, Dali Ismail, Aakriti Jain, Abusayeed Saifullah","doi":"10.1109/iotdi54339.2022.00019","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00019","url":null,"abstract":"Today, industrial Internet of Things (IIoT) are emerging in large-scale and wide-area applications (e.g., oil-field management). Traditional wireless solutions for industrial automation depend on short-range wireless technologies (WirelessHART, ISA100.11a), posing a big challenge to support the scale of today's IIoT. To address this limitation, we propose to adopt LoRa, a prominent low-power wide-area network technology, for industrial automation. Adopting LoRa for industrial automation poses some unique challenges. The fundamental building blocks of any industrial automation system are feedback control loops that largely rely on real-time communication. LoRa usually adopts a simple protocol based on ALOHA with no collision avoidance to minimize energy consumption which is less suitable for real-time communication. Existing real-time protocols for short-range technologies cannot be applied to a LoRa network due to its unique characteristics such as asymmetry between downlink and the uplink spectrum, predefined modes (class) of operation, and concurrent reception through orthogonal spreading factors. In this paper, we address these challenges and propose RTPL- a Real-Time communication Protocol for LoRa networks. RTPL is a low-overhead and conflict-free communication protocol allowing autonomous real-time communication of low-energy devices and exploits LoRa's capability of parallel communication. We implement our approach on LoRa devices and evaluate through both physical experiments and large scale simulations. All results show that RTPL achieves on average 75% improvement in real-time performance without sacrificing throughput or energy compared to traditional LoRa.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127035033","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}
Jie Hua, Haoxiang Yu, Sangsu Lee, H. Adal, Colin Milhaupt, G. Roman, C. Julien
{"title":"CoPI: Enabling Probabilistic Conflict Prediction in Smart Space Through Context-awareness","authors":"Jie Hua, Haoxiang Yu, Sangsu Lee, H. Adal, Colin Milhaupt, G. Roman, C. Julien","doi":"10.1109/iotdi54339.2022.00012","DOIUrl":"https://doi.org/10.1109/iotdi54339.2022.00012","url":null,"abstract":"In a smart space influenced by multiple parties, conflicts can arise when competing users try to control the same devices in different ways. Such conflicts usually require user negotiation to resolve and thus lower people's satisfaction and trust in the smart system. Finding a conflict is the first step to resolving it, and the timing when a conflict is identified impacts the options for resolution. Most existing approaches identify conflicts only at the time they occur, which offers little help to the users in resolving the conflicts, especially without them having to compromise. A better solution is to predict potential conflicts in advance so that the users can coordinate themselves to avoid conflict situations beforehand. In this paper, we propose a novel context-aware conflict prediction framework that addresses the research gaps identified in existing literature. We mine habit patterns from the user's previous interactions with smart devices in the various environments they occupy. These habits serve as inputs to our conflict prediction algorithm which takes the habits of pairs of users and outputs context situations in which those users have the potential to conflict. To support eventual flexible resolution, we use explicit models of the uncertainties of users' behaviors to associate each potential conflict scenario with a probability of that conflict occurring for these particular users. We evaluate our framework on real-world datasets to demonstrate the effectiveness of the proposed approach.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134538768","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}