2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)最新文献

筛选

英文中文

Digital Contact Tracing Using IP Colocation 使用IP主机的数字接触跟踪

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2020-06-16 DOI: 10.1109/IoTaIS53735.2021.9628446

Matthew Malloy, Aaron Cahn, Jonathan Koller

{"title":"Digital Contact Tracing Using IP Colocation","authors":"Matthew Malloy, Aaron Cahn, Jonathan Koller","doi":"10.1109/IoTaIS53735.2021.9628446","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628446","url":null,"abstract":"The spread of an infectious disease through a population can be modeled using a network or a graph. In digital advertising, internet device graphs are graph data sets that organize identifiers produced by mobile phones, PCs, TVs, and tablets as they access media on the internet. Characterized by immense scale, they have become ubiquitous as they enable targeted advertising, content customization and tracking. This paper posits that internet device graphs, in particular those based on IP colocation, can provide utility for contact tracing and predicting and modeling the spread of infectious disease. Starting the week of March 16th, 2020, in the United States, many individuals began to ‘shelter-in-place’ as schools and workplaces across the nation closed because of the COVID-19 pandemic. This paper quantifies the effect of the shelter-in-place orders on a large scale internet device graph with more than a billion nodes by studying the graph before and after orders went into effect. The structure of the graph suggests behavior least conducive to transmission of infection occurred in the US between April 12th and 19th, 2020. This paper also discusses the utility of device graphs for i) contact tracing, ii) prediction of ‘hot spots’, iii) simulation of infectious disease spread, and iv) delivery of advertisement-based warnings to potentially exposed individuals. The paper also posits an overarching question: can systems and datasets amassed by entities in the digital ad ecosystem aid in the fight against COVID-19?","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116425788","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

首页上一页