{"title":"ParaSight: Enabling Privacy-preserving Sensing Data Sharing via Device-to-device Utterance-based Communication","authors":"Youngwook Do, Seong-eun Moon, Minsuk Chang","doi":"10.1145/3491101.3519757","DOIUrl":null,"url":null,"abstract":"Privacy-invasive sensors such as cameras and microphones in smart devices (e.g., Facebook Portal, Google Nest Hub Max, Amazon Echo Show) are now ubiquitous in a user’s private setting, which raises users’ privacy concerns of always listening and monitoring. To address such privacy concerns, we developed ParaSight, a smart speaker add-on device that communicates to users sensing data transfer. ParaSight transmits the information yet speaks out loud what is being transmitted to a smart speaker connected to a server via utterances by leveraging the smart speaker’s ability to understand human languages. Communicating sensing data as utterances brings two benefits: (i) a user can hear and understand what data, and when, are being transferred as utterances are human-understandable; (ii) raw data are processed locally and only filtered signals can be uploaded to a server. ParaSight, for example, can receive and locally process raw data of a user’s audio and video data (e.g., snoring sound, workout video), and only transmit the filtered data to a server. We demonstrate two work-in-progress applications—snoring detection and home training applications—to show ParaSight’s use cases.","PeriodicalId":123301,"journal":{"name":"CHI Conference on Human Factors in Computing Systems Extended Abstracts","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CHI Conference on Human Factors in Computing Systems Extended Abstracts","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3491101.3519757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Privacy-invasive sensors such as cameras and microphones in smart devices (e.g., Facebook Portal, Google Nest Hub Max, Amazon Echo Show) are now ubiquitous in a user’s private setting, which raises users’ privacy concerns of always listening and monitoring. To address such privacy concerns, we developed ParaSight, a smart speaker add-on device that communicates to users sensing data transfer. ParaSight transmits the information yet speaks out loud what is being transmitted to a smart speaker connected to a server via utterances by leveraging the smart speaker’s ability to understand human languages. Communicating sensing data as utterances brings two benefits: (i) a user can hear and understand what data, and when, are being transferred as utterances are human-understandable; (ii) raw data are processed locally and only filtered signals can be uploaded to a server. ParaSight, for example, can receive and locally process raw data of a user’s audio and video data (e.g., snoring sound, workout video), and only transmit the filtered data to a server. We demonstrate two work-in-progress applications—snoring detection and home training applications—to show ParaSight’s use cases.