M. Bispham, S. Sattar, Clara Zard, Xavier Ferrer-Aran, Jide S. Edu, Guillermo Suarez-Tangil, J. Such
{"title":"第三方语音应用中的错误信息","authors":"M. Bispham, S. Sattar, Clara Zard, Xavier Ferrer-Aran, Jide S. Edu, Guillermo Suarez-Tangil, J. Such","doi":"10.1145/3571884.3604307","DOIUrl":null,"url":null,"abstract":"This paper investigates the potential for spreading misinformation via third-party voice applications in voice assistant ecosystems such as Amazon Alexa and Google Assistant. Our work fills a gap in prior work on privacy issues associated with third-party voice applications, looking at security issues related to outputs from such applications rather than compromises to privacy from user inputs. We define misinformation in the context of third-party voice applications and implement an infrastructure for testing third-party voice applications using automated natural language interaction. Using our infrastructure, we identify — for the first time — several instances of misinformation in third-party voice applications currently available on the Google Assistant and Amazon Alexa platforms. We then discuss the implications of our work for developing measures to pre-empt the threat of misinformation and other types of harmful content in third-party voice assistants becoming more significant in the future.","PeriodicalId":127379,"journal":{"name":"Proceedings of the 5th International Conference on Conversational User Interfaces","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Misinformation in Third-party Voice Applications\",\"authors\":\"M. Bispham, S. Sattar, Clara Zard, Xavier Ferrer-Aran, Jide S. Edu, Guillermo Suarez-Tangil, J. Such\",\"doi\":\"10.1145/3571884.3604307\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the potential for spreading misinformation via third-party voice applications in voice assistant ecosystems such as Amazon Alexa and Google Assistant. Our work fills a gap in prior work on privacy issues associated with third-party voice applications, looking at security issues related to outputs from such applications rather than compromises to privacy from user inputs. We define misinformation in the context of third-party voice applications and implement an infrastructure for testing third-party voice applications using automated natural language interaction. Using our infrastructure, we identify — for the first time — several instances of misinformation in third-party voice applications currently available on the Google Assistant and Amazon Alexa platforms. We then discuss the implications of our work for developing measures to pre-empt the threat of misinformation and other types of harmful content in third-party voice assistants becoming more significant in the future.\",\"PeriodicalId\":127379,\"journal\":{\"name\":\"Proceedings of the 5th International Conference on Conversational User Interfaces\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 5th International Conference on Conversational User Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3571884.3604307\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Conference on Conversational User Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3571884.3604307","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper investigates the potential for spreading misinformation via third-party voice applications in voice assistant ecosystems such as Amazon Alexa and Google Assistant. Our work fills a gap in prior work on privacy issues associated with third-party voice applications, looking at security issues related to outputs from such applications rather than compromises to privacy from user inputs. We define misinformation in the context of third-party voice applications and implement an infrastructure for testing third-party voice applications using automated natural language interaction. Using our infrastructure, we identify — for the first time — several instances of misinformation in third-party voice applications currently available on the Google Assistant and Amazon Alexa platforms. We then discuss the implications of our work for developing measures to pre-empt the threat of misinformation and other types of harmful content in third-party voice assistants becoming more significant in the future.