{"title":"WearLock:使用智能手表通过声学解锁手机","authors":"Shanhe Yi, Zhengrui Qin, Nancy Carter, Qun A. Li","doi":"10.1109/ICDCS.2017.183","DOIUrl":null,"url":null,"abstract":"Smartphone lock screens are implemented to reduce the risk of data loss or compromise given the fact that increasing amount of person data are accessible on smartphones nowadays. Unfortunately, many smartphone users abandon lock screens due to the inconvenience of unlocking their phones many times a day. With the wide adoption of wearables, token-based approaches have gained popularity in simplifying unlocking and retaining security at the same time. To this end, we propose to take advantage of the smartwatch for easy smartphone unlocking. In this paper, we have designed WearLock, a system that uses acoustic tones as tokens to automate the unlocking securely. We build a sub-channel selection and an adaptive modulation in the acoustic modem to maximize unlocking success rate against ambient noise only when those two devices are nearby. We leverage the motion sensor on the smartwatch to reduce the unlock frequency. We offload smartwatch tasks to the smartphone to speed up computation and save energy. We have implemented the WearLock prototype and conducted extensive evaluations. Results achieved a low average bit error rate (BER) as 8% in various experiments. Compared to traditional manual personal identification numbers (PINs) entry, WearLock achieves at least 18% unlock speedup without any manual effort.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"13 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"WearLock: Unlocking Your Phone via Acoustics Using Smartwatch\",\"authors\":\"Shanhe Yi, Zhengrui Qin, Nancy Carter, Qun A. Li\",\"doi\":\"10.1109/ICDCS.2017.183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smartphone lock screens are implemented to reduce the risk of data loss or compromise given the fact that increasing amount of person data are accessible on smartphones nowadays. Unfortunately, many smartphone users abandon lock screens due to the inconvenience of unlocking their phones many times a day. With the wide adoption of wearables, token-based approaches have gained popularity in simplifying unlocking and retaining security at the same time. To this end, we propose to take advantage of the smartwatch for easy smartphone unlocking. In this paper, we have designed WearLock, a system that uses acoustic tones as tokens to automate the unlocking securely. We build a sub-channel selection and an adaptive modulation in the acoustic modem to maximize unlocking success rate against ambient noise only when those two devices are nearby. We leverage the motion sensor on the smartwatch to reduce the unlock frequency. We offload smartwatch tasks to the smartphone to speed up computation and save energy. We have implemented the WearLock prototype and conducted extensive evaluations. Results achieved a low average bit error rate (BER) as 8% in various experiments. Compared to traditional manual personal identification numbers (PINs) entry, WearLock achieves at least 18% unlock speedup without any manual effort.\",\"PeriodicalId\":127689,\"journal\":{\"name\":\"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)\",\"volume\":\"13 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCS.2017.183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2017.183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
WearLock: Unlocking Your Phone via Acoustics Using Smartwatch
Smartphone lock screens are implemented to reduce the risk of data loss or compromise given the fact that increasing amount of person data are accessible on smartphones nowadays. Unfortunately, many smartphone users abandon lock screens due to the inconvenience of unlocking their phones many times a day. With the wide adoption of wearables, token-based approaches have gained popularity in simplifying unlocking and retaining security at the same time. To this end, we propose to take advantage of the smartwatch for easy smartphone unlocking. In this paper, we have designed WearLock, a system that uses acoustic tones as tokens to automate the unlocking securely. We build a sub-channel selection and an adaptive modulation in the acoustic modem to maximize unlocking success rate against ambient noise only when those two devices are nearby. We leverage the motion sensor on the smartwatch to reduce the unlock frequency. We offload smartwatch tasks to the smartphone to speed up computation and save energy. We have implemented the WearLock prototype and conducted extensive evaluations. Results achieved a low average bit error rate (BER) as 8% in various experiments. Compared to traditional manual personal identification numbers (PINs) entry, WearLock achieves at least 18% unlock speedup without any manual effort.