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Sen. Netw."],"published-print":{"date-parts":[[2023,8,31]]},"abstract":"<jats:p>\n            Authentication mechanisms deployed on access control systems undertake the responsibility of judging user identity to prevent unauthorized individuals from illegally approaching. In this article, we propose\n            <jats:bold>\n              <jats:italic>LIPAuth<\/jats:italic>\n            <\/jats:bold>\n            leveraging hand-dependent\n            <jats:bold>L<\/jats:bold>\n            ight\n            <jats:bold>I<\/jats:bold>\n            ntensity\n            <jats:bold>P<\/jats:bold>\n            attern to\n            <jats:bold>Auth<\/jats:bold>\n            enticate users. To be specific, lights released by a screen, are blocked and reflected by one hand above it; in this propagation process, hands exhibit user-specific ability in driving light absorption and attenuation due to owning unique structures, thereby outputting discriminative intensity patterns representing user identity. To implement\n            <jats:italic>LIPAuth<\/jats:italic>\n            , we first study the impact of screen contents on light intensity patterns, also explore the possibility of embedding hand structure biometrics into these patterns. We then design a customized dynamic stimulus-response mechanism for\n            <jats:italic>LIPAuth<\/jats:italic>\n            and make it resilient to the risks of potential registration profile leakage. Subsequently, we construct a joint pipeline consisting of signal processing and a learning-based generative adversarial network to overcome interference from variable user behaviors. More importantly,\n            <jats:italic>LIPAuth<\/jats:italic>\n            just utilizes common sensors to capture light signals, hence achieving low cost. We finally conduct extensive experiments in three scenarios to evaluate the authentication performance of\n            <jats:italic>LIPAuth<\/jats:italic>\n            prototype.\n          <\/jats:p>","DOI":"10.1145\/3572909","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T06:42:56Z","timestamp":1671172976000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["<i>LIPAuth<\/i>\n            : Hand-dependent Light Intensity Patterns for Resilient User Authentication"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0957-8576","authenticated-orcid":false,"given":"Hangcheng","family":"Cao","sequence":"first","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8268-2951","authenticated-orcid":false,"given":"Daibo","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7372-2539","authenticated-orcid":false,"given":"Hongbo","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, China"}]},{"given":"Ruize","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3215-2696","authenticated-orcid":false,"given":"Zhe","family":"Chen","sequence":"additional","affiliation":[{"name":"China-Singapore International Joint Research Institute, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5396-4554","authenticated-orcid":false,"given":"Jie","family":"Xiong","sequence":"additional","affiliation":[{"name":"College of Information and Computer Sciences, University of Massachusetts Amherst, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,5,8]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"2194","volume-title":"IEEE EMBS","author":"Jacobson A. 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