TY - GEN
T1 - WiLCA
T2 - 19th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2022
AU - Lin, Chi
AU - Ji, Chuanying
AU - Ma, Fenglong
AU - Wang, Lei
AU - Zhong, Wei
AU - Wu, Guowei
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Human authentication is critical to protect personal and property security. Existing contactless authentication methods face some drawbacks, such as requiring large data size and low accuracy in cross-domain recognition, which hinders widespread popularization in practical applications. In this paper, we design and implement WiLCA, a WiFi-based lightweight contactless authentication system. First, we devise a Channel State Information (CSI) stream selection scheme to extract human movement features and reduce the sample size in the recognition process. Then, an AGO model is proposed, in which a Siamese Neural Network (SNN) framework with a cross-entropy module is used to guarantee accurate human authentication with limited data, and a lightweight GhostNet accelerates authentication with cheap operations. At last, extensive experiments are conducted to demonstrate the advantages of WiLCA, revealing that compared with state-of-the-art methods, WiLCA can reduce the data size by at least 2.5 x and achieve accurate authentication with an accuracy of over 98%.
AB - Human authentication is critical to protect personal and property security. Existing contactless authentication methods face some drawbacks, such as requiring large data size and low accuracy in cross-domain recognition, which hinders widespread popularization in practical applications. In this paper, we design and implement WiLCA, a WiFi-based lightweight contactless authentication system. First, we devise a Channel State Information (CSI) stream selection scheme to extract human movement features and reduce the sample size in the recognition process. Then, an AGO model is proposed, in which a Siamese Neural Network (SNN) framework with a cross-entropy module is used to guarantee accurate human authentication with limited data, and a lightweight GhostNet accelerates authentication with cheap operations. At last, extensive experiments are conducted to demonstrate the advantages of WiLCA, revealing that compared with state-of-the-art methods, WiLCA can reduce the data size by at least 2.5 x and achieve accurate authentication with an accuracy of over 98%.
UR - http://www.scopus.com/inward/record.url?scp=85141196168&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141196168&partnerID=8YFLogxK
U2 - 10.1109/SECON55815.2022.9918594
DO - 10.1109/SECON55815.2022.9918594
M3 - Conference contribution
AN - SCOPUS:85141196168
T3 - Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
SP - 316
EP - 324
BT - 2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2022
PB - IEEE Computer Society
Y2 - 20 September 2022 through 23 September 2022
ER -