{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T18:06:29Z","timestamp":1770833189370,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T00:00:00Z","timestamp":1669766400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China NSFC Grant","award":["62172286"],"award-info":[{"award-number":["62172286"]}]},{"name":"China NSFC Grant","award":["2022A1515011509"],"award-info":[{"award-number":["2022A1515011509"]}]},{"name":"Guangdong NSF Grant","award":["62172286"],"award-info":[{"award-number":["62172286"]}]},{"name":"Guangdong NSF Grant","award":["2022A1515011509"],"award-info":[{"award-number":["2022A1515011509"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Handwritten signatures are widely used for identity authorization. However, verifying handwritten signatures is cumbersome in practice due to the dependency on extra drawing tools such as a digitizer, and because the false acceptance of a forged signature can cause damage to property. Therefore, exploring a way to balance the security and user experiment of handwritten signatures is critical. In this paper, we propose a handheld signature verification scheme called SilentSign, which leverages acoustic sensors (i.e., microphone and speaker) in mobile devices. Compared to the previous online signature verification system, it provides handy and safe paper-based signature verification services. The prime notion is to utilize the acoustic signals that are bounced back via a pen tip to depict a user\u2019s signing pattern. We designed the signal modulation stratagem carefully to guarantee high performance, developed a distance measurement algorithm based on phase shift, and trained a verification model. In comparison with the traditional signature verification scheme, SilentSign allows users to sign more conveniently as well as invisibly. To evaluate SilentSign in various settings, we conducted comprehensive experiments with 35 participants. Our results reveal that SilentSign can attain 98.2% AUC and 1.25% EER. We note that a shorter conference version of this paper was presented in Percom (2019). Our initial conference paper did not finish the complete experiment. This manuscript has been revised and provided additional experiments to the conference proceedings; for example, by including System Robustness, Computational Overhead, etc.<\/jats:p>","DOI":"10.3390\/s22239343","type":"journal-article","created":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T03:03:41Z","timestamp":1669863821000},"page":"9343","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Acoustic Sensing Based on Online Handwritten Signature Verification"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4159-7478","authenticated-orcid":false,"given":"Mengqi","family":"Chen","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Yuehai Street, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Yuehai Street, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongpan","family":"Zou","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Yuehai Street, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaishun","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Yuehai Street, Shenzhen 518061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8665","DOI":"10.1007\/s00500-021-05717-1","article-title":"A wrapper metaheuristic framework for handwritten signature verification","volume":"25","author":"Hancer","year":"2021","journal-title":"Soft Comput."},{"key":"ref_2","unstructured":"Morgan, J. (2022, November 01). 2020 AFP Payments Fraud and Control Survey. Available online: https:\/\/dynamic.afponline.org\/paymentsfraud."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Saleem, M., and Kovari, B. (2020, January 24\u201326). Survey of Preprocessing Techniques and Classification Approaches in Online Signature Verification. Proceedings of the International Conference on Image Analysis and Recognition, Povoa de Varzim, Portugal.","DOI":"10.1007\/978-3-030-50347-5_23"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Adamski, M., and Saeed, K. (2008, January 26\u201328). Online signature classification and its verification system. Proceedings of the 2008 7th Computer Information Systems and Industrial Management Applications, Ostrava, Czech Republic.","DOI":"10.1109\/CISIM.2008.38"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1049\/iet-bmt.2016.0103","article-title":"Online signature verification using double-stage feature extraction modelled by dynamic feature stability experiment","volume":"6","author":"Yahyatabar","year":"2017","journal-title":"IET Biom."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Auddya, S., Singh, R.K., and Sundaram, S. (2020, January 8\u201310). Online Signature Verification using Time Warp Edit Distance based kernel. Proceedings of the 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), Dortmund, Germany.","DOI":"10.1109\/ICFHR2020.2020.00065"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1002\/jsid.100","article-title":"A review of technologies for sensing contact location on the surface of a display","volume":"20","author":"Walker","year":"2012","journal-title":"J. Soc. Inf. Disp."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1109\/TBIOM.2019.2912401","article-title":"Wearables-driven freeform handwriting authentication","volume":"1","author":"Matovu","year":"2019","journal-title":"IEEE Trans. Biom. Behav. Identity Sci."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Chen, M., Lin, J., Zou, Y., Ruby, R., and Wu, K. (2020, January 23\u201327). Silentsign: Device-free handwritten signature verification through acoustic sensing. Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom), Austin, TX, USA.","DOI":"10.1109\/PerCom45495.2020.9127372"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Padmajadevi, G., and Aprameya, K. (2016, January 3\u20135). A review of handwritten signature verification systems and methodologies. Proceedings of the 2016 International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT), Chennai, India.","DOI":"10.1109\/ICEEOT.2016.7755443"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Fierrez, J., and Ortega-Garcia, J. (2008). On-line signature verification. Handbook of Biometrics, Springer.","DOI":"10.1007\/978-0-387-71041-9_10"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Levy, A., Nassi, B., Elovici, Y., and Shmueli, E. (2018). Handwritten signature verification using wrist-worn devices. InProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, ACM.","DOI":"10.1145\/3264929"},{"key":"ref_13","unstructured":"Muramatsu, D., and Matsumoto, T. (2007, January 27\u201329). Effectiveness of pen pressure, azimuth, and altitude features for online signature verification. Proceedings of the International Conference on Biometrics, Seoul, Republic of Korea."},{"key":"ref_14","unstructured":"Gurrala, K.K. (2011). Online Signature Verification Techniques. [Ph.D. Thesis, National Institute of Technology Rourkela]."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Shao, Y., Yang, T., and Wang, H. (2020). AirSign: Smartphone Authentication by Signing in the Air. Sensors, 21.","DOI":"10.3390\/s21010104"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1145\/3351238","article-title":"ASSV: Handwritten signature verification using acoustic signals","volume":"Volume 3","author":"Ding","year":"2019","journal-title":"Proceedings of the ACM Interactive, Mobile, Wearable Ubiquitous Technologies"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Liu, J., Wang, C., Chen, Y., and Saxena, N. (November, January 30). VibWrite: Towards finger-input authentication on ubiquitous surfaces via physical vibration. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, Dallas, TX, USA.","DOI":"10.1145\/3133956.3133964"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhao, C.X., Wysocki, T., Agrafioti, F., and Hatzinakos, D. (2012, January 23\u201327). Securing handheld devices and fingerprint readers with ECG biometrics. Proceedings of the 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), Arlington, VA, USA.","DOI":"10.1109\/BTAS.2012.6374570"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Chauhan, J., Hu, Y., Seneviratne, S., Misra, A., Seneviratne, A., and Lee, Y. (2017, January 19\u201323). BreathPrint: Breathing acoustics-based user authentication. Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, Niagara Falls, NY, USA.","DOI":"10.1145\/3081333.3081355"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1145\/3264962","article-title":"BiLock: User authentication via dental occlusion biometrics","volume":"Volume 2","author":"Zou","year":"2018","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3411806","article-title":"SmileAuth: Using Dental Edge Biometrics for User Authentication on Smartphones","volume":"Volume 4","author":"Jiang","year":"2020","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"ref_22","unstructured":"Zhou, B., Lohokare, J., Gao, R., and Ye, F. (November, January 29). EchoPrint: Two-factor Authentication using Acoustics and Vision on Smartphones. Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, New Delhi, India."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2152","DOI":"10.1109\/JIOT.2019.2959203","article-title":"EchoFace: Acoustic sensor-based media attack detection for face authentication","volume":"7","author":"Chen","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1145\/3264950","article-title":"Unlock with your heart: Heartbeat-based authentication on commercial mobile phones","volume":"Volume 2","author":"Wang","year":"2018","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1109\/JSEN.2019.2945364","article-title":"Stethoscope-sensed speech and breath-sounds for person identification with sparse training data","volume":"20","author":"Tran","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Aumi, M.T.I., and Kratz, S. (2014, January 23\u201326). Airauth: Evaluating in-air hand gestures for authentication. Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services, Toronto, ON, Canada.","DOI":"10.1145\/2628363.2628388"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Mao, W., He, J., and Qiu, L. (2016, January 3\u20137). Cat: High-precision acoustic motion tracking. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, New York, NY, USA.","DOI":"10.1145\/2973750.2973755"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nandakumar, R., Iyer, V., Tan, D., and Gollakota, S. (2016, January 7\u201312). Fingerio: Using active sonar for fine-grained finger tracking. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA.","DOI":"10.1145\/2858036.2858580"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wang, W., Liu, A.X., and Sun, K. (2016, January 3\u20137). Device-free gesture tracking using acoustic signals. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, New York, NY, USA.","DOI":"10.1145\/2973750.2973764"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Yun, S., Chen, Y.C., Zheng, H., Qiu, L., and Mao, W. (2017, January 19\u201323). Strata: Fine-grained acoustic-based device-free tracking. Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, Niagara Falls, NY, USA.","DOI":"10.1145\/3081333.3081356"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Wang, J., Wang, W., Wang, Z., and Liu, Y. (2018, January 16\u201319). Vernier: Accurate and fast acoustic motion tracking using mobile devices. Proceedings of the IEEE INFOCOM 2018-IEEE Conference on Computer Communications, Honolulu, HI, USA.","DOI":"10.1109\/INFOCOM.2018.8486365"},{"key":"ref_32","unstructured":"Sun, K., Zhao, T., Wang, W., and Xie, L. (November, January 29). Vskin: Sensing touch gestures on surfaces of mobile devices using acoustic signals. Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, New Delhi, India."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Zou, Y., Yang, Q., Ruby, R., Han, Y., Wu, S., Li, M., and Wu, K. (2019, January 7\u20139). EchoWrite: An acoustic-based finger input system without training. Proceedings of the IEEE ICDCS, Dallas, TX, USA.","DOI":"10.1109\/ICDCS.2019.00082"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, Y., Shen, J., and Zheng, Y. (2020). Push the Limit of Acoustic Gesture Recognition. IEEE Trans. Mob. Comput.","DOI":"10.1109\/INFOCOM41043.2020.9155402"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Peng, C., Shen, G., Zhang, Y., Li, Y., and Tan, K. (2007, January 6\u20139). Beepbeep: A high accuracy acoustic ranging system using cots mobile devices. Proceedings of the 5th International Conference on Embedded Networked Sensor Systems, Sydney, NSW, Australia.","DOI":"10.1145\/1322263.1322265"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lazik, P., and Rowe, A. (2012, January 6\u20139). Indoor pseudo-ranging of mobile devices using ultrasonic chirps. Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, Toronto, ON, Canada.","DOI":"10.1145\/2426656.2426667"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Wang, A., and Gollakota, S. (2019, January 4\u20139). Millisonic: Pushing the limits of acoustic motion tracking. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Scotland UK.","DOI":"10.1145\/3290605.3300248"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Cao, G., Yuan, K., Xiong, J., Yang, P., Yan, Y., Zhou, H., and Li, X.Y. (2020, January 16\u201319). EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking. Proceedings of the 18th Conference on Embedded Networked Sensor Systems, Virtual Event.","DOI":"10.1145\/3384419.3430730"},{"key":"ref_39","unstructured":"Nilsson, J., and Akenine-M\u00f6ller, T. (2020). Understanding ssim. arXiv."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1109\/34.232073","article-title":"Comparing images using the Hausdorff distance","volume":"15","author":"Huttenlocher","year":"1993","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_41","unstructured":"Rish, I. (2001, January 4\u201310). An empirical study of the naive Bayes classifier. Proceedings of the IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence, Seattle, WA, USA."},{"key":"ref_42","unstructured":"Seber, G.A., and Lee, A.J. (2012). Linear Regression Analysis, John Wiley & Sons."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_45","unstructured":"(2022, November 01). The STU-300 LCD Signature Pad. Available online: https:\/\/www.wacom.com\/en-jp\/products\/stu-300."},{"key":"ref_46","unstructured":"Goodfellow, I.J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014). Generative adversarial networks. arXiv."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/23\/9343\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:30:48Z","timestamp":1760146248000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/23\/9343"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,30]]},"references-count":46,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["s22239343"],"URL":"https:\/\/doi.org\/10.3390\/s22239343","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,30]]}}}