BeCAPTCHA: Behavioral bot detection using touchscreen and mobile sensors benchmarked on HuMIdb
EntityUAM. Departamento de Tecnología Electrónica y de las Comunicaciones
10.1016/j.engappai.2020.104058Acien, A.; Morales, A.; Fiérrez, J.; Vera-Rodríguez, R.; Delgado, Ó. BeCAPTCHA: Behavioral bot detection using touchscreen and mobile sensors benchmarked on HuMIdb, Engineering Applications of Artificial Intelligence 98 (2021): 104058.1-104058.11
Funded byThis work has been supported by projects: PRIMA, Spain (H2020-MSCA-ITN-2019-860315), TRESPASS-ETN, Spain (H2020-MSCA-ITN-2019-860813), BIBECA RTI2018-101248-B-I00 (MINECO/FEDER), and BioGuard, Spain (Ayudas Fundación BBVA a Equipos de Investigación Científica 2017). Spanish Patent Application P202030066
Projectinfo:eu-repo/grantAgreement/EC/H2020/860315/EU/PriMa-ITN; info:eu-repo/grantAgreement/EC/H2020/860813/EU/TReSPAsS-ETN; Gobierno de España. RTI2018-101248-B-I00
SubjectsBiometrics; Database; HCI; Mobile behavior; Multimodal; Smartphone; Telecomunicaciones
Rights© 2020 Elsevier Ltd.
In this paper we study the suitability of a new generation of CAPTCHA methods based on smartphone interactions. The heterogeneous flow of data generated during the interaction with the smartphones can be used to model human behavior when interacting with the technology and improve bot detection algorithms. For this, we propose BeCAPTCHA, a CAPTCHA method based on the analysis of the touchscreen information obtained during a single drag and drop task in combination with the accelerometer data. The goal of BeCAPTCHA is to determine whether the drag and drop task was realized by a human or a bot. We evaluate the method by generating fake samples synthesized with Generative Adversarial Neural Networks and handcrafted methods. Our results suggest the potential of mobile sensors to characterize the human behavior and develop a new generation of CAPTCHAs. The experiments are evaluated with HuMIdb1 (Human Mobile Interaction database), a novel multimodal mobile database that comprises 14 mobile sensors acquired from 600 users. HuMIdb is freely available to the research community
Google Scholar:Acién Ayala, Alejandro - Morales Moreno, Aythami - Fiérrez Aguilar, Julián - Vera Rodríguez, Rubén - Delgado Ben Mohatar, Óscar
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