Abstract The continuous advancement in the Internet of Things technology allows people to connect anywhere at any time, thus showing great potential in technology like smart devices (including smartphones and wearable devices). However, there is a possible risk of unauthorized access to these devices and technologies. Unfortunately, frequently used authentication schemes for protecting smart devices (such as passwords, PINs, and pattern locks) are vulnerable to many attacks. USB tokens and hardware keys have a risk of being lost. Biometric verification schemes are insecure as well as they are susceptible to spoofing attacks. Maturity in sensor chips and machine learning algorithms provides a better solution for authentication problems based on behavioral biometrics, which aims to identify the behavioral traits that a user possesses, such as hand movements and waving patterns. Therefore, this research study aims to provide a solution for passive and continuous authentication of smartphone users by analyzing their activity patterns when interacting with their phones. The motivation is to learn the physical interactions of a smartphone owner for distinguishing him/her from other users to avoid any unauthorized access to the device. Extensive experiments were conducted to test the performance of the proposed scheme using random forests, support vector machine, and Bayes net. The best average recognition accuracy of 74.97% is achieved with the random forests classifier, which shows the significance of recognizing smartphone users based on their interaction with the phones.

Mohammed A. Alqarni

Sajjad Hussain Chauhdary

Maryam Naseer Malik

Muhammad Ehatisham-ul-Haq

Muhammad Awais Azam

Human-centric Computing and Information Sciences

在以人为中心的计算和信息科学（HCIS）中，KIPS-CSWRG 发表了高质量的论文，涵盖了与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及 HCIS 范围内的其他问题具有重要价值的结果。此外，我们预计它们将引发与我们未来生活相关的进一步相关研究和技术改进。

The journal "Human-centric Computing and Information Sciences" focuses on Human-centric Computing and Information Sciences (HCIS) and is published by KIPS-CSWRG. It publishes high-quality papers covering various theoretical and practical applications related to HCIS. The published papers demonstrate significant contributions to solving various issues in applied services and other important problems within the HCIS domain. Furthermore, we anticipate that these studies will inspire further research and technological advancements related to our future lives.

《Human-centric Computing and Information Sciences》期刊专注于以人为中心的计算和信息科学（HCIS），由KIPS-CSWRG出版。期刊发表高质量的论文，涵盖与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及HCIS领域内其他重要问题的显著贡献。此外，我们期待这些研究能够引发与未来生活相关的进一步研究和技术改进。

Category	Quartile
计算机科学	2
计算机科学, 计算机信息系统	2

Identifying smartphone users based on how they interact with their phones

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	2