## 1 Introduction  
Smartphones have become an indispensable part of our lives as they are used for various aspects of people's daily activities. Besides communicating with others, we also use smartphones as cameras, notebooks, digital wallets, etc. Additionally, we exchange data and conduct payments using Near Field Communication (NFC) and control other devices through Bluetooth and WiFi. As a result, we keep a lot of personal data stored in our smartphones (e.g., videos, photos, credit card numbers, PINs, bank accounts, etc.). Currently, due to the COVID pandemic crisis, we also use smartphones for health issues, such as contact tracing, which entails storing data about our physical contacts [1]. The usefulness of smartphones has boosted them to the top of the most used devices on the web today, keeping a 55% of the global market share according to reported statistics [2]. This was achieved despite mobile users' security and privacy concerns [3] and, most importantly, their concern over the potential disclosure of sensitive data [4, 5]. Nowadays a new concern is arising, called nomophobia, due to the fear of losing smartphones along with the data stored in them [6, 7, 8]. At the same time, the growth of the Internet of Things (IoT) triggers a growth in the number of device connections, which entails that in the years to come, a vast number of connected devices must be protected [9]. To overcome these concerns, smartphone vendors implement authentication measures, such as passwords, PINs, and physiological biometrics (e.g., fingerprints, face recognition,etc.) to ensure that devices are used by legitimate users. The adoption rate of physiological biometrics has raised from 9% to 20% during the decade 2000-2010 [10]. Although these measures do provide increased security and privacy, one of their major limitations is that they authenticate users just once, when they connect to a mobile service [11]. Thus, if a smartphone gets stolen or lost while the user was logged in a service, the person who found or stole the smartphone can have access to the data stored in it. It has been shown that a password or PIN on its own is insufficient to provide adequate security for smartphones [4, 12, 13, 14]. To meet this challenge, new technologies that provide continuous authentication, such as Behavioral Biometric Continuous Authentication (BBCA), face detection, have been introduced [15, 16, 17, 18, 19]. BBCA has emerged as a combination of Behavioral Biometrics and Continuous Authentication. BBCA is an indirect method of validation of a legitimate user based on the capture of behavioral attributes using tools and built-in smartphone sensors [20]. Behavioral biometrics refer to the observable behavior used to identify or confirm the identity of an individual. In contrast to physiological biometrics, it focuses on behavior patterns instead of physical characteristics, such as fingerprints and facial features [21]. Continuous authentication offers a safer and more protective alternative [22], and behavioral biometrics, which are incorporated within the continuous authentication framework, constitute a preferable solution for the protection of users' data [23]. In addition, a large corpus of research has shown evidence regarding the superiority of the fusion of multimodal biometric approaches. A variety of combinations is used with the fusion of biometrics that achieves improved results compared to the single modality methods [15, 24, 25]. Thus, the fusion of multimodal biometrics authentication emerges as a definite future trend. Hence, we consider BBCA as an effective protective technology for smartphones users. Although a significant volume of research on BBCA has been published, the focus of recent BBCA research lies almost exclusively on the development and the improvement of behavioral biometrics continuous authentication systems [26]. On the other hand, the role of users' attitude towards BBCA technology has been overlooked.