Providing Privacy Protection and Personalization Awareness for Android Devices

Abstract

With an increasing number of applications appearing, smartphones with powerful processors and a variety of sensors are ideal mobile devices at hand. On one hand, various applications which are able to provide personalization functions that provide the service of interest to users rely on gathering and analyzing the sensor data and other sensitive information. On the other hand, attackers can accurately classify activities of mobile users from these data. As a result, the risk of users compromising their privacy has risen exponentially. Mobile users currently cannot control how various applications handle the privacy of their sensor data. To address the issue, we present P3Android whose architecture can support applications' personalization functions in Android according to users' personae and use the concept of profile to prevent sensitive information from unauthorized access. Furthermore, we provide a privacy protection service for legacy apps. which can enforce different protection policies according to the risk level of apps. All of these cooperate to provide both personalization awareness and privacy protection in Android. Experiments show that P3Android is feasible and effective.

Twitter Users’ Privacy Behavior: A Reasoned Action Approach

“…This research is discussed below. Other hypothesized predictors have included privacy management abilities (Dienlin & Metzger, 2016; Dienlin & Trepte, 2015; Epstein & Quinn, 2020), need for self-identity (Marwick & Boyd, 2011; Wu, 2019), attitude (Dienlin & Trepte, 2015; Epstein & Quinn, 2020), norms (Dienlin & Trepte, 2015), personality traits and intelligence (Nardis & Panek, 2019; Sindermann et al, 2021), privacy literacy (Desimpelaere et al, 2020), trust in online relationships (Aïmeur & Sahnoune, 2020), and background variables such as culture (Baruh et al, 2017; Liang et al, 2016), gender, and age (Baruh et al, 2017; Walrave et al, 2012).…”

“…Consistent with this recommendation, in the present study, we examined intentions to engage in privacy behavior on Twitter, a currently popular social networking site that serves as a platform for interpersonal communication as well as a microblogging platform (Marwick & Boyd, 2011) for mass communication (French & Bazarova, 2017). On Twitter, information is open to everyone unless users actively customize their privacy settings (Liang et al, 2016). Studying privacy behavior on this alternative platform has the potential to enrich our understanding of the processes underlying privacy behavior in a high-vulnerability environment.…”