Biometric Digital Privacy Protection behavior for deep fake Apps Users among Egyptian University Students

Kamal Moussa Diab, Mennatallah

doi:10.21608/jkom.2022.253088

Biometric Digital Privacy Protection behavior for deep fake Apps Users among Egyptian University Students

Author

Mennatallah Kamal Moussa Diab

Radio and Television Instructor , Faculty of Media ,Beni Suef University, Egypt

10.21608/jkom.2022.253088

Abstract

In light of the spread of many deep learning techniques and apps, electronic apps have appeared that require the collection of a huge amount of Biometric digital data from its users, one of the most prominent of those apps recently appeared-and depending on deep learning technology is the Deepfake Apps, which depend on creating fake photos and videos that humans cannot distinguish from the original photos and videos such as DeepFakeLab, Face Swap Live, Zao, Reface.
The importance of the study is clear due to the lake of Arab media studies dealing with the employing of artificial intelligence techniques and the new phenomena in Biometric digital media such as Deepfake Apps and the danger of these apps is that they require the collection and storage of different (biometric) characteristics, such as the face, iris, fingerprint which hacks the Biometric Digital Privacy of those apps users.
The current study aim to identify the behavior of biometric digital privacy protection for deep fake Apps Users among Egyptian University Students, it also aim to identify the usage rates of the study sample for those apps according to demographic variables, type of phone variable, the university and the nature of residence and to reveal the differences between them in the behavior of (biometric) digital privacy protection.
In this context, the (biometric) privacy protection motivation scale was applied on a convenience sample of 390 individuals from Egyptian (public-private) university students in (rural-urban) areas according to the Protection Motivation Theory PMT, which has been used in several studies to explore the behaviors of digital privacy online, the term “the (biometric) digital privacy protection behaviors refers to the procedures are used to avoid the stealing of sensitive personal and vital information.
The findings of the study indicated that there were statistically significant differences among students are using deep fake Apps and non-users of Apps in the five sub-dimensions of the scale (perceived intensity, perceived susceptibility to influence, self-efficacy, response effectiveness, and rewards) and the overall score on the biometric protection behavior scale.

Keywords

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