PriMe: A Novel Privacy Measuring Framework for Online Social Networks
Ahmad Hassanpour, Bian Yang · 2022
Online Social Networks are responsible for disclosing a large amount of sensitive information. Users unintentionally reveal their sensitive information and are unaware of the privacy risks involved. But the users should be well informed about their privacy quotient and should know where they stand on the privacy measuring scale. In this paper, we proposed an adaptive privacy measuring framework called PriMe that can measure the privacy leakage score for each action of a user in an OSN and subsequently adjust the privacy settings based on the preferred privacy scopes and boundaries. Various types of data, actions, and personal characteristics of each user have been considered to ensure the calculated privacy leakage score is accurate.