AFPr-AM: a novel fuzzy-AHP based privacy risk assessment model for strategic information management of social media platforms

• Main Authors: Ahvanooey, Milad Taleby, Zhu, Mark Xuefang, Ou, Shiyan, Mazraeh, Hassan Dana, Mazurczyk, Wojciech, Choo, Raymond Kim-Kwang, Li, Chuan
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Privacy Risk Assessment; Fuzzy Systems
• Online Access: https://hdl.handle.net/10356/172203
• Institution: Nanyang Technological University

Social Media Platforms (SMPs) have changed how we communicate, share, and obtain information. However, this also comes at a cost, as users (willingly) share their Privately Sensitive Data (PSDs), such as pictures, real-time locations, and other personal connections, on SMPs. Recently, privacy concerns have gained much attention from both academia and industry. The current literature lacks the privacy risk assessment model that can lead the management sectors (e.g., industrial, social, and governmental) to cooperate to mitigate the privacy invasion risks of users’ PSDs in SMPs. Hence, we propose a novel assessment model (hereafter referred to as AFPr-AM), suggesting alternative strategies for reducing privacy invasion risks of users’ PSDs in SMPs based on determinant criteria. First, we explore multiple factors from the literature that affect the privacy invasion risks of users’ PSDs. Then, to prioritize the importance of determinant criteria, we seek sixty experts to participate in our survey and rank these factors. Finally, we apply the fuzzy analytical hierarchy process approach for weighting the criteria based on the experts’ opinions. Moreover, we employ a cooperative game theory-based multi criteria decision making framework to assess the possibilities of players’ interactions (e.g., management sectors), considering the weighted criteria as players’ payoffs. Our extensive experiments demonstrate that the AFPr-AM model provides effective strategic alternatives to mitigate the possible invasion risks of users’ PSDs in SMPs.