Data Security and Privacy Research Trends: LDA Topic Modeling

Abstract

Abstract With the rapid advancement of big data technologies, the need for robust data security and privacy measures has intensified. Big data technologies have revolutionized the collection and analysis of a vast volume of research literature, offering unparalleled avenues for scholarly inquiry. Identifying prevalent research topics and discerning developmental trends is paramount, especially when grounded in an expansive literature base. This study examined abstracts and author keywords from 4,311 pertinent articles published between 1980 and 2023, sourced from the Web of Science core collection. The content of abstracts and author keywords underwent LDA theme modeling analysis. Consequently, five predominant research topics emerged: security and privacy measures for mobile applications, encryption protocols tailored for image security, privacy considerations in healthcare, intricate access control combined with security in cloud computing through attribute encryption, and ensuring security and information integrity for big data within the Internet of Things framework. The LDA model proficiently pinpoints these salient topics, assisting researchers in comprehending the current state of the domain and guiding potential future research trajectories.