Incidentes de segurança contra usuários em redes sociais: um mapeamento sistemático

Abstract

The growing use of social media has changed the way people communicate, share information, and interact in the digital environment. However, this popularization has also resulted in a significant increase in security incidents that directly affect users, such as phishing attacks, malware dissemination, social engineering, identity theft, and sensitive data exposure. This work aims to systematically map the scientific literature published between 2018 and 2024 to identify and categorize the main types of security incidents faced by social media users, the most commonly exploited vulnerabilities, and the strategies proposed to prevent and mitigate these risks. The methodology is based on the selection and analysis of scientific articles extracted from relevant databases, following specific inclusion and exclusion criteria. The results indicate that the most recurring themes involve social bots and malicious behavior (33%), phishing attacks (28%), social engineering (18%), malware (15%), and the privacy and data leaks (14%) and the application of machine learning and deep learning techniques for mitigation. It is concluded that security on social networks requires integrated actions between technology, digital education and data protection policies, in order to reduce the impacts of incidents and strengthen users’ trust in these platforms.