Cutting-edge trusted frameworks are the preferred choice in this online digital era. It is necessary to manage the development and design processes for scalable, reliable, robust, and highly secured frameworks to boost the efficiency and overall functionality of different framework applications. As the demand for online services continues to increase, organizations need to address security concerns. Continuously prioritizing the significance of a novel trust framework is essential that aids the privacy-preserving solutions and experiences of end-users. Moreover, the utilization of smart devices is increasing at a significant rate, which in turn causes significant traffic on communication networks and leads to high energy consumption. Novel trust framework models should be developed for privacy data aggregation, which plays a key role in reducing energy consumption and reducing redundant data. Protecting against attacks for illegal data access during secure data collection and transfer in social network applications is a challenge, as safeguarding the individual’s data is critical in social networks.

Optimizing privacy is more important than ever as there are a rising number of cybersecurity breaches, which in turn can provide the impetus for online social networks (OSNs) to achieve trustworthiness by mitigating attacks with novel methods. The growth of online social networks and their related challenges and solutions must be efficiently analyzed to bring potential transformation, with appropriate strategies, in the design and implementation of security controls and measures to manage the outcome of security threats. State-of-the-art techniques, algorithms, and trusted framework models with ground-breaking applications of multifactor authentication (MFA) for OSNs will all play a key role in providing an improved end-user experience. Thus, advances in trusted frameworks and the combination of tools, such as identity and access management (IAM) and endpoint security, are essential for effective real-time monitoring of online social network security in order to better aid organizations and individuals. Furthermore, the appropriate selection of efficient trusted frameworks is an intrinsic part of online social network security and so should be the topic of further research.

This Special Issue discusses the evolving security of online social networks, including potential risks, solutions, and models, privacy-preserving aggregation, improved authentication, and algorithms with the aid of recently developing trusted frameworks and their new applications.

Potential topics include but are not limited to the following:

• Trusted framework algorithms and analysis models for location privacy-preserving in online social networks
• Zero trust framework models and cloud-based online social network security for real-time applications
• Robust trust management framework and assessment methods for securing cyberspace and social networks
• Blockchain-based trusted framework for information authentication and secure connections in online social networks
• Trusted frameworks with artificial intelligence (AI)-based tools for monitoring and tracking social networks
• Trusted infrastructure strategic approaches with Internet of Things (IoT) for online social network security
• Current challenges of trusted frameworks in automating risk analysis and protecting social network privacy
• Recent trends in frameworks and techniques for optimizing personalization and privacy control in social networks
• Trusted frameworks with deep learning for fraud analytics in online social networks for preserving financial applications
• Cutting-edge technological integration in mobile social networks for privacy data aggregation and security