Innovative and sustainable framework for enhancing privacy and security in peer-to-peer social applications

Innovation includes peer-to-peer (P2P) confidentiality in social applications, which offers secure, decentralized communication. However, malware, phishing, and risks of data privacy are still on the list of challenges. The present research thus suggests a sustainable framework based on applied sciences: quantum communication, biometric authentication, and AI-driven threat prediction. Empirical trials validate the effectiveness of such a framework to mitigate risks of data breaches and unauthorized access. This study thus advances secure P2P systems, balancing privacy, functionality, and scalability, as it focuses on user education and adaptive privacy measures. It points to the need for continuous innovation in applied sciences, responding to continuously evolving cybersecurity challenges in decentralized networks.