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Research Paper | Computer Science | Volume 15 Issue 3, March 2026 | Pages: 50 - 57 | India
Advanced AI Techniques for Network Threat Detection and Protection in Social Platforms
Abstract: In the era of digital communication, social apps have become the dominant power in terms of communication, sharing information and socialization. Their popularity, however, has given cybercriminals easy targets of exploiting their security weaknesses. Traditional security controls might not be sufficient to detect and prevent advanced and emerging attacks on such systems. AI will make a positive contribution to the security of social apps through its machine learning, deep learning, and anomaly detection capabilities. Focusing on the importance of real-time threat detection and prevention, this paper is going to introduce the AI-based solution to enhance the security of social apps through the network. Through AI methods, the suggested system will identify the known and changing threats, minimize reaction time, and adjust to novel attacks. The paper offers an in-depth analysis of the potential use of the AI-based security solutions to safeguard user data and privacy by use of experimental research and case studies, thus assessing their effectiveness in the real world. The study has provided viable guidelines towards the implementation of AI-based interventions into the current security systems, and therefore encouraging the creation of additional robust security frameworks to social media.
Keywords: AI-based security, threat detection, social applications, anomaly detection, cybersecurity, network security, real-time prevention, privacy protection, data security
How to Cite?: Purva, Dr. Neha Gaba, "Advanced AI Techniques for Network Threat Detection and Protection in Social Platforms", Volume 15 Issue 3, March 2026, International Journal of Science and Research (IJSR), Pages: 50-57, https://www.ijsr.net/getabstract.php?paperid=SR26224115004, DOI: https://dx.dx.doi.org/10.21275/SR26224115004