AI-Based Detection of Deepfakes and Misinformation on Social Media

Abstract

Artificial Intelligence and Generative AI technologies have ramped up the generation and dissemination of deepfakes and misinformation on social media platforms. Manipulated videos, images, and synthetic audio, commonly known as ‘deepfake content,’ have become significant threats to digital trust, cybersecurity, political stability, public perception, and authenticity of information. The rapid dissemination of information on social media and the growing sophistication of techniques for generating synthetic media have created a very fertile ground for AI-powered misinformation operations.AI-powered misinformation campaigns are extremely effective and are well-suited to the current speed of information spread on social media, and the evolving techniques for creating synthetic media. Thus, the need for intelligent and automated detection systems is paramount for detecting manipulated content and mitigating its societal effect has become more acute.

This study presents a machine learning, deep learning and multimodal approach for identifying deepfakes and misinformation in social media. This article explores several tools and models for content detection, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer-based models, and hybrid AI systems for real-time content verification and moderation. Further, the study examines the system architectures of automated monitoring, feature extraction, behavioral analysis, and explainable AI mechanisms to enhance detection accuracy and explainability. Potential issues of adversarial attacks and dataset limitations, model bias, computational complexity, and ethical concerns are also examined. The research also identifies future research avenues such as federated learning, blockchain based auditing of media, explainable AI, and multi-platform misinformation detection tools. In summary, the study highlights the critical role of comprehensive AI-supported systems in mitigating the spread of deepfakes and ensuring the integrity of information in today's digital communication landscape.