Uncovering and Preventing Malicious Activities in Social Networks using Data Science and Machine Learning (MalUncover)

Malicious activities on social networks pose a significant threat to individuals, organizations, and society at large. They imply engagement in a range of harmful activities, including spreading false information, conducting fraudulent transactions, engaging in cyberbullying, and targeting vulnerable individuals for exploitation. To combat these threats, data scientists and machine learning experts are developing new and advanced AI models for detecting and mitigating the impact of these activities on social networks.

This special session at the 10th IEEE International Conference on Data Science and Advanced Analytics will focus on the latest research and developments in AI models for securing social networks from malicious activities. Papers will cover a range of technical topics, including new deep learning models that use or combine text, image, and video modalities for identifying malicious activities; graph neural networks for mapping their networks; and adversarial machine learning approaches for identifying patterns and anomalies that may indicate the presence of malicious activities.

The session will also explore the use of AI single modality, but also multimodal models. in real-world scenarios, such as identifying and mitigating fake news, preventing cyberbullying, and detecting fraudulent transactions on social networks. Presenters will showcase the latest techniques and best practices for implementing these models in production systems and evaluating their performance.

Overall, this special session provides an opportunity for researchers, practitioners, and experts to collaborate and share knowledge on advanced AI models for securing social networks from malicious activities. By bringing together diverse perspectives and expertise, we hope to accelerate the development of new and effective approaches and solutions for early detection and prevention of malicious activities on social networks, and ultimately help create a safer and more secure online environment for all users.