Social Networks and Web Security and Privacy

Web and social networking applications are essential parts of our daily life. We aim to make web and social networking applications secure and privacy-preserving. In particular, we study the social networks and web security and privacy problems that revolve around the data generated by them. For instance, the problems we focus on include, but not limited to, detecting fake and compromised users in social networking and web services, uncovering new privacy attacks (e.g., attribute inference attacks, link inference attacks) to social network users and their defenses, as well as developing new user authentication methods for social networking services. Our approach leverages artificial intelligence techniques including (trustworthy) machine/deep learning, network science, natural language processing, and optimization. A key challenge of leveraging artificial intelligence for web and social networks security and privacy is how to incorporate the unique characteristics of the security and privacy problems. We are interested in developing new artificial intelligence techniques to address the unique challenges of the security and privacy problems in social networks and web applications.


Inference attacks and their defenses

Machine learning is used by attackers to perform automated large-scale attacks. We develop new machine learning techniques as privacy attacks to infer users' private attributes (e.g., location, sexual orientation, political view), hidden social relationships, and identity, using users' data publicly available on social networks and web services. We also develop defenses for these inference attacks.               

Spam and fraud detection

We develop new machine learning methods to detect spam, fake accounts, and malicious accounts in social networking and web services.

Secure and privacy-preserving recommender systems

Recommender system is a key component of web services. We aim to make recommender systems secure and privacy-preserving.

User authentication

We leverage social networks to enhance user authentication. 

Social network measurement and modeling

Code and dataset