The First International Workshop on Online Privacy and Data Security is co-located with the 8th International Conference on Model and Data Engineering.
The workshop offers a unique opportunity for researchers and practitioners to share their state-of-the-art research and development that balance data access and users’ privacy.
Scope and Topic
With their unparalleled popularity, social networks have pervaded all aspects of our daily and professional lives. Social Networks, together with the users’ online activities, produce large amounts of data that is being collected and used to provide services. However, it is widely recognized that security and privacy are critical issues of social networks. Indeed, on one hand, social networks are used, by attackers, as a platform to launch attacks and distribute malicious information. On the other hand, privacy and data leakage through social networks has become common exercise to the point that users are resigned to the fact that there is no more privacy online.
The main objective of the workshop is to bring together experts and practitioners of data modeling, architectures and techniques in order to provide solutions that balance data access (necessary for social networks and online services) and users’ privacy.
Authors are encouraged to submit original work that illustrates research results and industrial experiences in the areas of data modeling, privacy and security.
Topics of interest include, but are not limited to, the following:
- Models, methods, and tools for data security in social networks
- Secure social network architecture with big data
- Privacy protection in social network
- Secure social networking applications with big data
- Security design for social networks in big data
- Risk analysis and data governance in social network
- Attacks in/via social networks
- Information control and detection
- Malicious behavior modelling in social networks
- Malicious information propagation via social networks
- Big data modelling and analytics for threats and attacks prediction
- Economics of privacy and personal data
- Privacy issues in artificial intelligence
- Modelling of data protection and privacy requirements
- Data models for privacy preserving personalization and recommendation services
- Emerging trends for data protection in social networks