DIT PhD Project Supervisor name & contact details: Name: Fredrick Mtenzi Email Fredrick.Mtenzi@dit.ie Supervisors Profile: Research Centre: Applied Intelligence Research Centre The Applied Intelligence Research Centre researches the application of computational intelligence technologies to real world problems. The core competencies of the AIRC include machine learning, language technologies, intelligent agents and data analytics. Research Centre website: www.comp.dit.ie/aigroup Supervisors Publication List: http://arrow.dit.ie/do/search/?q=Fredrick%20 Mtenzi&start=0&context=680085 Title of the Project: Predictive Protection of Sensitive Information Found in Social Networking Applications Project Summary: Social networking applications have emerged as powerful tools that are used in nearly all walks of life. The information shared in these networks is useful to its users and provides them with a persistent virtual presence. This information has entertainment and socialization value to individual users and business value to organisations. However, once the information is published its control and protection pose formidable challenges. These challenges are compounded by the availability of software tools and techniques that can aggregate information or may infer this information for malicious reasons. Most of the current security solutions for ensuring control and providing information protection cannot be used for social networking applications without significant modifications. For example, while encryption can be used as an efficient method for protecting information at rest, when applied to dynamic information residing in social networks a lot of challenges arise. These challenges include open questions such as: How can we encrypt dynamic information and keep it usable? Or how can we perform effective key management in an environment where we have less control? These and other challenges call for more research to be done. In this project an investigation of the challenges of controlling and protecting information that is found in social networking applications, which are outside the traditional organisation boundary (walls or firewalls), will be carried out. The next part of the project will be to implement strategies for quantifying and classifying the amount of information that is outside the organisation boundary. Ultimately the project will propose appropriate predictive protection approaches to support secure social networking exchanges and enhance the control and protection of users’ information. Ciência sem Fronteiras / Science Without Borders Priority Area: Information and Communication Technologies (ICTs)