DIT PhD Project

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DIT PhD Project
Supervisor name & contact details:
Name: Fredrick Mtenzi
Email [email protected]
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)
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