Dr Harjit Singh PhD
Brief biographical information
Behavioural Profiling and Intrusion Detection Systems Using Data Mining
The continuous growth of computer networks, coupled with the increasing number of people relying upon information technology, has inevitably attracted both mischievous and malicious abusers. Such abuse may originate from both outside an organisation and from within, and will not necessarily be prevented by traditional authentication and access control mechanisms. In the event that an unauthorised user compromises a systems initial authentication, the user is in the position to do virtually anything without being further challenged. This has caused interest in the concept of continuous authentication during a user?s active session based upon their behaviour characteristics.Dr Harjit Singh
Intrusion Detection Systems can contribute to a solution here by continuously monitoring for signs of unauthorised activity. The techniques employed often involve the collection of vast amounts of auditing data to identify abnormalities against historical user behaviour profiles and known intrusion scenarios. The approach may be optimised using domain expertise to extract only the relevant information from the wealth available, but this can be time consuming and knowledge intensive. Whereas most reported work in this area uses statistical approaches to model the temporal regularities exhibited by users, this thesis presents a series of comparative studies carried out using data mining techniques and algorithms.
This thesis examines the potential of Data Mining algorithms and techniques to automate the data analysis process and aid in the identification of system features and latent trends that could be used to profile user behaviour. It presents the result of the analysis carried out and discusses a proposed systematic correlation framework for continuous user authentication using the Data Mining methodology adopted in the comparative studies. The research shows how the correlation framework could be used to automate the analysis of the generated audit data as well as the processes involved in authenticating users in a networked environment.
Director of studies: Dr Benn Lines
Other supervisors: Dr Steven M Furnell, Prof. Emmanuel Ifeachor
Web Services: Opportunities and Obstacles in the path of its early adoption
A Correlation Framework for Continuous User Authentication Using Data Mining
A Preliminary Investigation of User Authentication Using Continuous Keystroke Analysis
Investigating and Evaluating Behavioural Profiling and Intrusion Detection Using Data Mining
5 Conference papers
Advanced Authentication and Intrusion Detection Technologies
6 publication(s) - all categories.