PhD Studentship: Characterisation of Nuisance Calls In-Network And Improved Detection using Machine Learning Techniques (PARR_U18iEPSRC)

University of East Anglia - School of Computing Sciences

Start date: October 2018

Supervisor: Primary: Professor Gerard Parr
                    Secondary: Dr Tony Bagnall

Project description:

Nuisance calls are a significant global problem. In this project you will be working alongside British Telecommunications (BT) to further the understanding of the in-network characteristics of nuisance calls extending our understanding of how advanced statistical and machine learning techniques can be used to better discriminate between classes of nuisance calls and legitimate traffic over the BT network.  You will have access to a big data environment and observations from the BT voice network to generate insights into the nature of nuisance calls.  Previous work at BT has focussed on time series analytics using similarity searches based on Dynamic Time Warping (DTW) and Symbolic Aggregate approXimation (SAX) to look for suspected nuisance calls in time series data generated from in-network parameters.

This PhD project will consist of two stages: firstly, identifying features associated with nuisance calls and then, in the second stage, using these features to identify nuisance calls over the network.  In contrast to the problem of detection of spam over email, detecting spam over the voice network is still relatively unexplored. In this project you will investigate the characteristics of nuisance calls over the voice network using methods such as unsupervised machine learning and graph theory to examine the relationships in-network. You will explore geometrical representations and visualisations which reveal the underlying nature of nuisance calls furthering our quantitative and qualitative understanding of the problem.

This PhD will be hosted at the School of Computing Sciences at UEA which provides a vibrant environment in which to carry out computing and allied research. As part of this project, the successful student will be expected to spend at least 3 months at BT Research Labs in Adastral Park in Suffolk, UK

With revenues over £20bn and over 102,000 staff, BT is one of the world’s leading digital communications service provider companies.

Person Specification:

Acceptable first degree Computer Science, Physics, Mathematics, Engineering or other numerate discipline. Standard minimum entry requirement is 2:1, but it is desirable that applicants will have a 1st Class Honours Degree in a related subject. 

Funding notes:

This EPSRC Industrial Case studentship is in partnership with BT and funded for 4 years.  An annual stipend of £14,777 plus an enhancement of £2,500 from BT will be available to the successful candidate who meets the UK Research Council eligibility criteria. These requirements are detailed in the RCUK eligibility guide which can be found at http://www.rcuk.ac.uk/documents/publications/traininggrantguidance-pdf/. In most cases UK and EU nationals who have been ordinarily resident in the UK for 3 years prior to the start of the course are eligible for a full-award.  Other EU nationals may qualify for a fees only award. 

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Type / Role:

PhD

Location(s):

South East England