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ALLSTAT  June 2018

ALLSTAT June 2018

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Subject:

Funded PhD opportunity: SYSTEMATIC CHARACTERISATION OF EARLY WARNING THREATS

From:

Alireza Daneshkhah <[log in to unmask]>

Reply-To:

Alireza Daneshkhah <[log in to unmask]>

Date:

Mon, 4 Jun 2018 15:39:55 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (132 lines)

SYSTEMATIC CHARACTERISATION OF EARLY WARNING THREATS
Eligibility: UK/EU/International students with the required entry requirements

Award Details: £15,000 bursary plus tuition fees

Duration: Full Time - between 3 years and 3 years 6 months fixed term

Application deadline: 31st July

Interview dates: 13th to 17th August

Start date: TBC

Informal enquiries are essential before application; contact Professor
Siraj Ahmed Shaikh to discuss this opportunity.

INTRODUCTION
Coventry University has been voted ‘Modern University of the Year’
three times running by The Times/Sunday Times Good University Guide.
Ranked in the UK’s top 15 (Guardian University Guide), we have a
global reputation for high quality teaching and research with impact.
Almost two-thirds (61%) of our research was judged ‘world leading’ or
‘internationally excellent’ in the Research Excellence Framework (REF)
2014.

The Systems Security Group is concerned with cyber-physical systems
security with a strong focus on systems designs and security
analytics. The group's research has had funding from EPSRC, RAEng,
NCSC, US ONR and MoD, worth over £1.2 million with a total value of
nearly £5 million to the consortiums involved. The Group is part of
the Institute for Future Transport and Cities (FTC), which is the
largest research centre at Coventry University, with over 138 research
staff and over a 125 research students.

THE PROJECT
The central research question addressed here is: how do we derive a
meaningful set of threat indicators that aid in early estimation of
threats, in the context of multi-stage attacks? This is broken down
into various sub-problems including

What mix of descriptive and dynamic characteristics account for
effective early estimation of network behaviour, given acceptable
levels of behavioural uncertainty?
Given a Bayesian-based decision-making framework, could priors and
likelihoods be mechanised in a structured fashion against a
combination of discrete and continuous threat characteristics? Could
this be validated for a real-world scenario?
The candidate will carry out a detailed critical review of the
literature on security analytics techniques focusing on stealthy
behaviour monitoring, threat intelligence gathering and noise
filtering in sensor-fused environments. Characterisation using threat
classes will also be reviewed to judge on suitability for early
indication criteria. A taxonomy will be proposed, over the MITRE’s
reference model Common Vulnerabilities and Exposures (CVE) to
accommodate for annotation for early indication. The candidate will
then be automating this with relevant interfaces (using an open API
standard) to inform risk-drive prior probabilities and likelihoods for
decision making.

FUNDING
Fully funded PhD opportunity –Stipend plus Tuition Fees UK/EU Students only

BENEFITS
Drawing the advert to a close, this aims to provide a snapshot of
unique selling points for the University and Faculty. It could cover
things like: investment; added value services and student support;
exceptional facilities and equipment; prestigious collaborations.

Our research strategy is underpinned by a £250m investment in research
and facilities
Dedicated Doctoral College and Centre for Research Capability
Development deliver high quality professional support for researchers,
from PhD to Professor
Free training: research career planning, managing your doctorate,
research communication skills, research ethics, research impact,
research integrity, research methods and research supervision
Coventry is a member of the Doctoral Training Alliance (DTA), the
largest multi-partner and only nationwide doctoral training initiative
of its kind.
ENTRY REQUIREMENTS
Successful applicants will have:

A minimum of a 2:1 first degree in a relevant discipline/subject area
with a minimum 60% mark in the Project element or equivalent with a
minimum 60% overall module average, or
A Masters Degree in a relevant subject area will be considered as an
equivalent. The Masters must have been attained with overall marks at
merit level (60%). In addition, the dissertation or equivalent element
in the Masters must also have been attained with a mark at merit level
(60%).
The potential to engage in innovative research and to complete the PhD
within a prescribed period of study
Language proficiency (IELTS overall minimum score of 7.0 with a
minimum of 6.5 in each component).
Additonally:

A minimum of a 2:1 first degree in computer science, cyber security,
mathematics, electronics or systems engineering
Good knowledge of one or more of these areas: cyber security, threat
modelling or network security.
ELIGIBILITY & APPLICATION PROCEDURE
Eligibility:

All UK/EU/International students are eligible to apply that meet the
academic requirements, the eligibility criteria can be found making an
application page.

In order to apply for this studentship, please visit:

https://www.coventry.ac.uk/research/research-students/research-studentships/systematic-characterisation-of-early-warning-threats/






Dr Alireza Daneshkhah
Senior Lecturer in Statistics
Course Director of Mathematics and Statistics/Data Analytics Courses
School of Computing, Electronics and Mathematics
Faculty of Engineering, Environment and Computing
Coventry University
Coventry, CV1 2JH, UK
T: (+44(0) 2477659179
E: [log in to unmask]
Linkedin: https://www.linkedin.com/in/alireza-daneshkhah-88034653/

You may leave the list at any time by sending the command

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