PhD Studentship in Computer Science: AI Model based Digital Forensics for CyberPhysical Systems
1 month ago
Overview
Forensics often takes place in a local context. However, to detect attacks, protect systems, recover operations, and identify attackers in cyberphysical systems requires cooperation across a number of defenders -- the cyberphysical network and the core. Indeed ISP networks have visibility into 60-70% of network traffic however, they don't have the intelligence or the context of the local cyberphysical system in order to attribute attacks or detect stepping stones.
This prompts several big research challenges. First, invisibility -- attackers avoid detection borrowing techniques from the field of anonymous communications. Second, cooperation -- the attack information is distributed across the core and the edge, and joining the dotted lines up seems inherently hard. Third, -- Attack attribution requires extensive cooperation across networks however, it is often impeded by uncooperative intermediaries.
Specifically, this project aims to develop methods and tools to address the challenges of visibility, scale, privacy, false-positives, and cooperation. AI based techniques will be explored to make Cyber Physical Systems forensic ready.
Number Of Awards
1
Start Date
September 2024
Award Duration
3.5 years
Application Closing Date
1 June 2024
Sponsor
EPSRC Doctoral Training Program
Supervisors
Dr Mujeeb Ahmed
Eligibility Criteria
You must have/expect to gain, minimum 2:1 MSc in a relevant field, such as Computer Science, Computer Engineering, or Cyber Security. Strong programming skills, preferably Python, Matlab, or R. Experience with one or more of hardware-programming, cyber physical/electrical systems, privacy-enhancing technologies, machine learning, signal processing. Good communication skills, especially in written English. Strong work ethics. Ability to think creatively and work independently.
Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills.
The studentship covers fees at the Home rate (UK and EU applicants with pre-settled/settled status and meet the residency criteria). International applicants are welcome to apply but will be required to cover the difference between Home and International fees.
International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.
How To Apply
Apply to Newcastle Portal
Select 'Create a Postgraduate Application'.
Use 'Course Search' to identify your programme of study:
· Search 'Course Title' using programme code: 8050F
· Research Area: Computing Science
· Select PhD Computer Science as programme of study
Provide the following information in 'Further Details' section:
· 'Personal Statement' (mandatory field) - You should provide a 200 word statement of interest in which you say why you are interested in studying for a PhD and how you believe you have the qualities and experiences for this research project.
· Studentship code COMP2161 in 'Studentship/Partnership Reference' field
· When prompted regarding research proposal - select 'Write Proposal'. You should type in the title of the research project from this advert.
In addition, before you submit your application you will need to upload the following supporting documentation:
· covering letter/CV
· degree transcripts/certificates, if English is not your first language, a copy of your English language qualification if already completed.
Contact Details
Dr Mujeeb Ahmed, Prof Shishir Nagaraja
100% Home fees covered and a minimum tax-free annual living allowance £18, UKRI rate)
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Newcastle upon Tyne, Newcastle upon Tyne, United Kingdom Newcastle University Full timeOverviewForensics often takes place in a local context. However, to detect attacks, protect systems, recover operations, and identify attackers in cyberphysical systems requires cooperation across a number of defenders -- the cyberphysical network and the core. Indeed ISP networks have visibility into 60-70% of network traffic however, they don't have the...
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Newcastle upon Tyne, Newcastle upon Tyne, United Kingdom Newcastle University Full timeOverviewForensics often takes place in a local context. However, to detect attacks, protect systems, recover operations, and identify attackers in cyberphysical systems requires cooperation across a number of defenders -- the cyberphysical network and the core. Indeed ISP networks have visibility into 60-70% of network traffic however, they don't have the...
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