A transferable and AI-enabled software security framework

A transferable and AI-enabled software security framework - Studentship opportunities | UWE Bristol

Recent cyber security incidents (e.g., “Wannacry”), caused by software vulnerabilities, showcased the necessity of proactive program analysis. Vulnerability discovery methodologies aim to identify software weaknesses by analysing software, either statically or dynamically. These weaknesses can be leveraged by an attacker who aims to access and/or compromise systems without authorisation.

During the 90s, a novel vulnerability detection method for UNIX systems called “fuzzing" was proposed. Fuzzers are systems that feed assessed code with invalid data (generating random input) aiming to discover new vulnerabilities. Fuzz testing is considered as one of the most important techniques for discovering zero-day vulnerabilities and it is rapidly growing in popularity among the cyber security community. This research project aims to investigate the feasibility and effectiveness of a transferable framework that will be able to leverage Machine Learning to efficiently perform fuzz testing in various systems. 

For an informal discussion about the studentship, please email Dr Panagiotis Andriotis ([Email Address Removed]).

PLEASE APPLY HERE: https://www.uwe.ac.uk/research/postgraduate-research-study/how-to-apply/studentship-opportunities/transferable-and-ai-enabled-software-security-framework

Eligibility

Applicants must have a good first degree or, ideally, a Masters. The successful candidate will be expected to demonstrate excellent programming expertise and will have a good practical understanding of machine learning concept, data analytics, and cyber security for networking diagnostics. Students from under-represented groups are particularly encouraged to apply. The studentship is available both for UK and overseas applicants.

A recognised English language qualification is required.

The candidate should have an interest in Cyber Security/Computer Science and especially in software security and program analysis and be familiar with Machine Learning and/or AI concepts.

How to apply

Please submit your application online. When prompted use the reference number 2022-JAN-FET06.

Supporting documentation: you will need to upload your research proposal, all your degree certificates and transcripts and your proof of English language proficiency as attachments to your application so please have these available when you complete the application form.

Applicants have the opportunity to discuss their studentship with Directors of Studies via a Webinar to take place on Wednesday 8^th September 2021 from 10am to 12noon. Please contact [Email Address Removed] to reserve your place at this webinar.