Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
Primary supervisor
Contact admissions office
Other projects with the same supervisor
- Application Level Verification of Solidity Smart Contracts
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Designing Safe & Explainable Neural Models in NLP
- Exploiting Software Vulnerabilities at Large Scale
- Verification Based Model Extraction Attack and Defence for Deep Neural Networks
- Using Program Synthesis for Program Repair in IoT Security
- Automated Repair of Deep Neural Networks
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
- Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
Funding
- Directly Funded Project (Students Worldwide)
This research project has funding attached. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.
Project description
Unmanned aerial vehicles (UAVs) have attracted significant attention due to its emergent importance in a wide range of applications, including military and civil areas. Teal Group's market studies estimate that investments in UAVs will be expanded from $6.4 bi in 2014 to $91 bi in 2024 between military and non-military expenditures. However, only a little amount has been invested in the reliability and security of UAVs. From a technical point of view, UAVs are highly exposed systems, multiply linked, consisting of complex pieces of hardware with high strategic and economic value. The classical UAV control design aims to obtain controllers that tolerate and compensate exogenous perturbations, e.g., wind turbulence and terrain disturbances, but they are unable to ensure the desired performance if a sensor or actuator fault occurs or when the UAV is victim of a cyber-attack. Thus, the main objective of this PhD research is to automatically detect and repair software vulnerabilities in UAVs using fuzzing and symbolic execution techniques. In particular, this PhD research aims to (1) automatically localise faults related to various security vulnerabilities such as buffer overflow, zero-day vulnerabilities and crash reproduction using existing symbolic execution and fuzzing techniques; (2) propose repairs using state-of-the-art program synthesisers, which are built on top of efficient symbolic execution engines, in order to analyse a buggy program against a set of selected tests to infer the specification of the intended system behaviour; and (3) produce patches that can automatically fix bugs related to software vulnerabilities in order to contribute to the vision of self-healing UAV software.
Person specification
For information
- Candidates must hold a minimum of an upper Second Class UK Honours degree or international equivalent in a relevant science or engineering discipline.
- Candidates must meet the School's minimum English Language requirement.
- Candidates will be expected to comply with the University's policies and practices of equality, diversity and inclusion.
Essential
Applicants will be required to evidence the following skills and qualifications.
- You must be capable of performing at a very high level.
- You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.
Desirable
Applicants will be required to evidence the following skills and qualifications.
- You will have good time management.
- You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
General
Applicants will be required to address the following.
- Comment on your transcript/predicted degree marks, outlining both strong and weak points.
- Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
- How well does your previous study prepare you for undertaking Postgraduate Research?
- Why do you believe you are suitable for doing Postgraduate Research?