Looking at predicting vulnerabilities in third party software using Machine-Learning and Data-Mining techniques
Your role
Background
Software security vulnerabilities are one of the critical issues in the realm of computer security. Due to their potential high severity impacts, many different approaches have been proposed in the past decades to mitigate the damages of software vulnerabilities. Machine-learning and data-mining techniques are also among the many approaches to address this issue. This poses a greater problem when a high security organisation wants to utilize external software from the open source community.
In this Master Thesis we want to look at this problem from both a theoretical and practical view. We need to explore what possibilities we have to secure the external software brought in to the organisation. By extracting open data such as open source issue trackers and CVE databases you could predict if a third party software contains known or even unknown vulnerabilities.
Description of the master thesis:
As implied above, this Master Thesis will be both theoretical and practical. We see three parts: One study phase to learn more about current technology for predicting vulnerabilities in software. The second phase is to gather data that can be used to predict vulnerabilities in software and the third phase is to experiment with ML models to predict vulnerabilities in software.
Your profile
We are looking for 2 master degree students with an interest in:
Data integrity and analysis
Machine learning
Cyber security
You are at the end of your master’s degree in Computer engineering, Computer Science, Electrical engineering, or equivalent, and is eligble for your 30 HP degree project.
This position requires that you pass a security vetting based on the current regulations around/of security protection. For positions requiring security clearance additional obligations on citizenship may apply.
What you will be a part of
You will collaborate with experienced engineers and professionals in an environment that fosters career development and personal growth. You will be part of Software Excellence at Saab Surveillance in Gothenburg or Stockholm.
Time period: During 2024
Location: Stockholm or Gothenburg
Surveillance, a Business Area within Saab, is a world-leading supplier of systems for detection of threats and self-protection. Design, Software excellence is an organisation with the strategy and mission to supply methods, tools and infrastructure for digital development, increasing the efficiency, speed and security in both products and tools.
Contact information
Thesis Superviser:
Stefan Pedersen, stefan.pedersen@saabgroup.com, +46 73 4373718
Freddy Aasberg, freddy.aasberg@saabgroup.com, +46 734375278
Saab is a leading defence and security company with an enduring mission, to help nations keep their people and society safe. Empowered by its 22,000 talented people, Saab constantly pushes the boundaries of technology to create a safer and more sustainable world.
Saab designs, manufactures and maintains advanced systems in aeronautics, weapons, command and control, sensors and underwater systems. Saab is headquartered in Sweden. It has major operations all over the world and is part of the domestic defence capability of several nations. Read more about us here