Looking at predicting vulnerabilities in third party software using Machine-Learning and Data-Mining techniques.

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 1or 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 eligible 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 X Innovation Lab at Saab Surveillance in Göteborg, 

, a Business Area within Saab, is a world-leading supplier of systems for detection of threats and self-protection. Business Unit Radar Solutions is responsible for Radar in airborne-, surface- and naval systems. 

X Innovation Lab is a group working with new technology and new ways of working within Saab Radar Solutions in Göteborg. We do research and create prototypes that are then used in the on-going development of Saab’s products.

Contact information:

Recruiting Manager Maria Stegberg; 

Saab is a company with a strong people-orientation. We offer a friendly work environment where we support and help each other to be at our best. Continuous learning, career & talent development and employee well-being are examples of areas where we always put the strongest effort to offer great opportunities