About this role
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About this opportunity:
Enterprise information and IT assets must be classified correctly so that security controls, access restrictions, storage, sharing, resilience, and lifecycle requirements are appropriate to their business value and criticality. Classification is often a manual process that depends on complete asset information, consistent interpretation of requirements, and expert judgement. Incomplete records or inconsistent decisions can result in assets being under-protected, over-protected, or handled incorrectly.
This master’s thesis will investigate how Generative AI can support the classification of enterprise information and IT assets. The aim is to design and evaluate an AI-assisted prototype that analyses available asset information, business context, and applicable security requirements and recommends suitable classification levels for confidentiality, integrity, availability, and asset criticality. Each recommendation should include clear reasoning, the evidence used, relevant uncertainties, and any missing information that requires human review.
The AI-generated classifications will be compared with assessments performed by experienced security experts or asset owners to evaluate accuracy, consistency, explainability, and usefulness.
What you will do:
• Review relevant literature and current approaches for information classification, asset management, criticality assessment, and AI-assisted decision support.
• Study applicable security and business requirements and translate them into transparent classification criteria.
• Identify the asset attributes and contextual information needed for reliable classification, including ownership, purpose, information handled, business impact, dependencies, regulatory obligations, and lifecycle stage.
• Design and implement a prototype that uses Generative AI to analyse structured and unstructured asset information and recommend classification levels.
• Provide traceable explanations for each recommendation and identify missing, conflicting, or low-confidence input that requires clarification.
• Create a representative, appropriately protected dataset and establish expert-reviewed reference classifications.
• Compare AI recommendations with expert assessments using measures such as accuracy, agreement, consistency, false-positive and false-negative rates, explanation quality, confidence calibration, and review effort.
• Analyse limitations, security and privacy risks, data-quality dependencies, and suitable human oversight for operational use.
The skills you bring:
• Master’s-level studies in computer science, cybersecurity, information systems, data science, software engineering, or a related field.
• Understanding of information security, asset management, risk assessment, or data governance.
• Experience with Python and Large Language Models, prompt engineering, machine learning, or Retrieval-Augmented Generation.
• Ability to work with structured and unstructured data and evaluate data quality.
• Interest in empirical evaluation, explainable AI, information protection, and responsible AI.
• Strong analytical, problem-solving, and communication skills.
Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Stockholm
Req ID: 791043