PhD position on Explainable Incident Response -- TUCCR

Analysts working in Security Operations Centres (SOCs) investigate thousands of alerts daily, often leading to burnout and fatigue. In recent years, machine learning (ML) has emerged as a promising solution to automate the workflows of SOC analysts. However, analysts are often contractually obligated to investigate all alerts, thus, making it critical that they can understand how such ML-based solutions work.

The objective of this PhD project is to create ‘AI-assisted practitioners' for incident response by developing novel human-in-the-loop ML algorithms that reduce analyst workload and provide decision-making assistance. We propose to develop explainable ML algorithms that summarize large volumes of observable data (intrusion alerts, network & system logs) to discover contextually meaningful patterns from them. The student will conduct fundamental research and explore various learning paradigms to develop actionable explanations from these discovered patterns that are tailored to the operator's expertise. The evaluation of these algorithms will be done under closed-world and open-world settings. For the closed-world setting, a major challenge is the lack of suitable datasets to evaluate ML models. The student will set up a testbed together with our industry collaborators for the collection of intrusion alert datasets. For the open-world setting, the student will deploy these algorithms in real SOC environments to measure the extent of workload reduction experienced by the analysts. In doing so, we aim to develop technologies that are not only novel but also have real-world applications.

The PhD student will be embedded within the Semantics, Cybersecurity, and Services (SCS) group at the University of Twente. The student will have the opportunity to participate in internships and/or collaboration with industry partners under the TUCCR initiative. The SCS group offers a stimulating, supportive, and diverse research environment, as well as plenty of opportunities for personal and professional growth.

Requirements:

• You are a highly motivated and enthusiastic researcher, aspiring to do world-class research and have real-world impact.
• You have a MSc degree with excellent grades in computer science, or similar, with a special emphasis on cybersecurity and/or artificial intelligence; Applications from students who are about to finish their MSc degree studies will be considered as well.
• You are interested in the domain of cybersecurity and explainability;
• You have a solid background in artificial intelligence and/or cybersecurity; Some industrial experience in an incident response role and prior experience with writing scientific papers are of additional advantage.
• You know your way around UNIX/Linux systems; You can code in Python and know your war around sklearn and tensorflow.
• You are curious and interested in learning how things work and how to make them better.
• You have a creative mindset and excellent analytical and communication skills.
• You have good team spirit and like to work in an interdisciplinary and internationally oriented environment;
• You are proficient in English.

Salary Benefits:

• As a PhD candidate at UT, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment;
• The University offers a dynamic ecosystem with enthusiastic colleagues;
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU);
• You will receive a gross monthly salary ranging from € 2.872,- (first year) to € 3.670,- (fourth year);
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;
• The flexibility to work (partially) from home;
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Free access to sports facilities on campus
• A family-friendly institution that offers parental leave (both paid and unpaid);
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;
• We encourage a high degree of responsibility and independence while collaborating with close colleagues, researchers and other staff.

40 hours per week

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