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The Department of Computing Science is now looking for a Doctoral student in cybersecurity with a focus on DDoS attacks and defense strategies for the cloud-edge continuum.

The department has been growing rapidly in recent years. An inclusive and participatory environment are key elements in our growth. The 60 doctoral students within the department are a diverse group from different nationalities, backgrounds, and fields. We offer very good employment conditions, and administrative and technical support, among other benefits. See more information at:

PhD Scholarships at the Institute of Science and Technology, Austria (ISTA)

The multilayer cloud-edge continuum poses several challenges, such as smart placement, workload prediction and relocation, energy usage prediction, and security for critical applications and infrastructures. Distributed Denial of Service (DDoS) is one of the critical threats that disrupt the benign services provided by servers based on distributed resources across the Continuum. The key security challenges faced by existing methods, particularly when it comes to DDoS attacks and defense strategies for the cloud-edge continuum. Challenges include unlimited reassignment of resources for microservices under attack, slow reaction time, lack of methods for validation in real environments, and weak kernel architecture in virtualized instances. Moreover, understanding the underlying differences between occasional benign load spikes and massive or stealthy DDoS attacks is unexplored in the cloud-edge continuum. Where machine learning (ML) is deployed both for optimizing performance (benign adaptation) and attack detection (DDoS), security researchers face the problem of considering the compound effect of each ML component’s uncertainty.

This project envisions exploring time-variant learning algorithms to understand the inherent differences between benign and malicious load patterns across the cloud-edge continuum, in particular, DDoS attacks and defence strategies. The plan will explicitly model uncertainty and investigate which protocols, service functions, and dependency chains characterize benign load variations and which ones must be treated as attacks. The impact of modelled attacks will then be assessed in cloud-edge continuum scenarios, where adversaries aim, for example, resource-sharing attacks. This project will further investigate the developed defence methods with three different threat models: stealthy, dynamic, and collateral-damage caused across the continuum, and will measure the overhead of each defence strategy itself in terms of resource use and recovery time.

The PhD Student will contribute to the Autonomous Distributed Systems (ADS) Lab within the Department of Computing Science. The ADS Lab is an internationally leading research group with a focus from distributed AI to autonomous resource management and modern. The Lab currently comprises over 20 experienced and world-leading research colleagues from more than 10 different countries. For more information, see

The position is funded by The Knut and Alice Wallenberg Foundation through The Wallenberg AI, Autonomous Systems and Software Program (WASP) within a new ambitious NEST project AIR2: AI for Attack Identification, Response and Recovery in collaboration with leading research groups on AI and Cybersecurity from KTH and Linköping University. WASP is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems, and software for the benefit of the Swedish industry. Read more:

The graduate school within WASP is dedicated to providing the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems, and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between Ph.D. students, researchers, and industry. Read more:

The general admission requirements for doctoral studies are a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad or equivalent qualifications. To fulfill the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed at least 90 ECTS credits in computing science.  Applicants who otherwise have acquired skills that are deemed equivalent are also eligible.

Additional requirements are to have solid foundations in the theory and algorithms of project-related areas, such as machine learning, edge computing, distributed systems, and excellent programming ability. Experience in broad competence areas, including developing machine learning algorithms, statistical analysis methods, distributed learning, and discrete optimization, is desirable. Additionally, experience in software development, configuring experimental testbeds, and developing simulations is a merit. Very good knowledge of the English language is an important requirement, we value strong communication skills and studies will be predominantly conducted in English.

Important personal qualities are creativity, an inquisitive mind, and the ability to work independently as well as with others, either in a group or outside. You are also expected to have a willingness to develop yourself continuously to become a competent researcher.

The position provides you with the opportunity to pursue PhD studies in Computing Science for four years, with the goal of achieving the degree of Doctor in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of the time), it may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly, resulting in a maximum of five years.

The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed.

The expected starting date is by agreement.

Applications must be submitted electronically using the e-recruitment system of Umeå University.

A complete application should contain the following documents:

  • A cover letter including a description of your research interests, your reasons to apply for the position, and your contact information. Generic cover letters, or applications without cover letter will not be considered.
  • A curriculum vitae.
  • Reprints/copies of completed BSc and/or MSc theses and other relevant publications, if any.
  • Copies of degree certificates, including documentation of completed academic courses and obtained grades.
  • Contact information for three reference persons.
  • Documentation and description of other relevant experiences or competences.

The application must be written in English or Swedish. Attached documents must be in pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than 15 January 2024.

Selected applicants will be invited for an interview round, including a computing and programming assignment.

The Department of Computing Science values gender diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position.

For additional information, please contact: Assist. Prof. Monowar Bhuyan ( or Prof. Erik Elmroth (

We look forward to receiving your application!

Application deadline: 15- January-2024

Online Application portal: here

Official Website: Click here

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