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PhD student in cyber security for the Internet of Things

Position Description
RISE offers this PhD position within the scope of the InSecTT (Intelligent Secure Trustable Things) project, a pan-European effort with 52 partners from 12 countries. The position has a specialization in network security and machine learning. The main goal in the InSecTT project is to provide intelligent, secure and trustworthy systems for industrial applications, in particular for the manufacturing industry. To achieve this goal, a combination of different technologies and techniques such as Artificial Intelligence (AI), Machine Learning (ML), cybersecurity and Internet of Things (IoT) are considered in the project.

Historically, industrial devices were isolated and air-gapped without connections to to the outside world. With the emergence of IIoT network, it's possible that what was previously a separate network for operational technology, responsible for monitoring and controlling physical devices such as pumps and valves, could be connected to the rest of the information technology network. While this can have benefits, the risk is that critical software that once ran in its own secure environment is now linked to a broader network, creating an easier target for hackers.

Intrusion Detection Solutions (IDS) for IIoT need to be customized to the nature of the devices.  Small devices with limited resources need a solution tailored to the types of attacks they are likely to experience without overwhelming the limited memory and computing resources of the device.  At the same time, the sophistication of the IDS must scale up to support more powerful gateways and control systems. The key is to monitor for, detect, and quickly report anomalous situations. This requires integration with a security management system where IDS events can be sent and viewed to determine if the anomalous events indicate a cyber-attack. Can we use machine learning to differentiate the attack message flows, classify attacks and eventually stop them? Can we allow the learning algorithm to understand new kind of attacks and grow in intelligence? Can we use a multi-agent approach? There is a need for an intelligent IDS that could detect different and dynamic attack patterns, and this research will develop such a system, providing answers to these and related questions.

The project will be performed in close cooperation with other partners in the project, which include large industries, research institutes and universities, as well as small and medium-sized enterprises from both Sweden and other European countries. The doctoral program will be hosted by Mälardalen University, campus Västerås.

About the position
In this role you will:

  • Be part of a team that conducts applied research together with creative colleagues and in collaboration with both industry and the public sector;
  • Develop methods and bring them into different application areas, in particular within the manufacturing industries;
  • Be involved in planning and management of projects;
  • Advocate research findings to diverse audiences through best suitable communication means: inspirational talks, demos, videos, presentations, and articles.

This is a full time position located in Västerås.  The start date is as agreed between the candidate and RISE. 

Minimum qualifications:

  • Master's Degree (at least 240 credits) in computer science or computer networks or corresponding qualifications, from a recognized academic institution;
  • Have experience or deep interest in network security, machine learning and artificial intelligence algorithms.

Preferred qualifications:
As a candidate you should

  • Have a background and experience in operations research, simulation, statistics, algorithms;
  • Be curious, goal-oriented, flexible, ambitious and communicative;
  • Be skilled in presenting and documenting your work in English, i.e. to describe the problem, the solution and the approach in an understandable manner;
  • Have excellent programming skills (e.g. C, C++, Java and Python);
  • Be able to read and understand state of the art research in network security and machine learning

Welcome with your application
Applications should include a short CV (max 3 pages), one-page cover letter, complete transcript of records, and any letters of recommendation. The application should also include information on relevant previous work, industry experiences, bachelor's or master's thesis, scientific papers, or even outline of a thesis under submission. Incomplete applications will not be considered. The final date to submit your application is September 15th, 2020.

For more information contact: Dr. Ali Balador, +46 73 053 21 33. 

Our union representatives are: Linda Ikatti, Unionen, +46 10-516 51 61 and Ingemar Petermann, Sveriges Ingenjörer, +46 10-228 41 22. 

Calls from external recruitment companies and sales persons are kindly declined as we rule under the Public Procurement Act.

PhD, applied research, cyber security, IoT, InSecTT, computer science, RISE, Västerås

Om jobbet

Ort

Västerås

Anställningsform

Visstidsanställning längre än 6 månader

Job type

Forskning - tex forskare/postdoktorer/doktorander

Kontaktperson

Dr. Ali Balador
+46 73 053 21 33

Referensnummer

2020/187

Sista ansökningsdag

2020-09-15

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