PhD: Mining Internet Payment Development Logs for Reliability & Security

21 dagen geleden

Arbeidsvoorwaarden

Standplaats:
Landelijk / geen vaste standplaats
Dienstverband:
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 uur
Salarisindicatie:
€ 2801 per maand
Opleidingsniveau:
WO

developing algorithms for learning behavioural models (state machines) in real-time from log-lines

Functieomschrijving

Within the recently granted NWO MIPL project, you will work closely together with Dr. Sicco Verwer and Prof. Arie van Deursen to develop novel algorithms for learning behavioural models (state machines) in real-time from vast volumes of software log-lines and methods for analysing these models. You will improve the security of a distributed payment system by inferring probabilistic state machine models from system interactions and log data. Building on technology for inferring complex communication protocols such as SIP, TLS, and EMV, you will develop new algorithms to infer behavioural models from massive logs of Adyen's payment system (https://www.adyen.com). Half of your time will be spent at Adyen in Amsterdam, working closely together with their developers and analysts in order to find anomalies and potential security issues. Your research will be used by software engineering experts to radically innovate the way log-lines are written and used. Together, you will think of new possibilities and evaluate their impact on log-line usability. You will join a team of experts in state machine learning technology, with applications ranging from reversing communication protocols to detecting malware.

Functie-eisen

We invite applicants who meet the following requirements:
• You have an MSc degree in computer science, artificial intelligence, or mathematics.
• You have excellent programming skills and a keen interest in cyber security or machine learning, preferably both.
• You have a good understanding of spoken and written English.
• Published work in software engineering, intrusion detection, reverse-engineering, machine learning, or data (stream) mining is a plus.

Conditions

The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit graduateschool.tudelft.nl/ for more information.

For more information about this position, please contact Sicco Verwer, phone: +31 (0)15-2788435, e-mail: s.e.verwer@tudelft.nl. To apply, please e-mail a detailed CV along with a letter of application by 1 June 2017 to E.C.L. Turlings, Hr-eemcs@tudelft.nl. When applying for this position, please refer to vacancy number EWI2016-39.

Additional information

Sicco Verwer
+31 (0)15-2788435
s.e.verwer@tudelft.nl

Technische Universiteit Delft

Bedrijfsomschrijving

Delft University of Technology (the TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. The TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At the TU Delft you will work in an environment where technical sciences and society converge. The TU Delft comprises eight faculties, unique laboratories, research institutes and schools. Electrical Engineering, Mathematics & Computer Science The Department of Intelligent Systems (INSY) conducts research on processing, interpretation and securing of data to enable humans and machines to deal with the increasing volume and complexity of data and communication. The cybersecurity section in INSY is a collaborative effort with the Technology, Policy, and Management (TPM) faculty to solve complex security issues from both a computer scientist’s and a policy maker's viewpoint. The TU Delft Software Engineering Research Group (SERG) aims at understanding how people build and evolve software and focuses on building tools to improve this practice.

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