PhD researcher on local and remote tamper detection on IoT sensor nodes

Leuven - PhD
More than two weeks ago
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For many years, cryptography has been studied in a black-box model, where an adversary could only observe inputs and outputs of a cryptographic function to construct a mathematical model. However, already more than 20 years ago, researchers have shown that this model does not correspond to reality, as an adversary could extract additional (secret) information from the physical implementation of the cryptographic algorithm via side-channel attacks and/or manipulate the internal operations of the algorithm. Therefore, secure implementations of cryptographic algorithms need to include side-channel protection. Moreover, high-end security systems (e.g. ATM machines, payment terminals, security servers, etc.) also have tamper detection on board.

One can expect that IoT sensor nodes will be subject to tampering attacks, as these often will be unattended and easily accessible to an adversary. Therefore, local tamper detection on IoT sensor nodes clearly improves the overall security level. However, deploying conventional tamper detection mechanisms on these nodes is not an option, due to cost reasons. Therefore, the goal of this PhD topic is to design and develop lightweight local tamper detection mechanisms which can be deployed on a resource-constrained IoT sensor node.

A related problem is remote tamper detection, where one wants to verify the integrity of remote sensor nodes. Remote attestation protocols have been proposed as a solution for this research problem. However, similarly as local tamper detection, there is a need for lightweight solutions that can be deployed on IoT nodes. The goal is to design and implement remote tamper detection schemes for IoT, given the resource constraints of the sensor nodes.

Required background: Strong background in electronics engineering or computer science, with an interest in security.

Type of work: analog or digital circuit design, security protocol design, prototype evaluation on ASIC, FPGA or embedded micro-controller (depending direction of the research)

Supervisor: Ingrid Verbauwhede (COSIC – KU Leuven)
Co-supervisor:  Guido Domans (TU Eindhoven)
Supervisors:  Thomas Kallstenius, Marianne Vandecasteele

The reference code for this PhD position is SE1712-07. Mention this reference code on your application form.

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