Muen on ARM - an Evaluation

Loosli, David (2017) Muen on ARM - an Evaluation. Student Research Project thesis, HSR Hochschule für Technik Rapperswil.

[thumbnail of HS 2017 2018-SA-EP-Loosli-Untersuchung der Portierung des Muen Separation Kernel auf A.pdf]
Preview
Text
HS 2017 2018-SA-EP-Loosli-Untersuchung der Portierung des Muen Separation Kernel auf A.pdf - Supplemental Material

Download (5MB) | Preview

Abstract

The Muen Separation Kernel (SK) is a specialised microkernel developed as a platform for high-security systems at the University of Applied Sciences Rapperswil (HSR). Muen ensures a strict and reliable isolation of components and protects critical security functions against unreliable software running on the same physical system. The programming language SPARK 2014 is used to achieve a particularly high degree of trustworthiness. The Muen SK was developed specifically for the Intel x86/64 architecture and uses the Intel VT-x and VT-d technology to separate the components.

This feasibility study investigates the ARMv8-A architecture and in particular the AArch64 Virtualization Extensions introduced with the latest ARM architecture and evaluates how this technology could be used for porting the Muen SK to ARM. In order to be able to achieve this, the mechanisms used by Muen SK are first examined in detail. Based on this investigation, the requirements for a target processor architecture are derived and compared with the features provided by the ARMv8-A architecture. Since the target hardware platform for this study is the Raspberry Pi 3, the requirements declared as „implementation defined“ by the ARM documentation are finally assessed with respect to this System on Chip designed by the Raspberry Pi Foundation.

Item Type: Thesis (Student Research Project)
Subjects: Topics > Software > Testing and Simulation
Area of Application > Security
Technologies > Virtualization
Divisions: Bachelor of Science FHO in Informatik > Student Research Project
Depositing User: OST Deposit User
Contributors:
Contribution
Name
Email
Thesis advisor
Steffen, Andreas
UNSPECIFIED
Date Deposited: 10 Apr 2018 09:15
Last Modified: 10 Apr 2018 09:15
URI: https://eprints.ost.ch/id/eprint/622

Actions (login required)

View Item
View Item