Supporting operating system kernel data disambiguation using points-to analysis

Authors:
Amani S. Ibrahim;John Grundy;James Hamlyn-Harris;Mohamed Almorsy
Affiliations:
Swinburne University of Technology, Australia;Swinburne University of Technology, Australia;Swinburne University of Technology, Australia;Swinburne University of Technology, Australia
Venue:
Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
Year:
2012

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Abstract

Generic pointers scattered around operating system (OS) kernels make the kernel data layout ambiguous. This limits current kernel integrity checking research to covering a small fraction of kernel data. Hence, there is a great need to obtain an accurate kernel data definition that resolves generic pointer ambiguities, in order to formulate a set of constraints between structures to support precise integrity checking. In this paper, we present KDD, a new tool for systematically generating a sound kernel data definition for any C-based OS e.g. Windows and Linux, without any prior knowledge of the kernel data layout. KDD performs static points-to analysis on the kernel’s source code to infer the appropriate candidate types for generic pointers. We implemented a prototype of KDD and evaluated it to prove its scalability and effectiveness.