Supporting operating system kernel data disambiguation using points-to analysis

Amani S. Ibrahim, John Grundy, James Hamlyn-Harris, Mohamed Almorsy

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)


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 Cbased 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.

Original languageEnglish
Title of host publication2012 27th IEEE/ACM International Conference on Automated Software Engineering, ASE 2012 - Proceedings
Number of pages4
Publication statusPublished - 2012
Externally publishedYes
EventAutomated Software Engineering Conference 2012 - Atlantic Congress Hotel, Essen, Germany
Duration: 3 Sept 20127 Sept 2012
Conference number: 27th (Conference website) (Proceedings)


ConferenceAutomated Software Engineering Conference 2012
Abbreviated titleASE 2012
OtherIEEE/ACM International Conference on Automated Software Engineering, ASE 2012
Internet address


  • Points-to analysis
  • Systematic kernel data integrity checking

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