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)

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 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
Pages234-237
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventAutomated Software Engineering Conference 2012 - Atlantic Congress Hotel, Essen, Germany
Duration: 3 Sep 20127 Sep 2012
Conference number: 27th
http://www.ase-conferences.org/ase/past/ase2012/index.html (Conference website)
https://dl.acm.org/doi/proceedings/10.1145/2351676 (Proceedings)

Conference

ConferenceAutomated Software Engineering Conference 2012
Abbreviated titleASE 2012
CountryGermany
CityEssen
Period3/09/127/09/12
OtherIEEE/ACM International Conference on Automated Software Engineering, ASE 2012
Internet address

Keywords

  • Points-to analysis
  • Systematic kernel data integrity checking

Cite this

Ibrahim, A. S., Grundy, J., Hamlyn-Harris, J., & Almorsy, M. (2012). Supporting operating system kernel data disambiguation using points-to analysis. In 2012 27th IEEE/ACM International Conference on Automated Software Engineering, ASE 2012 - Proceedings (pp. 234-237) https://doi.org/10.1145/2351676.2351710