ZeroKernel: Secure Context-isolated Execution on Commodity GPUs

Cited 3 time in webofscience Cited 0 time in scopus
  • Hit : 260
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKwon, Ohminko
dc.contributor.authorKim, Yonggonko
dc.contributor.authorHuh, Jaehyukko
dc.contributor.authorYoon, Hyunsooko
dc.date.accessioned2021-07-30T05:10:36Z-
dc.date.available2021-07-30T05:10:36Z-
dc.date.created2019-10-18-
dc.date.created2019-10-18-
dc.date.issued2021-07-
dc.identifier.citationIEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, v.18, no.4, pp.1974 - 1988-
dc.identifier.issn1545-5971-
dc.identifier.urihttp://hdl.handle.net/10203/286947-
dc.description.abstractIn the last decade, the dedicated graphics processing unit (GPU) has emerged as an architecture for high-performance computing workloads. Recently, researchers have also focused on the isolation property of a dedicated GPU and suggested GPU-based secure computing environments with several promising applications. However, despite the security analysis conducted by the prior studies, it has been unclear whether a dedicated GPU can be leveraged as a secure processor in the presence of a kernel-privileged attacker. In this paper, we first demonstrate the security of dedicated GPUs through comprehensive studies on context information for GPU execution. The paper shows that a kernel-privileged attacker can manipulate the GPU contexts to redirect memory accesses or execute arbitrary GPU codes on the running GPU kernel. Based on the security analysis, this paper proposes a new on-chip execution model for the dedicated GPU and a novel defense mechanism supporting the security of the on-chip execution. With comprehensive evaluation, the paper assures that the proposed solutions effectively isolate sensitive data in on-chip storages and defend against known attack vectors from a privileged attacker, supporting that the commodity GPUs can be leveraged as a secure processor.-
dc.languageEnglish-
dc.publisherIEEE COMPUTER SOC-
dc.titleZeroKernel: Secure Context-isolated Execution on Commodity GPUs-
dc.typeArticle-
dc.identifier.wosid000671788500034-
dc.identifier.scopusid2-s2.0-85112070970-
dc.type.rimsART-
dc.citation.volume18-
dc.citation.issue4-
dc.citation.beginningpage1974-
dc.citation.endingpage1988-
dc.citation.publicationnameIEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING-
dc.identifier.doi10.1109/TDSC.2019.2946250-
dc.contributor.localauthorHuh, Jaehyuk-
dc.contributor.localauthorYoon, Hyunsoo-
dc.contributor.nonIdAuthorKim, Yonggon-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorGraphics processing units-
dc.subject.keywordAuthorKernel-
dc.subject.keywordAuthorContext-
dc.subject.keywordAuthorSecurity-
dc.subject.keywordAuthorSystem-on-chip-
dc.subject.keywordAuthorRegisters-
dc.subject.keywordAuthorComputer architecture-
dc.subject.keywordAuthorGraphics processors-
dc.subject.keywordAuthorreverse engineering-
dc.subject.keywordAuthorsecurity-
dc.subject.keywordAuthoron-chip execution-
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 3 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0