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dc.contributor.authorMergendahl, Samuel
dc.contributor.authorFickas, Stephen
dc.contributor.authorNorris, Boyana
dc.contributor.authorSkowyra, Richard
dc.date.accessioned2025-01-28T14:54:13Z
dc.date.available2025-01-28T14:54:13Z
dc.date.issued2024-12-02
dc.identifier.isbn979-8-4007-0636-3
dc.identifier.urihttps://hdl.handle.net/1721.1/158086
dc.descriptionCCS ’24, October 14–18, 2024, Salt Lake City, UT, USAen_US
dc.description.abstractA μ-kernel is an operating system (OS) paradigm that facilitates a strong cybersecurity posture for embedded systems. Unlike a monolithic OS such as Linux, a μ-kernel reduces overall system privilege by deploying most OS functionality within isolated, userspace protection domains. Moreover, a μ-kernel ensures confidentiality and integrity between protection domains (i.e., spatial isolation), and offers timing predictability for real-time tasks in mixed-criticality systems (i.e., temporal isolation). One popular μ-kernel is seL4 which offers extensive formal guarantees of implementation correctness and flexible temporal budgeting mechanisms. However, we show that an untrusted protection domain on a μ-kernel can abuse service requests to other protection domains in order to corrode system availability. We generalize this denial-of-service (DoS) attack strategy as Manipulative Interference Attacks (MIAs) and introduce techniques to efficiently identify instances of MIAs within a configured system. Specifically, we propose a novel hybrid approach that first leverages static analysis to identify software components with influenceable execution times, and second, uses an automatically generated model-based analysis to determine which compromised protection domains can manipulate the influenceable components and trigger MIAs. We investigate the risk of MIAs in several representative system examples including the seL4 Microkit, as well as a case study of seL4 software artifacts from the DARPA Cyber Assured Systems Engineering (CASE) program. In particular, we demonstrate that our analysis is efficient enough to discover practical instances of MIAs in real-world systems.en_US
dc.publisherACM|Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Securityen_US
dc.relation.isversionofhttps://doi.org/10.1145/3658644.3690246en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleManipulative Interference Attacksen_US
dc.typeArticleen_US
dc.identifier.citationMergendahl, Samuel, Fickas, Stephen, Norris, Boyana and Skowyra, Richard. 2024. "Manipulative Interference Attacks."
dc.contributor.departmentLincoln Laboratoryen_US
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2025-01-01T08:49:35Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2025-01-01T08:49:35Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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