Parameter-Invariant Monitor Design for Cyber Physical Systems

Simple item page
dc.contributor.authorWeimer, James
dc.contributor.authorIvanov, Radoslav
dc.contributor.authorChen, Sanjian
dc.contributor.authorRoederer, Alexander
dc.contributor.authorSokolsky, Oleg
dc.contributor.authorLee, Insup
dc.contributor.authorWeimer, James
dc.contributor.authorIvanov, Radoslav
dc.contributor.authorChen, Sanjian
dc.contributor.authorRoederer, Alexander
dc.contributor.authorSokolsky, Oleg
dc.contributor.authorLee, Insup
dc.date2023-05-17T20:19:08.000
dc.date.accessioned2023-05-22T12:51:39Z
dc.date.available2023-05-22T12:51:39Z
dc.date.issued2018-01-01
dc.date.submitted2018-07-02T11:07:28-07:00
dc.description.abstractThe tight interaction between information technology and the physical world inherent in Cyber-Physical Systems (CPS) can challenge traditional approaches for monitoring safety and security. Data collected for robust CPS monitoring is often sparse and may lack rich training data describing critical events/attacks. Moreover, CPS often operate in diverse environments that can have significant inter/intra-system variability. Furthermore, CPS monitors that are not robust to data sparsity and inter/intra-system variability may result in inconsistent performance and may not be trusted for monitoring safety and security. Towards overcoming these challenges, this paper presents recent work on the design of parameter-invariant (PAIN) monitors for CPS. PAIN monitors are designed such that unknown events and system variability minimally affect the monitor performance. This work describes how PAIN designs can achieve a constant false alarm rate (CFAR) in the presence of data sparsity and intra/inter system variance in real-world CPS. To demonstrate the design of PAIN monitors for safety monitoring in CPS with different types of dynamics, we consider systems with networked dynamics, linear-time invariant dynamics, and hybrid dynamics that are discussed through case studies for building actuator fault detection, meal detection in type I diabetes, and detecting hypoxia caused by pulmonary shunts in infants. In all applications, the PAIN monitor is shown to have (significantly) less variance in monitoring performance and (often) outperforms other competing approaches in the literature. Finally, an initial application of PAIN monitoring for CPS security is presented along with challenges and research directions for future security monitoring deployments.
dc.description.comments<p>Proceedings of the IEEE, 106 (1), Jan 2018. pp. 71-92.</p>
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/6926
dc.legacy.articleid1893
dc.legacy.fields10.1109/JPROC.2017.2723847
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1893&amp;context=cis_papers&amp;unstamped=1
dc.rights<p>©2018 IEEE</p>
dc.source.beginpage71
dc.source.endpage92
dc.source.issue846
dc.source.issue1
dc.source.journalDepartmental Papers (CIS)
dc.source.journaltitleProceedings of the IEEE
dc.source.peerreviewedtrue
dc.source.statuspublished
dc.source.volume106
dc.subject.otherCPS Medical
dc.subject.otherCPS Theory
dc.subject.otherComputer Engineering
dc.subject.otherComputer Sciences
dc.titleParameter-Invariant Monitor Design for Cyber Physical Systems
dc.typeArticle
digcom.contributor.authorisAuthorOfPublication|email:weimerj@cis.upenn.edu|institution:University of Pennsylvania|Weimer, James
digcom.contributor.authorisAuthorOfPublication|email:rivanov@cis.upenn.edu|institution:University of Pennsylvania|Ivanov, Radoslav
digcom.contributor.authorisAuthorOfPublication|email:sanjian@cis.upenn.edu|institution:University of Pennsylvania|Chen, Sanjian
digcom.contributor.authorisAuthorOfPublication|email:roederer@cis.upenn.edu|institution:University of Pennsylvania|Roederer, Alexander
digcom.contributor.authorisAuthorOfPublication|email:sokolsky@cis.upenn.edu|institution:University of Pennsylvania|Sokolsky, Oleg
digcom.contributor.authorisAuthorOfPublication|email:lee@cis.upenn.edu|institution:University of Pennsylvania|Lee, Insup
digcom.identifiercis_papers/846
digcom.identifier.contextkey12428820
digcom.identifier.submissionpathcis_papers/846
digcom.typearticle
dspace.entity.typePublication
relation.isAuthorOfPublication03b71a10-c612-4bb1-8a80-1463efee44c5
relation.isAuthorOfPublicationf7d2d91b-2a20-4596-9649-43b222476db4
relation.isAuthorOfPublication07085e59-bb6d-4302-a53b-b7fbded24b2b
relation.isAuthorOfPublicationdf942cc0-3cfd-4043-b071-3427fe74d1a4
relation.isAuthorOfPublication35e1b18e-15fe-4438-be3b-84593f70a40a
relation.isAuthorOfPublication45a9eed5-3211-4c36-b40d-6394302dfdce
relation.isAuthorOfPublication.latestForDiscovery03b71a10-c612-4bb1-8a80-1463efee44c5
upenn.schoolDepartmentCenterDepartmental Papers (CIS)
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
IEee_main_3.pdf
Size:
4.97 MB
Format:
Adobe Portable Document Format
Download
Collection
Articles