Ítem
Solo Metadatos

NoisePrint: Attack detection using sensor and process noise fingerprint in cyber physical systems

Mostrar el registro sencillo de la publicación
dc.creatorAhmed C.M.spa
dc.creatorQadeer R.spa
dc.creatorOchoa M.spa
dc.creatorMurguia C.spa
dc.creatorZhou J.spa
dc.creatorMathur A.P.spa
dc.creatorRuths J.spa
dc.date.accessioned2020-05-25T23:59:30Z
dc.date.available2020-05-25T23:59:30Z
dc.date.created2018spa
dc.description.abstractAn attack detection scheme is proposed to detect data integrity attacks on sensors in Cyber-Physical Systems (CPSs). A combined fingerprint for sensor and process noise is created during the normal operation of the system. Under sensor spoofing attack, noise pattern deviates from the fingerprinted pattern enabling the proposed scheme to detect attacks. To extract the noise (difference between expected and observed value) a representative model of the system is derived. A Kalman filter is used for the purpose of state estimation. By subtracting the state estimates from the real system states, a residual vector is obtained. It is shown that in steady state the residual vector is a function of process and sensor noise. A set of time domain and frequency domain features is extracted from the residual vector. Feature set is provided to a machine learning algorithm to identify the sensor and process. Experiments are performed on two testbeds, a real-world water treatment (SWaT) facility and a water distribution (WADI) testbed. A class of zero-alarm attacks, designed for statistical detectors on SWaT are detected by the proposed scheme. It is shown that a multitude of sensors can be uniquely identified with accuracy higher than 90% based on the noise fingerprint. © 2018 Association for Computing Machinery.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1145/3196494.3196532
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/23055
dc.language.isoengspa
dc.publisherAssociation for Computing Machinery, Incspa
dc.relation.citationEndPage497
dc.relation.citationStartPage483
dc.relation.citationTitleASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security
dc.relation.ispartofASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security,(2018); pp. 483-497spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85049213203&doi=10.1145%2f3196494.3196532&partnerID=40&md5=d6fe0f65b66b694e6f50d8b69f12ce63spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordActuatorsspa
dc.subject.keywordCyber Physical Systemspa
dc.subject.keywordEmbedded systemsspa
dc.subject.keywordFrequency domain analysisspa
dc.subject.keywordLearning algorithmsspa
dc.subject.keywordLearning systemsspa
dc.subject.keywordSensorsspa
dc.subject.keywordState estimationspa
dc.subject.keywordTestbedsspa
dc.subject.keywordWater supply systemsspa
dc.subject.keywordWater treatmentspa
dc.subject.keywordCPS/ICS Securityspa
dc.subject.keywordCyber physical systems (cpss)spa
dc.subject.keywordData integrity attacksspa
dc.subject.keywordDevice fingerprintingspa
dc.subject.keywordFrequency domainsspa
dc.subject.keywordPhysical attacksspa
dc.subject.keywordSecurityspa
dc.subject.keywordWater distributionsspa
dc.subject.keywordPalmprint recognitionspa
dc.subject.keywordActuatorsspa
dc.subject.keywordCPS/ICS Securityspa
dc.subject.keywordCyber Physical Systemsspa
dc.subject.keywordDevice Fingerprintingspa
dc.subject.keywordPhysical Attacksspa
dc.subject.keywordSecurityspa
dc.subject.keywordSensorsspa
dc.titleNoisePrint: Attack detection using sensor and process noise fingerprint in cyber physical systemsspa
dc.typeconferenceObjecteng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaDocumento de conferenciaspa
Archivos
Colecciones
Artículos