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dc.contributor.authorAhmadi-Assalemi, Gabriela
dc.contributor.authoral-Khateeb, Haider
dc.contributor.authorEpiphaniou, Gregory
dc.contributor.authorCosson, Jon
dc.contributor.authorPillai, Prashant
dc.date.accessioned2019-04-18T09:47:29Z
dc.date.available2019-04-18T09:47:29Z
dc.date.issued2019-04-11
dc.identifier.citationAhmadi-Assalemi, G., Al-Khateeb, H. M., Epiphaniou, G., Cosson, J. and Pillai, P. (2019) Federated blockchain-based tracking and liability attribution framework for employees and cyber-physical objects in a smart workplace. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)en
dc.identifier.isbn9781538670026
dc.identifier.doi10.1109/ICGS3.2019.8688297
dc.identifier.urihttp://hdl.handle.net/2436/622302
dc.description.abstractThe systematic integration of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) into the supply chain to increase operational efficiency and quality has also introduced new complexities to the threat landscape. The myriad of sensors could increase data collection capabilities for businesses to facilitate process automation aided by Artificial Intelligence (AI) but without adopting an appropriate Security-by-Design framework, threat detection and response are destined to fail. The emerging concept of Smart Workplace incorporates many CPS (e.g. Robots and Drones) to execute tasks alongside Employees both of which can be exploited as Insider Threats. We introduce and discuss forensic-readiness, liability attribution and the ability to track moving Smart SPS Objects to support modern Digital Forensics and Incident Response (DFIR) within a defence-in-depth strategy. We present a framework to facilitate the tracking of object behaviour within Smart Controlled Business Environments (SCBE) to support resilience by enabling proactive insider threat detection. Several components of the framework were piloted in a company to discuss a real-life case study and demonstrate anomaly detection and the emerging of behavioural patterns according to objects' movement with relation to their job role, workspace position and nearest entry or exit. The empirical data was collected from a Bluetooth-based Proximity Monitoring Solution. Furthermore, a key strength of the framework is a federated Blockchain (BC) model to achieve forensic-readiness by establishing a digital Chain-of-Custody (CoC) and a collaborative environment for CPS to qualify as Digital Witnesses (DW) to support post-incident investigations.en
dc.formatapplication/PDFen
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttps://ieeexplore.ieee.org/document/8688297en
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectinsider threaten
dc.subjectanomaly detectionen
dc.subjectdigital witnessen
dc.subjectIoTen
dc.subjectsmart buildingen
dc.subjectsmart cityen
dc.subjectmonitoringen
dc.subjectauthenticityen
dc.subjectnon-repudiationen
dc.titleFederated blockchain-based tracking and liability attribution framework for employees and cyber-physical objects in a smart workplaceen
dc.typeConference contributionen
dc.conference.name2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)
pubs.finish-date2019-01-18
pubs.place-of-publicationLondon, England
pubs.start-date2019-01-16
dc.identifier.eisbn9781538670019
refterms.dateFOA2019-04-18T09:47:29Z


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Attribution 3.0 United States
Except where otherwise noted, this item's license is described as Attribution 3.0 United States