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Abstrakty
Design of distributed complex systems raises several important challenges, such as: confidentiality, data authentication and integrity, semantic contextual knowledge sharing, as well as common and intelligible understanding of the environment. Among the many challenges are semantic heterogeneity that occurs during dynamic knowledge extraction and authorization decisions which need to be taken when a resource is Accessem in an open, dynamic environment. Blockchain offers the tools to protect sensitive personal data and solve reliability issues by providing a secure communication architecture. However, setting-up blockchain-based applications comes with many challenges, including processing and fusing heterogeneous information from various sources. The ontology model explored in this paper relies on a unified knowledge representation method and thus is the backbone of a distributed system aiming to tackle semantic heterogeneity and to model decentralized management of Access control authorizations.We intertwine the blockchain technology with an ontological model to enhance knowledge management processes for distributed systems. Therefore, rather than reling on the mediation of a third party, the approach enhances autonomous decision-making. The proposed approach collects data generated by sensors into higher-level abstraction using n-ary hierarchical structures to describe entities and actions. Moreover, the proposed semantic architecture relies on hyperledger fabric to ensure the checking and authentication of knowledge integrity while preserving privacy.
Rocznik
Tom
Strony
75--83
Opis fizyczny
Bibliogr. 22 poz., rys.
Twórcy
autor
- Faculty of Mathematics and Informatics, University of Mohamed, El Bachir EL Ibrahimi, Algeria
autor
- Laboratory of Images, Signals and Intelligent Systems, University of Paris-Est, France
Bibliografia
- [1] A. Brunete, E. Gambao, M. Hernando, and R. Cedazo, “Smart Assistive Architecture for the Integration of IoT Devices, Robotic Systems, and Multimodal Interfaces in Healthcare Environments”, J. Sensors, vol. 21, no. 6, 2021 (DOI:10.3390/s21062212).
- [2] J.M. Byeong, S.K. Sonya, and C. JongSuk, “Organizing the Internet of Robotic Things: The Effect of Organization Structure on Users’ Evaluation and Compliance toward IoRT Service Platform”, IROS, pp. 628–629, 2020 (DOI:10.1109/IROS45743.2020.9340834).
- [3] A. Kumari and S. Tanwar, “Secure data analytics for smart grid systems in a sustainable smart city: Challenges, solutions, and future directions”, J. Sustainable Computing: Informatics and Systems, vol. 28, 2020 (DOI:10.1016/j.suscom.2020.100427).
- [4] B. Bhushan, P. Sinha, K.M. Sagayam, and J.A. Onesimu, “Untangling blockchain technology: A survey on state of the art, security threats, privacy services, applications and future research directions”, J. Computers Electrical Engineering, vol. 90, 2021 (DOI:10.1016/j.compeleceng.2020.106897).
- [5] S. Pal, A. Dorri, and E. Jurdak, “Blockchain for IoT Access Control: Recent Trends and Future Research Directions”, CoRR, 2021 (DOI:10.1016/j.jnca.2022.103371).
- [6] H.C. Chen, “Collaboration IoT–Based RBAC with Trust Evaluation Algorithm Model for Massive IoT Integrated Application”, J. Mob. Networks Appl, vol. 24, pp. 839–852, 2021 (DOI: 10.1007/s11036-018-1085-0).
- [7] S. Christos, E.P. Kostas, K. Byung-Gyu, and G. Brij, “Secure integration of IoT and Cloud Computing”, J. Future Generation Computer System, vol. 78, pp. 964–975, 2018 (DOI:10.1016/j.future.2016.11.031).
- [8] https://www.hyperledger.org/use/fabric
- [9] C. Iozgu and D. Yilmazer, “Improving privacy in health care with an ontology–based provenance management system”, J. Expert Systems, Special Issue: eHealth and Staying Smarter, vol. 37, 2020 (DOI:10.1111/exsy.12427).
- [10] P. Gonzalez-Gil, J.A. Martinez, and A.F. Skarmeta, “Lightweight Data-Security Ontology for IoT”, J. Sensors, vol. 20, 2020 (DOI:10.3390/s20030801).
- [11] L. Sabri and A. Boubetra, “Narrative Knowledge Representation and Blockchain: A Symbiotic Relationship”, Advanced Information Networking and Applications Proceedings of the 34th International Conference on Advanced Information Networking and Applications (AINA–2020), pp. 320–332, 2020 (DOI: 10.1007/978-3-030-44041-1_30).
- [12] B. Sejdiu, I. Florije, and L. Ahmedi, “A Management Model of Real-time Integrated Semantic Annotations to the Sensor Stream Data for the IoT”, WEBIST, pp. 59–66, 2020 (DOI:10.5220/0010111500590066).
- [13] G.P. Zarri, “A knowledge representation tool for encoding the ‘meaning’ of complex narrative texts”, Natural Language Engineering, vol. 3, pp. 231–253, 1997 (DOI: 10.1017/S1351324997001794).
- [14] A. Reyna, M. Cristian, J. Chen, E. Soler, and M. Diaz, “On blockchain and its integration with IoT. Challenges and opportunities”, J. Future Generation Computer Systems, vol. 388, pp. 173–190, 2018 (DOI:10.1016/j.future.2018.05.046).
- [15] F. Tschorsch and B. Scheuermann, “Bitcoin and beyond: a technical survey on decentralized digital currencies”, J. IEEE Communications Surveys & Tutorials, vol. 18, pp. 2084–2123, 2016 (DOI:10.1109/COMST.2016.2535718).
- [16] D.D. Fiergbor, “Blockchain Technology in Fund Management”, Communications in Computer and Information Science; Springer, vol. 899, pp. 310–319, 2018 (DOI: 10.1007/978-981-13-2035-4_27).
- [17] https://www.ibm.com/topics/hyperledger
- [18] https://protege.stanford.edu/
- [19] F. Baader, D.L. McGuinness, D. Nardi, and P.F. Patel–Schneider, “The Description Logic Handbook: Theory, implementation, and applications”, Cambridge University Press, 2010 (DOI:10.1017/CBO9780511711787).
- [20] J. Kwapień and S. Drożdż, “Physical approach to complex systems”, Physics Reports, vol. 515, no. 34, pp. 115–226, 2012 (DOI:10.1016/j.physrep.2012.01.007).
- [21] Y. Li, L. Qiao, and Z. Lv, “An Optimized Byzantine Fault Tolerance Algorithm for Consortium Blockchain”, Peer-to-Peer Netw. Appl, vol. 18, pp. 2826–2839, 2021 (dpi: 10.1007/s12083-021-01103-8).
- [22] D. Hooda and R. Rani, “Ontology driven human activity recognition in heterogeneous sensor measurements”, J. Ambient Intelligence and Humanized Computing, vol. 11, pp. 5947–5960, 2020 (DOI:10.1007/s12652-020-01835-0).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-15677006-b0e7-4dcf-a70a-7d8fc3e426fc