{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:07:03Z","timestamp":1787029623657,"version":"build-2736575974"},"reference-count":22,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,15]],"date-time":"2022-06-15T00:00:00Z","timestamp":1655251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Institute of Information and Communications Technology Planning and Evaluation (IITP)","award":["2021-0-01532"],"award-info":[{"award-number":["2021-0-01532"]}]},{"name":"Institute of Information and Communications Technology Planning and Evaluation (IITP)","award":["2020R1A2B5B01002145"],"award-info":[{"award-number":["2020R1A2B5B01002145"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["2021-0-01532"],"award-info":[{"award-number":["2021-0-01532"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["2020R1A2B5B01002145"],"award-info":[{"award-number":["2020R1A2B5B01002145"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Security and privacy in the Internet of Things (IoT) other significant challenges, primarily because of the vast scale and deployment of IoT networks. Blockchain-based solutions support decentralized protection and privacy. In this study, a private blockchain-based smart home network architecture for estimating intrusion detection empowered with a Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system model is proposed. This study investigates the methodology of RTS-DELM implemented in blockchain-based smart homes to detect any malicious activity. The approach of data fusion and the decision level fusion technique are also implemented to achieve enhanced accuracy. This study examines the numerous key components and features of the smart home network framework more extensively. The Fused RTS-DELM technique achieves a very significant level of stability with a low error rate for any intrusion activity in smart home networks. The simulation findings indicate that this suggested technique successfully optimizes smart home networks for monitoring and detecting harmful or intrusive activities.<\/jats:p>","DOI":"10.3390\/s22124522","type":"journal-article","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T03:01:22Z","timestamp":1655348482000},"page":"4522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["Blockchain-Based Smart Home Networks Security Empowered with Fused Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Muhammad Sajid","family":"Farooq","sequence":"first","affiliation":[{"name":"School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Safiullah","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of IT Convergence Engineering, Gachon University, Seongnam 13120, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5867-8231","authenticated-orcid":false,"given":"Abdur","family":"Rehman","sequence":"additional","affiliation":[{"name":"School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sagheer","family":"Abbas","sequence":"additional","affiliation":[{"name":"School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4854-9935","authenticated-orcid":false,"given":"Muhammad Adnan","family":"Khan","sequence":"additional","affiliation":[{"name":"Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam 13557, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4240-6255","authenticated-orcid":false,"given":"Seong Oun","family":"Hwang","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Gachon University, Seongnam 13120, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,15]]},"reference":[{"key":"ref_1","first-page":"21260","article-title":"Bitcoin: A peer-to-peer electronic cash system","volume":"10","author":"Nakamoto","year":"2008","journal-title":"Decentralized Bus. Rev."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jnca.2019.06.018","article-title":"Blockchain for smart communities: Applications, challenges and opportunities","volume":"144","author":"Aggarwal","year":"2019","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.rser.2018.10.014","article-title":"Blockchain technology in the energy sector: A systematic review of challenges and opportunities","volume":"100","author":"Andoni","year":"2019","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1109\/MNET.011.2000514","article-title":"A machine learning approach for blockchain-based smart home networks security","volume":"35","author":"Khan","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TSMC.2019.2896323","article-title":"Secure and efficient vehicle-to-grid energy trading in cyber physical systems: Integration of blockchain and edge computing","volume":"50","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/MNET.001.1900179","article-title":"Application-aware consensus management for software-defined intelligent blockchain in IoT","volume":"34","author":"Wu","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Sivaraman, V., Gharakheili, H.H., Vishwanath, A., Boreli, R., and Mehani, O. (2015, January 19\u201321). Network-level security and privacy control for smart-home IoT devices. Proceedings of the 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/WiMOB.2015.7347956"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lee, B., Malik, S., Wi, S., and Lee, J.H. (2016). Firmware verification of embedded devices based on a blockchain. International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, Springer.","DOI":"10.1007\/978-3-319-60717-7_6"},{"key":"ref_9","unstructured":"Panwar, N., Sharma, S., Mehrotra, S., Krzywiecki, \u0141., and Venkatasubramanian, N. (2019). Smart home survey on security and privacy. arXiv."},{"key":"ref_10","first-page":"3399","article-title":"Data Fusion-based machine learning architecture for intrusion detection","volume":"70","author":"Khan","year":"2022","journal-title":"Comput. Mater. Contin."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hsu, Y.L., Chou, P.H., Chang, H.C., Lin, S.L., Yang, S.C., Su, H.Y., Chang, C.C., Cheng, Y.S., and Kuo, Y.C. (2017). Design and implementation of a smart home system using multisensor data fusion technology. Sensors, 17.","DOI":"10.3390\/s17071631"},{"key":"ref_12","first-page":"87","article-title":"Privacy preserving blockchain technique to achieve secure and reliable sharing of IoT data","volume":"65","author":"Lydia","year":"2020","journal-title":"Comput. Mater. Contin."},{"key":"ref_13","first-page":"2365","article-title":"Data secure storage mechanism of sensor networks based on blockchain","volume":"65","author":"Wang","year":"2020","journal-title":"Comput. Mater. Contin."},{"key":"ref_14","first-page":"155","article-title":"Trust provision in the internet of things using transversal blockchain networks","volume":"25","author":"Bordel","year":"2019","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref_15","first-page":"153","article-title":"A key recovery system based on password-protected secret sharing in a permissioned blockchain","volume":"65","author":"Ra","year":"2020","journal-title":"Comput. Mater. Contin."},{"key":"ref_16","first-page":"12","article-title":"DeepBlockScheme: A deep learning-based blockchain driven scheme for secure smart city","volume":"11","author":"Singh","year":"2021","journal-title":"Hum. Cent. Comput. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"521","DOI":"10.32604\/csse.2021.014530","article-title":"A storage optimization scheme for blockchain transaction databases","volume":"36","author":"Zhang","year":"2021","journal-title":"Comput. Syst. Sci. Eng."},{"key":"ref_18","first-page":"21","article-title":"Deep learning enabled secure IoT handover authentication for blockchain networks","volume":"11","author":"Salim","year":"2021","journal-title":"Hum. Cent. Comput. Inf. Sci."},{"key":"ref_19","first-page":"446","article-title":"A study on NSL-KDD dataset for intrusion detection system based on classification algorithms","volume":"4","author":"Dhanabal","year":"2015","journal-title":"Int. J. Adv. Res. Comput. Commun. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Tavallaee, M., Bagheri, E., Lu, W., and Ghorbani, A.A. (2009, January 8\u201310). A detailed analysis of the KDD CUP 99 data set. Proceedings of the 2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications, Ottawa, ON, Canada.","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ingre, B., and Yadav, A. (2015, January 2\u20133). Performance analysis of NSL-KDD dataset using ANN. Proceedings of the 2015 International Conference on Signal Processing and Communication Engineering Systems, Guntur, India.","DOI":"10.1109\/SPACES.2015.7058223"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Alshinina, R., and Elleithy, K. (2018, January 17\u201320). A highly accurate machine learning approach for developing wireless sensor network middleware. Proceedings of the 2018 Wireless Telecommunications Symposium (WTS), Phoenix, AZ, USA.","DOI":"10.1109\/WTS.2018.8363955"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4522\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:31:56Z","timestamp":1760139116000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,15]]},"references-count":22,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22124522"],"URL":"https:\/\/doi.org\/10.3390\/s22124522","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,15]]}}}