{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T16:54:10Z","timestamp":1783529650026,"version":"3.55.0"},"reference-count":142,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T00:00:00Z","timestamp":1683763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The Internet of Things (IoT) continues to attract attention in the context of computational resource growth. Various disciplines and fields have begun to employ IoT integration technologies in order to enable smart applications. The main difficulty in supporting industrial development in this scenario involves potential risk or malicious activities occurring in the network. However, there are tensions that are difficult to overcome at this stage in the development of IoT technology. In this situation, the future of security architecture development will involve enabling automatic and smart protection systems. Due to the vulnerability of current IoT devices, it is insufficient to ensure system security by implementing only traditional security tools such as encryption and access control. Deep learning and blockchain technology has now become crucial, as it provides distinct and secure approaches to IoT network security. The aim of this survey paper is to elaborate on the application of deep learning and blockchain technology in the IoT to ensure secure utility. We first provide an introduction to the IoT, deep learning, and blockchain technology, as well as a discussion of their respective security features. We then outline the main obstacles and problems of trusted IoT and how blockchain and deep learning may be able to help. Next, we present the future challenges in integrating deep learning and blockchain technology into the IoT. Finally, as a demonstration of the value of blockchain in establishing trust, we provide a comparison between conventional trust management methods and those based on blockchain.<\/jats:p>","DOI":"10.3390\/fi15050178","type":"journal-article","created":{"date-parts":[[2023,5,11]],"date-time":"2023-05-11T05:05:02Z","timestamp":1683781502000},"page":"178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Survey of Distributed and Decentralized IoT Securities: Approaches Using Deep Learning and Blockchain Technology"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7239-8074","authenticated-orcid":false,"given":"Ayodeji","family":"Falayi","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4238-4909","authenticated-orcid":false,"given":"Qianlong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1444-8925","authenticated-orcid":false,"given":"Weixian","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.future.2021.08.006","article-title":"Recent advancements and challenges of Internet of Things in smart agriculture: A survey","volume":"126","author":"Sinha","year":"2022","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.susoc.2022.01.008","article-title":"Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability","volume":"3","author":"Javaid","year":"2022","journal-title":"Sustain. Oper. Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"100584","DOI":"10.1016\/j.iot.2022.100584","article-title":"A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city","volume":"20","author":"Rizi","year":"2022","journal-title":"Internet Things"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1109\/JIOT.2017.2683200","article-title":"A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications","volume":"4","author":"Lin","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_5","unstructured":"Malini, M., and Chandrakala, N. (2022). Evolutionary Computing and Mobile Sustainable Networks: Proceedings of ICECMSN 2021, Springer."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"79523","DOI":"10.1109\/ACCESS.2019.2920763","article-title":"Secure Internet of Things (IoT)-Based Smart-World Critical Infrastructures: Survey, Case Study and Research Opportunities","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1109\/MC.2017.62","article-title":"Botnets and internet of things security","volume":"50","author":"Bertino","year":"2017","journal-title":"Computer"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/MC.2017.201","article-title":"DDoS in the IoT: Mirai and other botnets","volume":"50","author":"Kolias","year":"2017","journal-title":"Computer"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.comnet.2019.01.023","article-title":"Internet of Things: A survey on machine learning-based intrusion detection approaches","volume":"151","author":"Papa","year":"2019","journal-title":"Comput. Netw."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.comnet.2018.11.026","article-title":"A survey on internet of things security from data perspectives","volume":"148","author":"Hou","year":"2019","journal-title":"Comput. Netw."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.comnet.2018.03.012","article-title":"Internet of things security: A top-down survey","volume":"141","author":"Kouicem","year":"2018","journal-title":"Comput. Netw."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1109\/JSAC.2020.2980909","article-title":"Reinforcement Learning-Based Control and Networking Co-Design for Industrial Internet of Things","volume":"38","author":"Xu","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.comnet.2018.11.025","article-title":"Current research on Internet of Things (IoT) security: A survey","volume":"148","author":"Noor","year":"2019","journal-title":"Comput. Netw."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gao, W., Hatcher, W.G., and Yu, W. (August, January 30). A Survey of Blockchain: Techniques, Applications, and Challenges. Proceedings of the 2018 27th International Conference on Computer Communication and Networks (ICCCN), Hangzhou, China.","DOI":"10.1109\/ICCCN.2018.8487348"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lahbib, A., Toumi, K., Laouiti, A., Laube, A., and Martin, S. (2019, January 15\u201318). Blockchain based trust management mechanism for IoT. Proceedings of the 2019 IEEE Wireless Communications and Networking Conference (WCNC), Marrakech, Morocco.","DOI":"10.1109\/WCNC.2019.8885994"},{"key":"ref_16","unstructured":"Pilkington, M. (2016). Research Handbook on Digital Transformations, Edward Elgar Publishing."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.1109\/COMST.2020.2986444","article-title":"Machine learning in IoT security: Current solutions and future challenges","volume":"22","author":"Hussain","year":"2020","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_18","unstructured":"Yang, Q., An, D., and Yu, W. (2013, January 21\u201323). On time desynchronization attack against IEEE 1588 protocol in power grid systems. Proceedings of the 2013 IEEE Energytech, Cleveland, OH, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2985","DOI":"10.1109\/TII.2020.3023507","article-title":"Challenges and opportunities in securing the industrial internet of things","volume":"17","author":"Serror","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103201","DOI":"10.1016\/j.micpro.2020.103201","article-title":"Cyber-physical systems security: Limitations, issues and future trends","volume":"77","author":"Yaacoub","year":"2020","journal-title":"Microprocess. Microsyst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1646","DOI":"10.1109\/COMST.2020.2988293","article-title":"A survey of machine and deep learning methods for internet of things (IoT) security","volume":"22","author":"Mohamed","year":"2020","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e4946","DOI":"10.1002\/cpe.4946","article-title":"An overview of Internet of Things (IoT): Architectural aspects, challenges, and protocols","volume":"32","author":"Gupta","year":"2020","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.jpdc.2022.01.015","article-title":"Machine learning and the Internet of Things security: Solutions and open challenges","volume":"162","author":"Farooq","year":"2022","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2671","DOI":"10.1109\/COMST.2019.2896380","article-title":"Network intrusion detection for IoT security based on learning techniques","volume":"21","author":"Chaabouni","year":"2019","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.jbi.2015.04.007","article-title":"Security and privacy issues in implantable medical devices: A comprehensive survey","volume":"55","author":"Camara","year":"2015","journal-title":"J. Biomed. Inform."},{"key":"ref_26","unstructured":"Rieback, M.R., Crispo, B., and Tanenbaum, A.S. (2006, January 13\u201317). Is your cat infected with a computer virus?. Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications (PERCOM\u201906), Pisa, Italy."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Bose, T., Bandyopadhyay, S., Ukil, A., Bhattacharyya, A., and Pal, A. (2015, January 7\u20139). Why not keep your personal data secure yet private in IoT?: Our lightweight approach. Proceedings of the 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Singapore.","DOI":"10.1109\/ISSNIP.2015.7106942"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/j.procs.2015.05.013","article-title":"SEA: A secure and efficient authentication and authorization architecture for IoT-based healthcare using smart gateways","volume":"52","author":"Moosavi","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.comnet.2014.11.008","article-title":"Security, privacy and trust in Internet of Things: The road ahead","volume":"76","author":"Sicari","year":"2015","journal-title":"Comput. Netw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"65","DOI":"10.13052\/jcsm2245-1439.414","article-title":"Cyber security and the internet of things: Vulnerabilities, threats, intruders and attacks","volume":"4","author":"Abomhara","year":"2015","journal-title":"J. Cyber Secur. Mobil."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hu, X., Xie, C., Fan, Z., Duan, Q., Zhang, D., Jiang, L., Wei, X., Hong, D., Li, G., and Zeng, X. (2022). Hyperspectral anomaly detection using deep learning: A review. Remote Sens., 14.","DOI":"10.3390\/rs14091973"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MSP.2021.3119273","article-title":"Unsupervised deep learning methods for biological image reconstruction and enhancement: An overview from a signal processing perspective","volume":"39","author":"Yaman","year":"2022","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"24411","DOI":"10.1109\/ACCESS.2018.2830661","article-title":"A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends","volume":"6","author":"Hatcher","year":"2018","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"18042","DOI":"10.1109\/ACCESS.2017.2747560","article-title":"Network traffic classifier with convolutional and recurrent neural networks for Internet of Things","volume":"5","author":"Carro","year":"2017","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Vinayakumar, R., Soman, K., and Poornachandran, P. (2017, January 13\u201316). Applying convolutional neural network for network intrusion detection. Proceedings of the 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India.","DOI":"10.1109\/ICACCI.2017.8126009"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"25399","DOI":"10.1109\/ACCESS.2018.2833746","article-title":"Deep convolution neural network and autoencoders-based unsupervised feature learning of EEG signals","volume":"6","author":"Wen","year":"2018","journal-title":"IEEE Access"},{"key":"ref_37","unstructured":"Karhunen, J., Raiko, T., and Cho, K. (2015). Advances in Independent Component Analysis and Learning Machines, Academic Press."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1109\/MNET.2018.1700202","article-title":"Learning IoT in edge: Deep learning for the Internet of Things with edge computing","volume":"32","author":"Li","year":"2018","journal-title":"IEEE Netw."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Lakshmanna, K., Kaluri, R., Gundluru, N., Alzamil, Z.S., Rajput, D.S., Khan, A.A., Haq, M.A., and Alhussen, A. (2022). A review on deep learning techniques for IoT data. Electronics, 11.","DOI":"10.3390\/electronics11101604"},{"key":"ref_40","unstructured":"Hermans, M., and Schrauwen, B. (2013, January 5\u201310). Training and analysing deep recurrent neural networks. Proceedings of the NIPS\u201913: Proceedings of the 26th International Conference on Neural Information Processing Systems, Lake Tahoe, NV, USA."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zhao, K., and Ge, L. (2013, January 14\u201315). A survey on the internet of things security. Proceedings of the 2013 Ninth International Conference on Computational Intelligence and Security, Washington, DC, USA.","DOI":"10.1109\/CIS.2013.145"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"15132","DOI":"10.1109\/ACCESS.2018.2806881","article-title":"A Survey on Big Data Market: Pricing, Trading and Protection","volume":"6","author":"Liang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Baranwal, T., and Pateriya, P.K. (2016, January 14\u201315). Development of IoT based smart security and monitoring devices for agriculture. Proceedings of the 2016 6th International Conference-Cloud System and Big Data Engineering (Confluence), Noida, India.","DOI":"10.1109\/CONFLUENCE.2016.7508189"},{"key":"ref_44","first-page":"9324035","article-title":"Internet of things: Architectures, protocols, and applications","volume":"2017","author":"Sethi","year":"2017","journal-title":"J. Electr. Comput. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.eswa.2018.03.056","article-title":"Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges","volume":"105","author":"Nweke","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"117134","DOI":"10.1109\/ACCESS.2019.2936094","article-title":"A survey of blockchain from the perspectives of applications, challenges, and opportunities","volume":"7","author":"Monrat","year":"2019","journal-title":"IEEE Access"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.bushor.2018.12.001","article-title":"Blockchain adoption: A value driver perspective","volume":"62","author":"Angelis","year":"2019","journal-title":"Bus. Horizons"},{"key":"ref_48","first-page":"56","article-title":"Blockchain technology for next generation ICT","volume":"53","author":"Kogure","year":"2017","journal-title":"Fujitsu Sci. Tech. J."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Anilkumar, V., Joji, J.A., Afzal, A., and Sheik, R. (2019, January 15\u201317). Blockchain simulation and development platforms: Survey, issues and challenges. Proceedings of the 2019 International Conference on Intelligent Computing and Control Systems (ICCS), Madurai, India.","DOI":"10.1109\/ICCS45141.2019.9065421"},{"key":"ref_50","first-page":"14","article-title":"Understanding blockchain consensus models","volume":"4","author":"Baliga","year":"2017","journal-title":"Persistent"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e1436","DOI":"10.1002\/widm.1436","article-title":"Blockchain networks: Data structures of Bitcoin, Monero, Zcash, Ethereum, Ripple, and Iota","volume":"12","author":"Akcora","year":"2022","journal-title":"Wiley Interdiscip. Rev. Data Min. Knowl. Discov."},{"key":"ref_52","unstructured":"Cao, S., Cao, Y., Wang, X., and Lu, Y. (2017, January 26\u201328). A review of researches on blockchain. Proceedings of the WHICEB 2017 Proceedings, Wuhan, China."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Mohanta, B.K., Panda, S.S., and Jena, D. (2018, January 10\u201312). An overview of smart contract and use cases in blockchain technology. Proceedings of the 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Bengaluru, India.","DOI":"10.1109\/ICCCNT.2018.8494045"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"36282","DOI":"10.1109\/ACCESS.2021.3062845","article-title":"A trusted blockchain-based traceability system for fruit and vegetable agricultural products","volume":"9","author":"Yang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Susilo, B., and Sari, R.F. (2020). Intrusion detection in IoT networks using deep learning algorithm. Information, 11.","DOI":"10.3390\/info11050279"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Ibitoye, O., Shafiq, O., and Matrawy, A. (2019, January 9\u201313). Analyzing adversarial attacks against deep learning for intrusion detection in IoT networks. Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA.","DOI":"10.1109\/GLOBECOM38437.2019.9014337"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"9463","DOI":"10.1109\/JIOT.2020.2996590","article-title":"A deep blockchain framework-enabled collaborative intrusion detection for protecting IoT and cloud networks","volume":"8","author":"Alkadi","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"102662","DOI":"10.1016\/j.jnca.2020.102662","article-title":"Detecting Internet of Things attacks using distributed deep learning","volume":"163","author":"Parra","year":"2020","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.aej.2020.06.056","article-title":"Application of ensemble RNN deep neural network to the fall detection through IoT environment","volume":"60","author":"Farsi","year":"2021","journal-title":"Alex. Eng. J."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"74571","DOI":"10.1109\/ACCESS.2020.2988854","article-title":"Fog-based attack detection framework for internet of things using deep learning","volume":"8","author":"Samy","year":"2020","journal-title":"IEEE Access"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"21954","DOI":"10.1109\/ACCESS.2017.2762418","article-title":"A deep learning approach for intrusion detection using recurrent neural networks","volume":"5","author":"Yin","year":"2017","journal-title":"IEEE Access"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"e2039","DOI":"10.1002\/nem.2039","article-title":"Botnet detection based on network flow summary and deep learning","volume":"28","author":"Acarman","year":"2018","journal-title":"Int. J. Netw. Manag."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/MC.2018.3011034","article-title":"Intrusion detection in the era of IoT: Building trust via traffic filtering and sampling","volume":"51","author":"Meng","year":"2018","journal-title":"Computer"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Kim, J., Kim, J., Thu, H.L.T., and Kim, H. (2016, January 15\u201317). Long short term memory recurrent neural network classifier for intrusion detection. Proceedings of the 2016 International Conference on Platform Technology and Service (PlatCon), Jeju, Republic of Korea.","DOI":"10.1109\/PlatCon.2016.7456805"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1145\/2990499","article-title":"Intelligent intrusion detection in low-power IoTs","volume":"16","author":"Saeed","year":"2016","journal-title":"ACM Trans. Internet Technol. (TOIT)"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Zhao, G., Zhang, C., and Zheng, L. (2017, January 21\u201324). Intrusion detection using deep belief network and probabilistic neural network. Proceedings of the 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Guangzhou, China.","DOI":"10.1109\/CSE-EUC.2017.119"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Banaamah, A.M., and Ahmad, I. (2022). Intrusion Detection in IoT Using Deep Learning. Sensors, 22.","DOI":"10.3390\/s22218417"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Shobana, M., and Poonkuzhali, S. (2020, January 13\u201314). A novel approach to detect IoT malware by system calls using Deep learning techniques. Proceedings of the 2020 International Conference on Innovative Trends in Information Technology (ICITIIT), Kottayam, India.","DOI":"10.1109\/ICITIIT49094.2020.9071531"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1016\/j.future.2017.08.043","article-title":"Distributed attack detection scheme using deep learning approach for Internet of Things","volume":"82","author":"Diro","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/TNSM.2020.2966951","article-title":"IoT-KEEPER: Detecting malicious IoT network activity using online traffic analysis at the edge","volume":"17","author":"Hafeez","year":"2020","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"105124","DOI":"10.1016\/j.knosys.2019.105124","article-title":"Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues","volume":"189","author":"Aldweesh","year":"2020","journal-title":"Knowl.-Based Syst."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.comcom.2020.01.016","article-title":"Deep learning and big data technologies for IoT security","volume":"151","author":"Amanullah","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.future.2018.03.007","article-title":"A deep recurrent neural network based approach for internet of things malware threat hunting","volume":"85","author":"HaddadPajouh","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"6348","DOI":"10.1109\/JIOT.2020.2966778","article-title":"FDC: A secure federated deep learning mechanism for data collaborations in the Internet of Things","volume":"7","author":"Yin","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Nguyen, T.D., Marchal, S., Miettinen, M., Fereidooni, H., Asokan, N., and Sadeghi, A.R. (2019, January 7\u201310). D\u00cfoT: A federated self-learning anomaly detection system for IoT. Proceedings of the 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), Dallas, TX, USA.","DOI":"10.1109\/ICDCS.2019.00080"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"McDermott, C.D., Majdani, F., and Petrovski, A.V. (2018, January 8\u201313). Botnet detection in the internet of things using deep learning approaches. Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil.","DOI":"10.1109\/IJCNN.2018.8489489"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"2742","DOI":"10.1109\/TMC.2017.2687918","article-title":"Cloud-based malware detection game for mobile devices with offloading","volume":"16","author":"Xiao","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.ins.2018.08.019","article-title":"Deep neural networks for bot detection","volume":"467","author":"Kudugunta","year":"2018","journal-title":"Inf. Sci."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1109\/TSUSC.2018.2809665","article-title":"Robust malware detection for internet of (battlefield) things devices using deep eigenspace learning","volume":"4","author":"Azmoodeh","year":"2018","journal-title":"IEEE Trans. Sustain. Comput."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MC.2018.3011046","article-title":"IoT as a land of opportunity for DDoS hackers","volume":"51","author":"Vlajic","year":"2018","journal-title":"Computer"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Shaaban, A.R., Abd-Elwanis, E., and Hussein, M. (2019, January 8\u20139). DDoS attack detection and classification via Convolutional Neural Network (CNN). Proceedings of the 2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS), Cairo, Egypt.","DOI":"10.1109\/ICICIS46948.2019.9014826"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Nugraha, B., and Murthy, R.N. (2020, January 10\u201312). Deep learning-based slow DDoS attack detection in SDN-based networks. Proceedings of the 2020 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), Madrid, Spain.","DOI":"10.1109\/NFV-SDN50289.2020.9289894"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"van Roosmalen, J., Vranken, H., and van Eekelen, M. (2018, January 9\u201313). Applying deep learning on packet flows for botnet detection. Proceedings of the 33rd Annual ACM Symposium on Applied Computing, Pau, France.","DOI":"10.1145\/3167132.3167306"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Hodo, E., Bellekens, X., Hamilton, A., Dubouilh, P.L., Iorkyase, E., Tachtatzis, C., and Atkinson, R. (2016, January 11\u201313). Threat analysis of IoT networks using artificial neural network intrusion detection system. Proceedings of the 2016 International Symposium on Networks, Computers and Communications (ISNCC), Hammamet, Tunisia.","DOI":"10.1109\/ISNCC.2016.7746067"},{"key":"ref_85","first-page":"825","article-title":"A deep learning based intelligent framework to mitigate DDoS attack in fog environment","volume":"34","author":"Priyadarshini","year":"2022","journal-title":"J. King Saud-Univ.-Comput. Inf. Sci."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Sabeel, U., Heydari, S.S., Mohanka, H., Bendhaou, Y., Elgazzar, K., and El-Khatib, K. (2019, January 17\u201319). Evaluation of deep learning in detecting unknown network attacks. Proceedings of the 2019 International Conference on Smart Applications, Communications and Networking (SmartNets), Sharm El Sheik, Egypt.","DOI":"10.1109\/SmartNets48225.2019.9069788"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1109\/TNSM.2020.2971776","article-title":"LUCID: A practical, lightweight deep learning solution for DDoS attack detection","volume":"17","author":"Millar","year":"2020","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Shi, C., Liu, J., Liu, H., and Chen, Y. (2017, January 10\u201314). Smart user authentication through actuation of daily activities leveraging WiFi-enabled IoT. Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc Networking and Computing, Chennai, India.","DOI":"10.1145\/3084041.3084061"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Das, R., Gadre, A., Zhang, S., Kumar, S., and Moura, J.M. (2018, January 20\u201324). A deep learning approach to IoT authentication. Proceedings of the 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA.","DOI":"10.1109\/ICC.2018.8422832"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"S48","DOI":"10.1016\/j.diin.2018.01.007","article-title":"MalDozer: Automatic framework for android malware detection using deep learning","volume":"24","author":"Karbab","year":"2018","journal-title":"Digit. Investig."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Su, J., Vasconcellos, D.V., Prasad, S., Sgandurra, D., Feng, Y., and Sakurai, K. (2018, January 23\u201327). Lightweight classification of IoT malware based on image recognition. Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Tokyo, Japan.","DOI":"10.1109\/COMPSAC.2018.10315"},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Hamdan, S., Ayyash, M., and Almajali, S. (2020). Edge-computing architectures for internet of things applications: A survey. Sensors, 20.","DOI":"10.3390\/s20226441"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"102112","DOI":"10.1016\/j.sysarc.2021.102112","article-title":"A secure and efficient authentication and data sharing scheme for Internet of Things based on blockchain","volume":"117","author":"Fan","year":"2021","journal-title":"J. Syst. Archit."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"26609","DOI":"10.1007\/s11042-020-10087-1","article-title":"A remix IDE: Smart contract-based framework for the healthcare sector by using Blockchain technology","volume":"81","author":"Hussain","year":"2022","journal-title":"Multimed. Tools Appl."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.jmsy.2020.01.009","article-title":"Blockchain-based data management for digital twin of product","volume":"54","author":"Huang","year":"2020","journal-title":"J. Manuf. Syst."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"15596","DOI":"10.1109\/JIOT.2021.3073500","article-title":"Blockchain-aided privacy-preserving outsourcing algorithms of bilinear pairings for internet of things devices","volume":"8","author":"Zhang","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.compeleceng.2018.08.021","article-title":"Towards decentralized IoT security enhancement: A blockchain approach","volume":"72","author":"Qian","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Verma, P., Sonanis, R., Goel, U., De, A., Kondaveeti, S.A., and Shekhar, S. (2018, January 15\u201320). Continuous security in IoT using blockchain. Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canada.","DOI":"10.1109\/ICASSP.2018.8462513"},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Gong, X., Liu, E., and Wang, R. (2020, January 15\u201318). Blockchain-based IoT application using smart contracts: Case study of M2M autonomous trading. Proceedings of the 2020 5th International Conference on Computer and Communication Systems (ICCCS), Shanghai, China.","DOI":"10.1109\/ICCCS49078.2020.9118549"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1016\/j.ins.2018.12.043","article-title":"Blockchain-based system for secure outsourcing of bilinear pairings","volume":"527","author":"Lin","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"101933","DOI":"10.1016\/j.adhoc.2019.101933","article-title":"A secure communicating things network framework for industrial IoT using blockchain technology","volume":"94","author":"Rathee","year":"2019","journal-title":"Ad Hoc Netw."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"164908","DOI":"10.1109\/ACCESS.2019.2950872","article-title":"Privacy-preserving solutions for blockchain: Review and challenges","volume":"7","author":"Bernabe","year":"2019","journal-title":"IEEE Access"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"3680","DOI":"10.1109\/TII.2019.2903342","article-title":"Towards secure industrial IoT: Blockchain system with credit-based consensus mechanism","volume":"15","author":"Huang","year":"2019","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1007\/s12083-016-0456-1","article-title":"The IoT electric business model: Using blockchain technology for the internet of things","volume":"10","author":"Zhang","year":"2017","journal-title":"Peer-to-Peer Netw. Appl."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Lin, J., Yu, W., Yang, X., Yang, Q., Fu, X., and Zhao, W. (July, January 29). A Novel Dynamic En-Route Decision Real-Time Route Guidance Scheme in Intelligent Transportation Systems. Proceedings of the 2015 IEEE 35th International Conference on Distributed Computing Systems, Columbus, OH, USA.","DOI":"10.1109\/ICDCS.2015.15"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"8738","DOI":"10.1109\/TVT.2018.2845744","article-title":"Data Integrity Attacks Against Dynamic Route Guidance in Transportation-Based Cyber-Physical Systems: Modeling, Analysis, and Defense","volume":"67","author":"Lin","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"1550147719825820","DOI":"10.1177\/1550147719825820","article-title":"Trust management in social internet of vehicles: Factors, challenges, blockchain, and fog solutions","volume":"15","author":"Iqbal","year":"2019","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"79694","DOI":"10.1109\/ACCESS.2019.2922236","article-title":"Privacy management in social internet of vehicles: Review, challenges and blockchain based solutions","volume":"7","author":"Butt","year":"2019","journal-title":"IEEE Access"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.cie.2019.07.022","article-title":"Smart contract-based approach for efficient shipment management","volume":"136","author":"Hasan","year":"2019","journal-title":"Comput. Ind. Eng."},{"key":"ref_110","doi-asserted-by":"crossref","unstructured":"Malik, S., Dedeoglu, V., Kanhere, S.S., and Jurdak, R. (2019, January 14\u201317). Trustchain: Trust management in blockchain and iot supported supply chains. Proceedings of the 2019 IEEE International Conference on Blockchain (Blockchain), Atlanta, GA, USA.","DOI":"10.1109\/Blockchain.2019.00032"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"78238","DOI":"10.1109\/ACCESS.2018.2884906","article-title":"A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective","volume":"6","author":"Xu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"107746","DOI":"10.1016\/j.cie.2021.107746","article-title":"A review of Industry 4.0 characteristics and challenges, with potential improvements using blockchain technology","volume":"162","author":"Aoun","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"3108","DOI":"10.1109\/TVT.2021.3138203","article-title":"A blockchain based user subscription data management and access control scheme in mobile communication networks","volume":"71","author":"Xue","year":"2021","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_114","first-page":"40","article-title":"Blockchain with internet of things: Benefits, challenges, and future directions","volume":"10","author":"Atlam","year":"2018","journal-title":"Int. J. Intell. Syst. Appl."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"3582","DOI":"10.1109\/TII.2021.3116132","article-title":"Blockchain-empowered decentralized horizontal federated learning for 5G-enabled UAVs","volume":"18","author":"Feng","year":"2021","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/MC.2018.2880021","article-title":"Blockchain and electronic healthcare records [cybertrust]","volume":"51","author":"Kshetri","year":"2018","journal-title":"Computer"},{"key":"ref_117","first-page":"192","article-title":"Toward integrating distributed energy resources and storage devices in smart grid","volume":"4","author":"Xu","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1109\/TPDS.2013.92","article-title":"On False Data-Injection Attacks against Power System State Estimation: Modeling and Countermeasures","volume":"25","author":"Yang","year":"2014","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/JIOT.2020.2993601","article-title":"Blockchain for future smart grid: A comprehensive survey","volume":"8","author":"Mollah","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"252","DOI":"10.3991\/ijet.v13i10.9455","article-title":"Application of blockchain technology in online education","volume":"13","author":"Sun","year":"2018","journal-title":"Int. J. Emerg. Technol. Learn."},{"key":"ref_121","doi-asserted-by":"crossref","unstructured":"Mallapuram, S., Ngwum, N., Yuan, F., Lu, C., and Yu, W. (2017, January 24\u201326). Smart city: The state of the art, datasets, and evaluation platforms. Proceedings of the 2017 IEEE\/ACIS 16th International Conference on Computer and Information Science (ICIS), Wuhan, China.","DOI":"10.1109\/ICIS.2017.7960034"},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Lau, C.H., Alan, K.H.Y., and Yan, F. (2018, January 10\u201313). Blockchain-based authentication in IoT networks. Proceedings of the 2018 IEEE Conference on Dependable and Secure Computing (DSC), Kaohsiung, Taiwan.","DOI":"10.1109\/DESEC.2018.8625141"},{"key":"ref_123","first-page":"5782","article-title":"A systematic literature mapping on secure identity management using blockchain technology","volume":"34","author":"Rathee","year":"2022","journal-title":"J. King Saud-Univ.-Comput. Inf. Sci."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"2130006","DOI":"10.1142\/S0218126621300063","article-title":"A survey on internet of things: Applications, recent issues, attacks, and security mechanisms","volume":"30","author":"Uganya","year":"2021","journal-title":"J. Circuits Syst. Comput."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MS.2020.2992783","article-title":"Design pattern as a service for blockchain-based self-sovereign identity","volume":"37","author":"Liu","year":"2020","journal-title":"IEEE Softw."},{"key":"ref_126","unstructured":"Lundkvist, C., Heck, R., Torstensson, J., Mitton, Z., and Sena, M. (2023, March 23). Uport: A Platform for Self-Sovereign Identity. Available online: https:\/\/whitepaper.uport.me\/uPort_whitepaper_DRAFT20170221.pdf."},{"key":"ref_127","unstructured":"Reed, D., Sporny, M., Longley, D., Allen, C., Grant, R., and Sabadello, M. (2023, March 23). Decentralized Identifiers (DIDs) v1. 0\u2013Data Model and Syntaxes for Decentralized Identifiers (W3C Credentials Community Group). Available online: https:\/\/www.w3.org\/TR\/did-core\/."},{"key":"ref_128","unstructured":"ShoCard, S. (2023, March 23). Travel Identity of the Future\u2013White Paper. Available online: https:\/\/canada-ca.github.io\/PCTF-CCP\/docs\/RelatedPolicies\/SITA_Identity_2016.pdf."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"3102","DOI":"10.1109\/JIOT.2018.2833206","article-title":"Low power data integrity in IoT systems","volume":"5","author":"Aman","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Liu, B., Yu, X.L., Chen, S., Xu, X., and Zhu, L. (2017, January 25\u201330). Blockchain based data integrity service framework for IoT data. Proceedings of the 2017 IEEE International Conference on Web Services (ICWS), Honolulu, HI, USA.","DOI":"10.1109\/ICWS.2017.54"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"164996","DOI":"10.1109\/ACCESS.2019.2952635","article-title":"Blockchain based data integrity verification for large-scale IoT data","volume":"7","author":"Wang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.comcom.2020.01.030","article-title":"Decentralized authorization in constrained IoT environments exploiting interledger mechanisms","volume":"152","author":"Siris","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Siris, V.A., Dimopoulos, D., Fotiou, N., Voulgaris, S., and Polyzos, G.C. (2019, January 15\u201318). OAuth 2.0 meets blockchain for authorization in constrained IoT environments. Proceedings of the 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), Limerick, Ireland.","DOI":"10.1109\/WF-IoT.2019.8767223"},{"key":"ref_134","doi-asserted-by":"crossref","unstructured":"Oksiiuk, O., and Dmyrieva, I. (2020, January 25\u201329). Security and privacy issues of blockchain technology. Proceedings of the 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine.","DOI":"10.1109\/TCSET49122.2020.235489"},{"key":"ref_135","doi-asserted-by":"crossref","unstructured":"Jonathan, K., and Sari, A.K. (2019, January 5\u20136). Security issues and vulnerabilities on a blockchain system: A review. Proceedings of the 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia.","DOI":"10.1109\/ISRITI48646.2019.9034659"},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Sayeed, S., and Marco-Gisbert, H. (2019). Assessing blockchain consensus and security mechanisms against the 51% attack. Appl. Sci., 9.","DOI":"10.3390\/app9091788"},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1109\/MNET.011.2000263","article-title":"A blockchain-based decentralized federated learning framework with committee consensus","volume":"35","author":"Li","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Hsueh, C.W., and Chin, C.T. (2022). Toward Trusted IoT by General Proof-of-Work. Sensors, 23.","DOI":"10.3390\/s23010015"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1007\/s12083-022-01422-4","article-title":"An improved Kalman filter using ANN-based learning module to predict transaction throughput of blockchain network in clinical trials","volume":"16","author":"Hang","year":"2023","journal-title":"Peer-to-Peer Netw. Appl."},{"key":"ref_140","doi-asserted-by":"crossref","unstructured":"Lebanoff, L., Peterson, C., and Dechev, D. (2019, January 17\u201321). Check-wait-pounce: Increasing transactional data structure throughput by delaying transactions. Proceedings of the Distributed Applications and Interoperable Systems: 19th IFIP WG 6.1 International Conference, DAIS 2019, Held as Part of the 14th International Federated Conference on Distributed Computing Techniques, DisCoTec 2019, Kongens Lyngby, Denmark.","DOI":"10.1007\/978-3-030-22496-7_2"},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"34517","DOI":"10.1007\/s11042-020-08776-y","article-title":"Blockchain based privacy preserving multimedia intelligent video surveillance using secure Merkle tree","volume":"80","author":"Lee","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"6900","DOI":"10.1109\/ACCESS.2017.2778504","article-title":"A Survey on the Edge Computing for the Internet of Things","volume":"6","author":"Yu","year":"2018","journal-title":"IEEE Access"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/15\/5\/178\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:32:52Z","timestamp":1760124772000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/15\/5\/178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,11]]},"references-count":142,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["fi15050178"],"URL":"https:\/\/doi.org\/10.3390\/fi15050178","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,11]]}}}