{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T05:59:49Z","timestamp":1784613589693,"version":"3.55.0"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T00:00:00Z","timestamp":1773446400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"vor","delay-in-days":26,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"ESAIP - ECOLE D\u2019INGENIEURS"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"DOI":"10.1186\/s40537-026-01373-0","type":"journal-article","created":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T13:05:32Z","timestamp":1773493532000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["GEN-SECHEALTH: an AI-powered generative architecture for self-scalable cybersecurity and flexible data privacy protection in intricate healthcare systems"],"prefix":"10.1186","volume":"13","author":[{"given":"Sajid","family":"Mehmood","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rashid","family":"Amin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio","family":"Costanzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asma Hassan","family":"Alshehri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Faisal S.","family":"Alsubaei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,14]]},"reference":[{"key":"1373_CR1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0332752","volume":"20","author":"A Alqhatani","year":"2025","unstructured":"Alqhatani A, Mehmood S, Amin R, et al. Deep memory for deep threats: A novel architecture combining grus and deep learning models for ids. PLoS ONE. 2025;20:e0332752.","journal-title":"PLoS ONE"},{"key":"1373_CR2","doi-asserted-by":"publisher","first-page":"6256","DOI":"10.1109\/TAES.2024.3408139","volume":"60","author":"B Xue","year":"2024","unstructured":"Xue B, Zheng Q, Li Z, et al. Isar weak feature enhancement with perturbation defense using hybrid clustering oversegmentation. IEEE Trans Aerosp Electron Syst. 2024;60:6256\u201374.","journal-title":"IEEE Trans Aerosp Electron Syst"},{"key":"1373_CR3","doi-asserted-by":"publisher","first-page":"4060","DOI":"10.3390\/s23084060","volume":"23","author":"H Riggs","year":"2023","unstructured":"Riggs H, Tufail S, Parvez I, et al. Impact, vulnerabilities, and mitigation strategies for cyber-secure critical infrastructure. Sensors. 2023;23:4060.","journal-title":"Sensors"},{"key":"1373_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.109420","volume":"138","author":"B Xue","year":"2024","unstructured":"Xue B, Zheng Q, Li Z, et al. Perturbation defense ultra high-speed weak target recognition. Eng Appl Artif Intell. 2024;138:109420.","journal-title":"Eng Appl Artif Intell"},{"key":"1373_CR5","doi-asserted-by":"crossref","unstructured":"Ding F, Liu Z, Wang Y, et al. Intelligent event triggered lane keeping security control for autonomous vehicle under dos attacks, IEEE Transactions on Fuzzy Systems;2025.","DOI":"10.1109\/TFUZZ.2025.3597276"},{"key":"1373_CR6","doi-asserted-by":"publisher","first-page":"5571","DOI":"10.1109\/TMC.2023.3314837","volume":"23","author":"F Han","year":"2023","unstructured":"Han F, Yang P, Du H, Li X-Y. Accuth \u229d\u208a\u208a: Accelerometer-based anti-spoofing voice authentication on wrist-worn wearables. IEEE Trans Mob Comput. 2023;23:5571\u201388.","journal-title":"IEEE Trans Mob Comput"},{"key":"1373_CR7","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s12939-019-0982-6","volume":"18","author":"C Chen","year":"2019","unstructured":"Chen C, Pan J. The effect of the health poverty alleviation project on financial risk protection for rural residents: evidence from chishui city, china. Int J Equity Health. 2019;18:79.","journal-title":"Int J Equity Health"},{"key":"1373_CR8","doi-asserted-by":"crossref","unstructured":"Jin J, Wu M, Ouyang A, et al. A novel dynamic hill cipher and its applications on medical iot. IEEE Internet Things J;2025.","DOI":"10.1109\/JIOT.2025.3525623"},{"key":"1373_CR9","unstructured":"Regulatory barriers to threat intelligence sharing. R. Agarwal and L. Masterson, Hipaa vs. cybersecurity innovation. Journal of Healthcare IT. 2024;12:112\u201330."},{"key":"1373_CR10","doi-asserted-by":"crossref","unstructured":"He W, Tan J, Wang R, et al.: A deep reinforcement learning approach to time delay differential game deception resource deployment, IEEE Transactions on Dependable and Secure Computing;2025.","DOI":"10.1109\/TDSC.2025.3620151"},{"key":"1373_CR11","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1016\/j.ins.2023.01.020","volume":"629","author":"Z Zhao","year":"2023","unstructured":"Zhao Z, Li X, Luan B, et al. Secure internet of things (iot) using a novel brooks iyengar quantum byzantine agreement-centered blockchain networking (biqba-bcn) model in smart healthcare. Inf Sci. 2023;629:440\u201355.","journal-title":"Inf Sci"},{"key":"1373_CR12","unstructured":"Barker E, Smid M. Limitations of nist csf in healthcare environments, NIST Interagency Report 8401, National Institute of Standards and Technology;2023."},{"key":"1373_CR13","doi-asserted-by":"crossref","unstructured":"Ma Q, Han Y, Chen M, et al. The impact of a large-scale chronic disease prevention and control program on the health benefits of older adults: Evidence from a natural experiment in china. China Econ Rev. 2025:102632.","DOI":"10.1016\/j.chieco.2025.102632"},{"key":"1373_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/979-8-8688-0823-4","volume-title":"Security and Privacy for Modern Networks","author":"S Lekkala","year":"2024","unstructured":"Lekkala S, Gurijala P. Security and Privacy for Modern Networks. Springer; 2024."},{"key":"1373_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.107881","volume":"131","author":"Y Akkem","year":"2024","unstructured":"Akkem Y, Biswas SK, Varanasi A. A comprehensive review of synthetic data generation in smart farming by using variational autoencoder and generative adversarial network. Eng Appl Artif Intell. 2024;131:107881.","journal-title":"Eng Appl Artif Intell"},{"key":"1373_CR16","unstructured":"Al Zami MB, Shaon S, Quy VK, Nguyen DC. Digital twin in industries: A comprehensive survey, IEEE Access;2025."},{"key":"1373_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11235-025-01365-0","volume":"88","author":"MS Alshehri","year":"2025","unstructured":"Alshehri MS, Mehmood S, Frnda J, et al. Enhanced cybersecurity for digital substations: a hybrid sdn-ids with active threat mitigation and fault localization. Telecommun Syst. 2025;88:1\u201318.","journal-title":"Telecommun Syst"},{"key":"1373_CR18","doi-asserted-by":"publisher","first-page":"76071","DOI":"10.1109\/ACCESS.2023.3296707","volume":"11","author":"A Dunmore","year":"2023","unstructured":"Dunmore A, Jang-Jaccard J, Sabrina F, Kwak J. A comprehensive survey of generative adversarial networks (gans) in cybersecurity intrusion detection. IEEE Access. 2023;11:76071\u201394.","journal-title":"IEEE Access"},{"key":"1373_CR19","doi-asserted-by":"publisher","DOI":"10.3390\/electronics13020322","volume":"13","author":"G Agrawal","year":"2024","unstructured":"Agrawal G, Kaur A, Myneni S. A review of generative models in generating synthetic attack data for cybersecurity. Electronics. 2024;13:322.","journal-title":"Electronics"},{"key":"1373_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2024.100572","volume":"17","author":"AA Neloy","year":"2024","unstructured":"Neloy AA, Turgeon M. A comprehensive study of auto-encoders for anomaly detection: efficiency and trade-offs. Machine Learning with Applications. 2024;17:100572.","journal-title":"Machine Learning with Applications"},{"key":"1373_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112899","volume":"309","author":"J Yan","year":"2025","unstructured":"Yan J, Huang H, Yang K, et al. Synthetic data for enhanced privacy: a vae-gan approach against membership inference attacks. Knowl Based Syst. 2025;309:112899.","journal-title":"Knowl Based Syst"},{"key":"1373_CR22","doi-asserted-by":"publisher","DOI":"10.3390\/info11050243","volume":"11","author":"PS Muhuri","year":"2020","unstructured":"Muhuri PS, Chatterjee P, Yuan X, et al. Using a long short-term memory recurrent neural network (lstm-rnn) to classify network attacks. Information. 2020;11:243.","journal-title":"Information"},{"key":"1373_CR23","doi-asserted-by":"publisher","first-page":"2433","DOI":"10.1109\/OJCOMS.2024.3362271","volume":"5","author":"A Celik","year":"2024","unstructured":"Celik A, Eltawil AM. At the dawn of generative ai era: a tutorial-cum-survey on new frontiers in 6g wireless intelligence. IEEE Open Journal of the Communications Society. 2024;5:2433\u201389.","journal-title":"IEEE Open Journal of the Communications Society"},{"key":"1373_CR24","volume":"35","author":"A Nazir","year":"2023","unstructured":"Nazir A, He J, Zhu N, et al. Advancing iot security: a systematic review of machine learning approaches for the detection of iot botnets. Journal of King Saud University. 2023;35:101820.","journal-title":"Journal of King Saud University"},{"key":"1373_CR25","doi-asserted-by":"publisher","first-page":"1676189","DOI":"10.3389\/fpubh.2025.1676189","volume":"13","author":"F Hu","year":"2025","unstructured":"Hu F, Yang H, Wei S, et al. Spatial networks of china\u2019s specialized, refined, distinctive, and innovative medical device firms based on parent-subsidiary contacts: implications for regional health policy. Front Public Health. 2025;13:1676189.","journal-title":"Front Public Health"},{"key":"1373_CR26","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-025-07255-1","volume":"81","author":"A Nazir","year":"2025","unstructured":"Nazir A, He J, Zhu N, et al. Empirical evaluation of ensemble learning and hybrid cnn-lstm for iot threat detection on heterogeneous datasets. The Journal of Supercomputing. 2025;81:775.","journal-title":"The Journal of Supercomputing"},{"key":"1373_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2024.101939","volume":"36","author":"A Nazir","year":"2024","unstructured":"Nazir A, He J, Zhu N, et al. Collaborative threat intelligence: enhancing iot security through blockchain and machine learning integration. J King Saud Univ. 2024;36:101939.","journal-title":"J King Saud Univ"},{"key":"1373_CR28","doi-asserted-by":"publisher","first-page":"8367","DOI":"10.1007\/s10586-024-04436-0","volume":"27","author":"A Nazir","year":"2024","unstructured":"Nazir A, He J, Zhu N, et al. Enhancing iot security: a collaborative framework integrating federated learning, dense neural networks, and blockchain. Cluster Comput. 2024;27:8367\u201392.","journal-title":"Cluster Comput"},{"key":"1373_CR29","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-25107-z","volume":"15","author":"M Tawfik","year":"2025","unstructured":"Tawfik M, Abu-Ein AA, Noaman HM, et al. Fedmedsecure: federated few-shot learning with cross-attention mechanisms and explainable ai for collaborative healthcare cybersecurity. Sci Rep. 2025;15:40050.","journal-title":"Sci Rep"},{"key":"1373_CR30","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0304082","volume":"19","author":"M Tawfik","year":"2024","unstructured":"Tawfik M. Optimized intrusion detection in iot and fog computing using ensemble learning and advanced feature selection. PLoS One. 2024;19:e0304082.","journal-title":"PLoS One"},{"key":"1373_CR31","doi-asserted-by":"crossref","unstructured":"Sarker IH. Generative ai and large language modeling in cybersecurity, in AI-Driven Cybersecurity and Threat Intelligence: Cyber Automation, Intelligent Decision-Making and Explainability, (Springer), 2024:79\u201399.","DOI":"10.1007\/978-3-031-54497-2_5"},{"key":"1373_CR32","doi-asserted-by":"crossref","unstructured":"Monferran P, Costanzo A, de S\u00e3o Jos\u00e9 AN, et al. Machine learning techniques for the geolocalization of jamming sources in indoor wireless networks, in 2024 International Symposium on Electromagnetic Compatibility-EMC Europe, (IEEE, City, Country), 2024:534\u2013539.","DOI":"10.1109\/EMCEurope59828.2024.10722202"},{"key":"1373_CR33","doi-asserted-by":"crossref","unstructured":"Costanzo A, Deniau V, Loscri V. Effects of intentional rf interference on optical wireless communication systems, in 2024 International Symposium on Electromagnetic Compatibility-EMC Europe. City, Country: IEEE; 2024. p. 528\u201333.","DOI":"10.1109\/EMCEurope59828.2024.10722477"},{"key":"1373_CR34","first-page":"479","volume":"7","author":"R Panigrahi","year":"2018","unstructured":"Panigrahi R, Borah S. A detailed analysis of cicids2017 dataset for designing intrusion detection systems. International Journal of Engineering & Technology. 2018;7:479\u201382.","journal-title":"International Journal of Engineering & Technology"},{"key":"1373_CR35","unstructured":"Li E, Shang Z, Gungor O, Rosing T. Safe: Self-supervised anomaly detection framework for intrusion detection;2025. arXiv preprint arXiv:2502.07119 ."},{"key":"1373_CR36","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-72049-z","volume":"14","author":"A Qaddos","year":"2024","unstructured":"Qaddos A, Yaseen MU, Al-Shamayleh AS, et al. A novel intrusion detection framework for optimizing iot security. Sci Rep. 2024;14:21789.","journal-title":"Sci Rep"},{"key":"1373_CR37","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s40537-024-00886-w","volume":"11","author":"MA Talukder","year":"2024","unstructured":"Talukder MA, Islam MM, Uddin MA, et al. Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction. J Big Data. 2024;11:33.","journal-title":"J Big Data"}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40537-026-01373-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-026-01373-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-026-01373-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T09:00:35Z","timestamp":1775725235000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s40537-026-01373-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,14]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1373"],"URL":"https:\/\/doi.org\/10.1186\/s40537-026-01373-0","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,14]]},"assertion":[{"value":"13 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"58"}}