{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T19:00:48Z","timestamp":1785006048824,"version":"3.55.0"},"reference-count":85,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s10586-026-06164-z","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T10:38:07Z","timestamp":1781692687000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FinSecure-FL: a blockchain-secured federated support vector regression framework with adaptive aggregation for privacy-preserving financial market prediction"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3102-6559","authenticated-orcid":false,"given":"Zakia","family":"Zouaghia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1872-9364","authenticated-orcid":false,"given":"Zahra","family":"Kodia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9225-884X","authenticated-orcid":false,"given":"Lamjed","family":"Ben Said","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"key":"6164_CR1","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.future.2021.08.028","volume":"127","author":"U Ahmed","year":"2022","unstructured":"Ahmed, U., Srivastava, G., Lin, J.C.W.: Reliable customer analysis using federated learning and exploring deep-attention edge intelligence. Future Generation Computer Systems 127, 70\u201379 (2022). https:\/\/doi.org\/10.1016\/j.future.2021.08.028","journal-title":"Future Generation Computer Systems"},{"issue":"5","key":"6164_CR2","doi-asserted-by":"publisher","first-page":"143","DOI":"10.32996\/jcsts.2024.6.5.12","volume":"6","author":"TR Akash","year":"2024","unstructured":"Akash, T.R., Lessard, N.D.J., Reza, N.R., Islam, M.S.: Investigating methods to enhance data privacy in business, especially in sectors like analytics and finance. Journal of Computer Science and Technology Studies 6(5), 143\u2013151 (2024)","journal-title":"Journal of Computer Science and Technology Studies"},{"key":"6164_CR3","doi-asserted-by":"crossref","unstructured":"Albori, M., Nispi Landi, V., & Moro, A. (2024). US election risks and the impact of Trump\u2019s re-election odds on financial markets. Available at SSRN. https:\/\/ssrn.com\/abstract=4910415","DOI":"10.2139\/ssrn.4910415"},{"key":"6164_CR4","doi-asserted-by":"publisher","unstructured":"Alhamis, I. (2025). The Resurgence of Trumponomics: Implications for the Future of ESG Investments in a Changing Political Landscape. arXiv preprint arXiv:2502.02627. https:\/\/doi.org\/10.24297\/jssr.v21i.9702","DOI":"10.24297\/jssr.v21i.9702"},{"issue":"6","key":"6164_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2022.103061","volume":"59","author":"S Banabilah","year":"2022","unstructured":"Banabilah, S., Aloqaily, M., Alsayed, E., Malik, N., Jararweh, Y.: Federated learning review: Fundamentals, enabling technologies, and future applications. Information processing & management 59(6), 103061 (2022). https:\/\/doi.org\/10.1016\/j.ipm.2022.103061","journal-title":"Information processing & management"},{"issue":"4","key":"6164_CR6","doi-asserted-by":"publisher","first-page":"2983","DOI":"10.1109\/COMST.2023.3315746","volume":"25","author":"ETM Beltr\u00e1n","year":"2023","unstructured":"Beltr\u00e1n, E.T.M., P\u00e9rez, M.Q., S\u00e1nchez, P.M.S., Bernal, S.L., Bovet, G., P\u00e9rez, M.G., Celdr\u00e1n, A.H.: Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges. IEEE Communications Surveys & Tutorials 25(4), 2983\u20133013 (2023). https:\/\/doi.org\/10.1109\/COMST.2023.3315746","journal-title":"IEEE Communications Surveys & Tutorials"},{"key":"6164_CR7","unstructured":"Bollerslev, T., D. J. Hsieh, and M. W. Yu.: Volatility and market data: a review of the empirical evidence. In: handbook of financial data and risk information I. Springer, 1-27, (2020)"},{"key":"6164_CR8","unstructured":"CALFIRE: Palisades Fire: Incident Update on 01\/21\/2025 at 6:32 PM | CAL FIRE. (2025) https:\/\/www.fire.ca.gov\/incidents\/2025\/1\/7\/palisades-fire\/updates\/6cb6ffe9-3b14-47fd-849a-b3debb163afd"},{"issue":"7","key":"6164_CR9","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1145\/3359552","volume":"63","author":"C Catalini","year":"2020","unstructured":"Catalini, C., Gans, J.S.: Some simple economics of the blockchain. Communications of the ACM 63(7), 80\u201390 (2020). https:\/\/doi.org\/10.1145\/3359552","journal-title":"Communications of the ACM"},{"key":"6164_CR10","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.eswa.2016.02.006","volume":"55","author":"RC Cavalcante","year":"2016","unstructured":"Cavalcante, R.C., Brasileiro, R.C., Souza, V.L., Nobrega, J.P., Oliveira, A.L.: Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications 55, 194\u2013211 (2016). https:\/\/doi.org\/10.1016\/j.eswa.2016.02.006","journal-title":"Expert Systems with Applications"},{"key":"6164_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbvi.2019.e00151","volume":"13","author":"Y Chen","year":"2020","unstructured":"Chen, Y., Bellavitis, C.: Blockchain disruption and decentralized finance: The rise of decentralized business models. J. Bus. Ventur. Insights 13, e00151 (2020). https:\/\/doi.org\/10.1016\/j.jbvi.2019.e00151","journal-title":"J. Bus. Ventur. Insights"},{"issue":"3","key":"6164_CR12","doi-asserted-by":"publisher","first-page":"2321","DOI":"10.1007\/s10115-024-02285-2","volume":"67","author":"C Chen","year":"2025","unstructured":"Chen, C., Liu, J., Tan, H., Li, X., Wang, K.I.K., Li, P., Dou, D.: Trustworthy federated learning: Privacy, security, and beyond. Knowl. Inf. Syst. 67(3), 2321\u20132356 (2025). https:\/\/doi.org\/10.1007\/s10115-024-02285-2","journal-title":"Knowl. Inf. Syst."},{"issue":"1","key":"6164_CR13","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s10844-023-00804-1","volume":"62","author":"R Corizzo","year":"2024","unstructured":"Corizzo, R., Rosen, J.: Stock market prediction with time series data and news headlines: a stacking ensemble approach. Journal of Intelligent Information Systems 62(1), 27\u201356 (2024). https:\/\/doi.org\/10.1007\/s10844-023-00804-1","journal-title":"Journal of Intelligent Information Systems"},{"key":"6164_CR14","doi-asserted-by":"publisher","unstructured":"Dwork, C., McSherry, F., Nissim, K., & Smith, A.: Calibrating noise to sensitivity in private data analysis. In Theory of cryptography conference (pp. 265-284). Berlin, Heidelberg: Springer Berlin Heidelberg. (2006) https:\/\/doi.org\/10.1007\/11681878_14","DOI":"10.1007\/11681878_14"},{"issue":"3-4","key":"6164_CR15","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1561\/0400000042","volume":"9","author":"C Dwork","year":"2014","unstructured":"Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Foundations and trends\u00ae in theoretical computer science 9(3\u20134), 211\u2013487 (2014). https:\/\/doi.org\/10.1561\/0400000042","journal-title":"Foundations and trends\u00ae in theoretical computer science"},{"key":"#cr-split#-6164_CR16.1","doi-asserted-by":"crossref","unstructured":"European Parliament & Council. (2016). Regulation","DOI":"10.59403\/1v8s9t8"},{"key":"#cr-split#-6164_CR16.2","unstructured":"(EU) 2016\/679 of the European Parliament and of the Council (General Data Protection Regulation - GDPR). Official Journal of the European Union. https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX%3A32016R0679"},{"key":"6164_CR17","unstructured":"European Parliament & Council. (2014). Directive 2014\/65\/EU on markets in financial instruments (MiFID II). Official Journal of the European Union. https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX%3A32014L0065"},{"key":"6164_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2021.107669","volume":"137","author":"MN Fekri","year":"2022","unstructured":"Fekri, M.N., Grolinger, K., Mir, S.: Distributed load forecasting using smart meter data: Federated learning with Recurrent Neural Networks. International Journal of Electrical Power & Energy Systems 137, 107669 (2022). https:\/\/doi.org\/10.1016\/j.ijepes.2021.107669","journal-title":"International Journal of Electrical Power & Energy Systems"},{"key":"6164_CR19","doi-asserted-by":"publisher","unstructured":"George, J.: Harnessing the power of real-time analytics and reverse ETL: Strategies for unlocking data-driven insights and enhancing decision-making. Available at SSRN 4963391, (2023). https:\/\/doi.org\/10.2139\/ssrn.4963391","DOI":"10.2139\/ssrn.4963391"},{"issue":"1","key":"6164_CR20","doi-asserted-by":"publisher","first-page":"54","DOI":"10.5281\/zenodo.10001735","volume":"1","author":"AS George","year":"2023","unstructured":"George, A.S.: Securing the future of finance: how AI, Blockchain, and machine learning safeguard emerging Neobank technology against evolving cyber threats. Partners Universal Innovative Research Publication 1(1), 54\u201366 (2023). https:\/\/doi.org\/10.5281\/zenodo.10001735","journal-title":"Partners Universal Innovative Research Publication"},{"key":"6164_CR21","doi-asserted-by":"crossref","unstructured":"Gimello-Mesplomb, F. Decoding January 2025 Los Angeles Wildfires: How (and Why) the Emotional Power of Iconic Fires Revives Ancestral Fears and Fuels Misinformation","DOI":"10.33767\/osf.io\/p6cfn"},{"key":"6164_CR22","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.ijin.2021.09.005","volume":"2","author":"A Haleem","year":"2021","unstructured":"Haleem, A., Javaid, M., Singh, R.P., Suman, R., Rab, S.: Blockchain technology applications in healthcare: An overview. International Journal of Intelligent Networks 2, 130\u2013139 (2021). https:\/\/doi.org\/10.1016\/j.ijin.2021.09.005","journal-title":"International Journal of Intelligent Networks"},{"key":"6164_CR23","unstructured":"Emma, L. (2024). Big data analytics for real-time insights and strategic business planning. no. December. https:\/\/www.researchgate.net\/publication\/386336003_Big_data_analytics_for_real-time_insights_and_strategic_business_planning"},{"key":"6164_CR24","doi-asserted-by":"publisher","unstructured":"Herath, H.M.S.S., Herath, H.M.K.K.M.B., Madhusanka, B.G.D.A., Guruge, L.G.P.K. (2024). Data protection challenges in the processing of sensitive data. In: Hewage, C., Yasakethu, L., Jayakody, D.N.K. (eds) Data Protection. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-76473-8_8","DOI":"10.1007\/978-3-031-76473-8_8"},{"key":"6164_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.iswa.2022.200064","volume":"14","author":"A Imteaj","year":"2022","unstructured":"Imteaj, A., Amini, M.H.: Leveraging asynchronous federated learning to predict customers financial distress. Intelligent Systems with Applications 14, 200064 (2022). https:\/\/doi.org\/10.1016\/j.iswa.2022.200064","journal-title":"Intelligent Systems with Applications"},{"issue":"1","key":"6164_CR26","doi-asserted-by":"publisher","first-page":"112","DOI":"10.18080\/jtde.v12n1.945","volume":"12","author":"R Jallouli","year":"2024","unstructured":"Jallouli, R., Bach Tobji, M.A., Soares, A.M., Casais, B., Belkhir, M.: Editorial: Emerging technologies and innovation for digital economy and transformation. Journal of Telecommunications and the Digital Economy 12(1), 112\u2013123 (2024)","journal-title":"Journal of Telecommunications and the Digital Economy"},{"key":"6164_CR27","unstructured":"Javaid, H. A. (2024). Ai-driven predictive analytics in finance: Transforming risk assessment and decision-making. Advances in Computer Sciences, 7(1). https:\/\/academicpinnacle.com\/index.php\/acs"},{"key":"6164_CR28","unstructured":"John P.: What\u2019s DeepSeek, China\u2019s AI startup sending shockwaves through global tech?, Al Jazeera, (2025). https:\/\/www.aljazeera.com\/economy\/2025\/1\/28\/why-chinas-ai-startup-deepseek-is-sending-shockwaves-through-global-tech"},{"key":"6164_CR29","doi-asserted-by":"publisher","unstructured":"Kirubakaran, A. M., Saha, S., Mazumder, A., Kodali, R. K., Butra, L., & Eswararaj, D. (2025, December). Hybrid Time Series and Sentiment Analysis for Stock Forecasting on Distributed Big Data Platforms. In 2025 International Conference on Computer and Applications (ICCA) (pp. 1-6). IEEE. https:\/\/doi.org\/10.1038\/s41598-026-41985-3","DOI":"10.1038\/s41598-026-41985-3"},{"issue":"2","key":"6164_CR30","doi-asserted-by":"publisher","first-page":"409","DOI":"10.2308\/acch-51065","volume":"29","author":"JP Krahel","year":"2015","unstructured":"Krahel, J.P., Titera, W.R.: Consequences of big data and formalization on accounting and auditing standards. Accounting Horizons 29(2), 409\u2013422 (2015). https:\/\/doi.org\/10.2308\/acch-51065","journal-title":"Accounting Horizons"},{"key":"6164_CR31","doi-asserted-by":"publisher","unstructured":"Kumar, S., Sharma, D., Rao, S., Lim, W.M., Mangla, S.K.: Past, present, and future of sustainable finance: insights from big data analytics through machine learning of scholarly research. Ann. Oper. Res. 1\u201344, (2022). https:\/\/doi.org\/10.1007\/s10479-021-04410-8","DOI":"10.1007\/s10479-021-04410-8"},{"issue":"1","key":"6164_CR32","doi-asserted-by":"publisher","DOI":"10.1007\/s44196-024-00680-9","volume":"17","author":"J Kumarappan","year":"2024","unstructured":"Kumarappan, J., Rajasekar, E., Vairavasundaram, S., Kotecha, K., Kulkarni, A.: Federated Learning Enhanced MLP\u2013LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction. International Journal of Computational Intelligence Systems 17(1), 267 (2024). https:\/\/doi.org\/10.1007\/s44196-024-00680-9","journal-title":"International Journal of Computational Intelligence Systems"},{"issue":"1","key":"6164_CR33","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1007\/s12652-023-04570-4","volume":"2","author":"SM Lundberg","year":"2020","unstructured":"Lundberg, S.M., Erion, G., Chen, H., DeGrave, A., Prutkin, J.M., Nair, B., Lee, S.I.: From local explanations to global understanding with explainable AI for trees. Nature machine intelligence 2(1), 56\u201367 (2020). https:\/\/doi.org\/10.1007\/s12652-023-04570-4","journal-title":"Nature machine intelligence"},{"issue":"42","key":"6164_CR34","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-021-14792-8","volume":"28","author":"Y Latif","year":"2021","unstructured":"Latif, Y., Shunqi, G., Bashir, S., Iqbal, W., Ali, S., Ramzan, M.: COVID-19 and stock exchange return variation: empirical evidences from econometric estimation. Environ. Sci. Pollut. Res. Int. 28(42), 60019 (2021). https:\/\/doi.org\/10.1007\/s11356-021-14792-8","journal-title":"Environ. Sci. Pollut. Res. Int."},{"key":"6164_CR35","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.neucom.2020.02.024","volume":"396","author":"Y Lei","year":"2020","unstructured":"Lei, Y., Du, W., Hu, Q.: Face sketch-to-photo transformation with multi-scale self-attention GAN. Neurocomputing 396, 13\u201323 (2020). https:\/\/doi.org\/10.1016\/j.neucom.2020.02.024","journal-title":"Neurocomputing"},{"issue":"2","key":"6164_CR36","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1109\/tkde.2017.2763144","volume":"30","author":"Q Li","year":"2017","unstructured":"Li, Q., Chen, Y., Wang, J., Chen, Y., Chen, H.: Web media and stock markets: A survey and future directions from a big data perspective. IEEE Trans. Knowl. Data Eng. 30(2), 381\u2013399 (2017). https:\/\/doi.org\/10.1109\/tkde.2017.2763144","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"6164_CR37","first-page":"429","volume":"2","author":"T Li","year":"2020","unstructured":"Li, T., Sahu, A.K., Zaheer, M., Sanjabi, M., Talwalkar, A., Smith, V.: Federated optimization in heterogeneous networks. Proceedings of Machine learning and systems 2, 429\u2013450 (2020)","journal-title":"Proceedings of Machine learning and systems"},{"issue":"3","key":"6164_CR38","doi-asserted-by":"publisher","first-page":"243","DOI":"10.69554\/UBKI3139","volume":"8","author":"P Luehr","year":"2025","unstructured":"Luehr, P., Reilly, B.: Data minimisation: A crucial pillar of cyber security. Cyber Security: A Peer-Reviewed Journal 8(3), 243\u2013254 (2025). https:\/\/doi.org\/10.69554\/UBKI3139","journal-title":"Cyber Security: A Peer-Reviewed Journal"},{"key":"6164_CR39","doi-asserted-by":"publisher","DOI":"10.1038\/s41558-025-02244-x","author":"A Mandel","year":"2025","unstructured":"Mandel, A., Battiston, S., Monasterolo, I.: Mapping global financial risks under climate change. Nat. Clim. Chang. (2025). https:\/\/doi.org\/10.1038\/s41558-025-02244-x","journal-title":"Nat. Clim. Chang."},{"issue":"3","key":"6164_CR40","first-page":"555","volume":"68","author":"DJ Marcus","year":"2018","unstructured":"Marcus, D.J.: The data breach dilemma. Duke law journal 68(3), 555\u2013593 (2018)","journal-title":"Duke law journal"},{"key":"6164_CR41","unstructured":"McMahan, B., Moore, E., Ramage, D., Hampson, S., & Arcas, B. A.: Communication-efficient learning of deep networks from decentralized data. In Artificial intelligence and statistics (pp. 1273-1282). Pmlr. (2015) https:\/\/proceedings.mlr.press\/v54\/mcmahan17a.html"},{"issue":"2","key":"6164_CR42","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1111\/ecin.13195","volume":"62","author":"S Mukanjari","year":"2024","unstructured":"Mukanjari, S., Sterner, T.: Do markets Trump politics? Fossil and renewable market reactions to major political events. Econ. Inq. 62(2), 805\u2013836 (2024). https:\/\/doi.org\/10.1111\/ecin.13195","journal-title":"Econ. Inq."},{"key":"6164_CR43","unstructured":"M\u00f6llers, Thomas M.J., European Legislative Practice 2.0: Dynamic Harmonisation of Capital Markets Law \u2014 MiFID II and PRIIP (November 2015). 31 B.F.L.R. 141 \u2013 176 (2015), Available at SSRN: https:\/\/ssrn.com\/abstract=2732522"},{"key":"6164_CR44","doi-asserted-by":"publisher","DOI":"10.1007\/s11069-025-07168-5","author":"MZ Naser","year":"2025","unstructured":"Naser, M.Z., Kodur, V.: Vulnerability of structures and infrastructure to wildfires: a perspective into assessment and mitigation strategies. Nat. Hazards (2025). https:\/\/doi.org\/10.1007\/s11069-025-07168-5","journal-title":"Nat. Hazards"},{"key":"6164_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119640","volume":"219","author":"N Nazareth","year":"2023","unstructured":"Nazareth, N., Reddy, Y.V.R.: Financial applications of machine learning: A literature review. Expert Systems with Applications 219, 119640 (2023). https:\/\/doi.org\/10.1016\/j.eswa.2023.119640","journal-title":"Expert Systems with Applications"},{"issue":"10","key":"6164_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2023.101820","volume":"35","author":"A Nazir","year":"2023","unstructured":"Nazir, A., He, J., Zhu, N., Wajahat, A., Ma, X., Ullah, F., Pathan, M.S.: Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets. Journal of King Saud University-Computer and Information Sciences 35(10), 101820 (2023). https:\/\/doi.org\/10.1016\/j.jksuci.2023.101820","journal-title":"Journal of King Saud University-Computer and Information Sciences"},{"issue":"2","key":"6164_CR47","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., Wajahat, A., Ullah, F., Qureshi, S., Pathan, M.S.: Collaborative threat intelligence: Enhancing IoT security through blockchain and machine learning integration. Journal of King Saud University-Computer and Information Sciences 36(2), 101939 (2024). https:\/\/doi.org\/10.1016\/j.jksuci.2024.101939","journal-title":"Journal of King Saud University-Computer and Information Sciences"},{"issue":"6","key":"6164_CR48","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., Anwar, M.S., Pathan, M.S.: Enhancing IoT security: a collaborative framework integrating federated learning, dense neural networks, and blockchain. Clust. Comput. 27(6), 8367\u20138392 (2024). https:\/\/doi.org\/10.1007\/s10586-024-04436-0","journal-title":"Clust. Comput."},{"issue":"6","key":"6164_CR49","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., Wajahat, A., Ullah, F., Qureshi, S., Pathan, M.S.: Empirical evaluation of ensemble learning and hybrid CNN-LSTM for IoT threat detection on heterogeneous datasets: A. Nazir et al. The Journal of Supercomputing 81(6), 775 (2025). https:\/\/doi.org\/10.1007\/s11227-025-07255-1","journal-title":"The Journal of Supercomputing"},{"issue":"1","key":"6164_CR50","doi-asserted-by":"publisher","first-page":"1968","DOI":"10.30574\/ijsra.2024.11.1.0267","volume":"11","author":"CC Okoye","year":"2024","unstructured":"Okoye, C.C., Nwankwo, E.E., Usman, F.O., Mhlongo, N.Z., Odeyemi, O., Ike, C.U.: Securing financial data storage: A review of cybersecurity challenges and solutions. International Journal of Science and Research Archive 11(1), 1968\u20131983 (2024). https:\/\/doi.org\/10.30574\/ijsra.2024.11.1.0267","journal-title":"International Journal of Science and Research Archive"},{"issue":"2","key":"6164_CR51","doi-asserted-by":"publisher","first-page":"1969","DOI":"10.30574\/wjarr.2024.21.2.0444","volume":"21","author":"O Olubusola","year":"2024","unstructured":"Olubusola, O., Mhlongo, N.Z., Daraojimba, D.O., Ajayi-Nifise, A.O., Falaiye, T.: Machine learning in financial forecasting: A US review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets. World Journal of Advanced Research and Reviews 21(2), 1969\u20131984 (2024). https:\/\/doi.org\/10.30574\/wjarr.2024.21.2.0444","journal-title":"World Journal of Advanced Research and Reviews"},{"key":"6164_CR52","doi-asserted-by":"publisher","first-page":"49","DOI":"10.5539\/cis.v17n1p49","volume":"17","author":"OS Owolabi","year":"2024","unstructured":"Owolabi, O.S., Uche, P.C., Adeniken, N.T., Ihejirika, C., Islam, R.B., Chhetri, B.J.T., Jung, B.: Ethical implication of artificial intelligence (AI) adoption in financial decision making. Comput. Inf. Sci 17, 49\u201356 (2024). https:\/\/doi.org\/10.5539\/cis.v17n1p49","journal-title":"Comput. Inf. Sci"},{"issue":"4","key":"6164_CR53","doi-asserted-by":"publisher","first-page":"4529","DOI":"10.1007\/s12652-023-04570-4","volume":"14","author":"S Pourroostaei Ardakani","year":"2023","unstructured":"Pourroostaei Ardakani, S., Du, N., Lin, C., Yang, J.C., Bi, Z., Chen, L.: A federated learning-enabled predictive analysis to forecast stock market trends. Journal of Ambient Intelligence and Humanized Computing 14(4), 4529\u20134535 (2023). https:\/\/doi.org\/10.1007\/s12652-023-04570-4","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"6164_CR54","unstructured":"Raditio Ghifiardi. (2025). How DeepSeek Shook the Nasdaq and Redefined the Market: What Happened and What\u2019s Next? https:\/\/moderndiplomacy.eu\/2025\/01\/30\/how-deepseek-shook-the-nasdaq-and-redefined-the-market-what-happened-and-whats-next\/ (January 30, 2025)"},{"key":"6164_CR55","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2025.066366","author":"S Reno","year":"2025","unstructured":"Reno, S., Roy, K.: Navigating the blockchain trilemma: A review of recent advances and emerging solutions in decentralization, security, and scalability optimization. Computers, Materials & Continua (2025). https:\/\/doi.org\/10.32604\/cmc.2025.066366","journal-title":"Computers, Materials & Continua"},{"issue":"1","key":"6164_CR56","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0318166","volume":"20","author":"M Schuster","year":"2025","unstructured":"Schuster, M., Kr\u00fcger, J., Lueg, R.: Physical climate risk: Stock price reactions to the historically most extreme European and United States heat waves since 1979. PLoS ONE 20(1), e0318166 (2025). https:\/\/doi.org\/10.1371\/journal.pone.0318166","journal-title":"PLoS ONE"},{"issue":"4","key":"6164_CR57","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1049\/sfw2.12092","volume":"17","author":"NN Sakhare","year":"2023","unstructured":"Sakhare, N.N., Shaik, I.S., Saha, S.: Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm. IET Software 17(4), 705\u2013716 (2023). https:\/\/doi.org\/10.1049\/sfw2.12092","journal-title":"IET Software"},{"issue":"1","key":"6164_CR58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/jsan13010001","volume":"13","author":"M Shaheen","year":"2023","unstructured":"Shaheen, M., Farooq, M.S., Umer, T.: Reduction in data imbalance for client-side training in federated learning for the prediction of stock market prices. J. Sens. Actuator Netw. 13(1), 1 (2023). https:\/\/doi.org\/10.3390\/jsan13010001","journal-title":"J. Sens. Actuator Netw."},{"key":"6164_CR59","doi-asserted-by":"publisher","first-page":"95949","DOI":"10.1109\/ACCESS.2021.3094089","volume":"9","author":"M Savi","year":"2021","unstructured":"Savi, M., Olivadese, F.: Short-term energy consumption forecasting at the edge: A federated learning approach. IEEE access 9, 95949\u201395969 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3094089","journal-title":"IEEE access"},{"key":"6164_CR60","doi-asserted-by":"publisher","DOI":"10.1108\/jcefts-03-2024-0026","author":"RA Salem","year":"2025","unstructured":"Salem, R.A., Lila, S., Lewaaelhamd, I.: The impact of Russian\u2013Ukrainian conflict on international financial markets: a comparative analysis of oil-importing and oil-exporting countries. Journal of Chinese Economic and Foreign Trade Studies (2025). https:\/\/doi.org\/10.1108\/jcefts-03-2024-0026","journal-title":"Journal of Chinese Economic and Foreign Trade Studies"},{"key":"6164_CR61","doi-asserted-by":"publisher","unstructured":"Samuel, A., & Edegbe, G. N. (2024). A Systematic Review of Centralized and Decentralized Machine Learning Models: Security Concerns, Defenses and Future Directions. NIPES-Journal of Science and Technology Research, 6(4). https:\/\/doi.org\/10.5281\/zenodo.14681449","DOI":"10.5281\/zenodo.14681449"},{"issue":"112","key":"6164_CR62","first-page":"1","volume":"23","author":"JR Smith","year":"2022","unstructured":"Smith, J.R., Birchfield, S.T., Gupta, M.: Parameter variance as a convergence diagnostic for federated learning. Journal of Machine Learning Research 23(112), 1\u201335 (2022)","journal-title":"Journal of Machine Learning Research"},{"key":"6164_CR63","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/B:STCO.0000035301.49549.88","volume":"14","author":"AJ Smola","year":"2004","unstructured":"Smola, A.J., Sch\u00f6lkopf, B.: A tutorial on support vector regression. Statistics and Computing 14, 199\u2013222 (2004)","journal-title":"Statistics and Computing"},{"key":"6164_CR64","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1016\/j.procs.2024.10.343","volume":"245","author":"LM Soegianto","year":"2024","unstructured":"Soegianto, L.M., Hinandra, A.T., Suri, P.A., Fajar, M.: Comparison of model performance on housing business using linear regression, random forest regressor, svr, and neural network. Procedia Computer Science 245, 1139\u20131145 (2024). https:\/\/doi.org\/10.1016\/j.procs.2024.10.343","journal-title":"Procedia Computer Science"},{"key":"6164_CR65","doi-asserted-by":"publisher","unstructured":"Sowmya, G., Sridevi, R., & Shiramshetty, S. G. (2024). Transforming Finance: Exploring the Role of Blockchain and Smart Contracts. In Fintech Applications in Islamic Finance: AI, Machine Learning, and Blockchain Techniques (pp. 255-271). IGI Global. https:\/\/doi.org\/10.4018\/979-8-3693-1038-0.ch017","DOI":"10.4018\/979-8-3693-1038-0.ch017"},{"key":"6164_CR66","unstructured":"Stephane H. Maes \"The Circle of Life for LLMs. Was the Reaction to DeepSeek Justified?\" (2025). https:\/\/doi.org\/10.5281\/zenodo.14838733 , https:\/\/shmaes.wordpress.com\/2025\/02\/15\/the-circle-of-life-for-llms-was-the-reaction-to-deepseek-justified\/, February 5, 2025"},{"key":"6164_CR67","volume-title":"Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world","author":"D Tapscott","year":"2016","unstructured":"Tapscott, D., Tapscott, A.: Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world. Penguin (2016)"},{"issue":"5","key":"6164_CR68","doi-asserted-by":"publisher","first-page":"611","DOI":"10.36676\/jrps.v13.i5.1530","volume":"13","author":"KK Tirupati","year":"2022","unstructured":"Tirupati, K.K., Mahadik, S., Khair, M.A., Goel, O., Jain, A.: Optimizing machine learning models for predictive analytics in cloud environments. International Journal for Research Publication & Seminar 13(5), 611\u2013634 (2022). https:\/\/doi.org\/10.36676\/jrps.v13.i5.1530","journal-title":"International Journal for Research Publication &amp; Seminar"},{"issue":"4","key":"6164_CR69","doi-asserted-by":"publisher","first-page":"3637","DOI":"10.1109\/TSG.2021.3066577","volume":"12","author":"Y Wang","year":"2021","unstructured":"Wang, Y., Bennani, I.L., Liu, X., Sun, M., Zhou, Y.: Electricity consumer characteristics identification: A federated learning approach. IEEE Transactions on Smart Grid 12(4), 3637\u20133647 (2021). https:\/\/doi.org\/10.1109\/TSG.2021.3066577","journal-title":"IEEE Transactions on Smart Grid"},{"key":"6164_CR70","doi-asserted-by":"publisher","unstructured":"Wang, H., Kaplan, Z., Niu, D., Li, B.: Optimizing federated learning on non-IID data with reinforcement learning. IEEE INFOCOM 1698\u20131707, (2020). https:\/\/doi.org\/10.1109\/INFOCOM41043.2020.9155494","DOI":"10.1109\/INFOCOM41043.2020.9155494"},{"key":"6164_CR71","unstructured":"World Economic Forum. (2020). Data for Humanity: A Global Governance Framework. Retrieved from https:\/\/www.weforum.org\/publications\/the-global-risks-report-2020\/"},{"key":"6164_CR72","doi-asserted-by":"publisher","DOI":"10.1049\/blc2.12067","author":"H Wu","year":"2024","unstructured":"Wu, H., Yao, Q., Liu, Z., Huang, B., Zhuang, Y., Tang, H., Liu, E.: Blockchain for finance: A survey. IET Blockchain (2024). https:\/\/doi.org\/10.1049\/blc2.12067","journal-title":"IET Blockchain"},{"key":"6164_CR73","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/j.iotcps.2023.04.001","volume":"3","author":"JPA Yaacoub","year":"2023","unstructured":"Yaacoub, J.P.A., Noura, H.N., Salman, O.: Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions. Internet of Things and Cyber-Physical Systems 3, 155\u2013179 (2023). https:\/\/doi.org\/10.1016\/j.iotcps.2023.04.001","journal-title":"Internet of Things and Cyber-Physical Systems"},{"issue":"3","key":"6164_CR74","doi-asserted-by":"publisher","first-page":"125","DOI":"10.18034\/abr.v11i3.694","volume":"11","author":"SR Yerram","year":"2021","unstructured":"Yerram, S.R., Goda, D.R., Mahadasa, R., Mallipeddi, S.R., Varghese, A., Ande, J.R.P.K., Surarapu, P., Dekkati, S.: The role of blockchain technology in enhancing financial security amidst digital transformation. Asian Bus. Rev 11(3), 125\u2013134 (2021). https:\/\/doi.org\/10.18034\/abr.v11i3.694","journal-title":"Asian Bus. Rev"},{"key":"6164_CR75","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L. A Collective Intelligence to Predict Stock Market Indices Applying an Optimized Hybrid Ensemble Learning Model. In: Nguyen, N.T., et al. Computational Collective Intelligence. ICCCI 2024. Lecture Notes in Computer Science, vol 14810. Springer, Cham. (2024). https:\/\/doi.org\/10.1007\/978-3-031-70816-9_6","DOI":"10.1007\/978-3-031-70816-9_6"},{"issue":"1","key":"6164_CR76","doi-asserted-by":"publisher","first-page":"612","DOI":"10.18080\/jtde.v12n1.843","volume":"12","author":"Z Zouaghia","year":"2024","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L.: A novel AutoCNN model for stock market index prediction. Journal of Telecommunications and the Digital Economy 12(1), 612\u2013636 (2024)","journal-title":"Journal of Telecommunications and the Digital Economy"},{"key":"6164_CR77","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Kodia, Z., & Said, L. B. Pred-IFDSS: an intelligent financial decision support system based on machine learning models. In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 67-72). IEEE. (2024). https:\/\/doi.org\/10.1109\/CoDIT62066.2024.10708156","DOI":"10.1109\/CoDIT62066.2024.10708156"},{"key":"6164_CR78","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-024-20270-3","author":"Z Zouaghia","year":"2024","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L.: Predicting the stock market prices using a machine learning-based framework during crisis periods. Multimedia Tools and Applications (2024). https:\/\/doi.org\/10.1007\/s11042-024-20270-3","journal-title":"Multimedia Tools and Applications"},{"key":"6164_CR79","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Aouina, Z. K., & Said, L. B. Stock movement prediction based on technical indicators applying hybrid machine learning models. In 2023 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1-4). IEEE. (2023). https:\/\/doi.org\/10.1109\/ISNCC58260.2023.10323971","DOI":"10.1109\/ISNCC58260.2023.10323971"},{"key":"6164_CR80","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L. A machine learning-based trading strategy integrating technical analysis and multi-agent simulation. In: Mathieu, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Digital Twins: The PAAMS Collection. PAAMS 2024. Lecture Notes in Computer Science, vol 15157. Springer, Cham. (2025). https:\/\/doi.org\/10.1007\/978-3-031-70415-4_26","DOI":"10.1007\/978-3-031-70415-4_26"},{"key":"6164_CR81","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L. TunPredML: A machine learning-based financial decision support system for crisis-aware stock market forecasting and risk mitigation: empirical insights from the Tunisian stock market. Comput. Econ. 1\u201362, (2026). https:\/\/doi.org\/10.1007\/s10614-025-11221-7","DOI":"10.1007\/s10614-025-11221-7"},{"issue":"6","key":"6164_CR82","doi-asserted-by":"publisher","first-page":"5775","DOI":"10.1007\/s41060-025-00811-1","volume":"20","author":"Z Zouaghia","year":"2025","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L.: SMAPF-HNNA: A novel stock market analysis and prediction framework using hybrid neural network architectures across major US indices. International Journal of Data Science and Analytics 20(6), 5775\u20135811 (2025). https:\/\/doi.org\/10.1007\/s41060-025-00811-1","journal-title":"International Journal of Data Science and Analytics"},{"key":"6164_CR83","doi-asserted-by":"publisher","unstructured":"Zouaghia, Z., Kodia, Z., & Ben Said, L. A novel approach for dynamic portfolio management integrating K-means clustering, mean-variance optimization, and reinforcement learning: Z. Zouaghia et al. Knowledge and Information Systems, 1\u201373 (2025). https:\/\/doi.org\/10.1007\/s10115-025-02475-6","DOI":"10.1007\/s10115-025-02475-6"},{"issue":"1","key":"6164_CR84","doi-asserted-by":"publisher","DOI":"10.1007\/s41060-026-01085-x","volume":"22","author":"Z Zouaghia","year":"2026","unstructured":"Zouaghia, Z., Kodia, Z., Ben Said, L.: Simulated quantum feature maps for interpretable credit risk prediction: a comparative benchmark study. International Journal of Data Science and Analytics 22(1), 111 (2026). https:\/\/doi.org\/10.1007\/s41060-026-01085-x","journal-title":"International Journal of Data Science and Analytics"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06164-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-026-06164-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06164-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T18:31:27Z","timestamp":1785004287000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-026-06164-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":85,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["6164"],"URL":"https:\/\/doi.org\/10.1007\/s10586-026-06164-z","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"4 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"364"}}