{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T07:00:29Z","timestamp":1764572429818,"version":"3.46.0"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003065","name":"University of Vienna","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003065","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Inf. Secur."],"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Privacy-Preserving Data Mining (PPDM) requires methods that safeguard sensitive information while retaining the analytical value of data. This paper presents GAFSOM (Genetic-Fuzzy Algorithm for Self-Organizing Maps), a meta-heuristic anonymization framework that combines fuzzy sets with genetic optimization to balance privacy protection and clustering fidelity. By selectively applying fuzzification to high-risk attributes and leveraging genetic search to minimize distortion, GAFSOM preserves the topological structure of Self-Organizing Maps, an aspect often overlooked in existing anonymization techniques. The approach is evaluated on two benchmark datasets, UCI Adult and Bank Marketing, against a range of baselines including traditional SOM, k-anonymity, Fuzzy C-Means, genetic clustering, and differential privacy-enhanced SOM. Experimental results demonstrate that GAFSOM achieves superior clustering accuracy, lower information loss, and reduced topographic error, while maintaining competitive computational efficiency. Moreover, structural analyses confirm that the method preserves SOM\u2019s neighborhood relationships with minimal distortion even under anonymization. These findings highlight GAFSOM as an effective and scalable solution for privacy-preserving, topology-sensitive data mining tasks.<\/jats:p>","DOI":"10.1007\/s10207-025-01138-5","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T17:24:33Z","timestamp":1760549073000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GAFSOM: A Privacy-Preserving Machine Learning Algorithm for SOM Clustering"],"prefix":"10.1007","volume":"24","author":[{"given":"Fatemeh","family":"Amiri","sequence":"first","affiliation":[]},{"given":"Gerald","family":"Quirchmayr","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,15]]},"reference":[{"key":"1138_CR1","unstructured":"Amiri, F., Quirchmayr, G., Kieseberg, P.: \"Sensitive data anonymization using genetic algorithms for SOM-based clustering.\" 21-29, (2018)"},{"key":"1138_CR2","first-page":"609","volume":"2","author":"F Amiri","year":"2018","unstructured":"Amiri, F., Quirchmayr, G., Kieseberg, P.: A Machine Learning Approach for Privacy-preservation in E-business Applications. In ICETE 2, 609\u2013618 (2018)","journal-title":"In ICETE"},{"key":"1138_CR3","doi-asserted-by":"crossref","unstructured":"Gan, G., Ma, C., Wu, J.: Data clustering: theory, algorithms, and applications. Society for Industrial and Applied Mathematics, (2020)","DOI":"10.1137\/1.9781611976335"},{"key":"1138_CR4","doi-asserted-by":"crossref","unstructured":"Han, S., Ng, W. K.: \"Privacy-preserving self-organizing map.\" In International Conference on Data Warehousing and Knowledge Discovery, pp. 428-437. Berlin, Heidelberg: Springer Berlin Heidelberg, (2007)","DOI":"10.1007\/978-3-540-74553-2_40"},{"key":"1138_CR5","unstructured":"Simon, H.: Neural networks: a comprehensive foundation. Prentice Hall PTR, (1998)"},{"key":"1138_CR6","doi-asserted-by":"crossref","unstructured":"Kimmo, K.: \"Topology preservation in self-organizing maps.\" In Proceedings of International Conference on Neural Networks (ICNN\u201996), 1, 294-299. IEEE, (1996)","DOI":"10.1109\/ICNN.1996.548907"},{"key":"1138_CR7","volume-title":"Introduction to data mining Pearson Education India","author":"P-N Tan","year":"2018","unstructured":"Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to data mining Pearson Education India. New Delhi, India, Indian Nursing Council (2018)"},{"issue":"4","key":"1138_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1749603.1749605","volume":"42","author":"Benjamin CM Fung","year":"2010","unstructured":"Fung, Benjamin CM., Wang, Ke., Chen, Rui, Philip, S Yu.: Privacy-preserving data publishing: A survey of recent developments. ACM Computing Surveys (Csur) 42(4), 1\u201353 (2010)","journal-title":"ACM Computing Surveys (Csur)"},{"key":"1138_CR9","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1016\/j.jbi.2014.06.002","volume":"50","author":"A Gkoulalas-Divanis","year":"2014","unstructured":"Gkoulalas-Divanis, A., Loukides, G., Sun, J.: Publishing data from electronic health records while preserving privacy: A survey of algorithms. J. Biomed. Inform. 50, 4\u201319 (2014)","journal-title":"J. Biomed. Inform."},{"key":"1138_CR10","first-page":"232","volume-title":"Adaptation in artificial and natural systems","author":"J Holland","year":"1975","unstructured":"Holland, J.: Adaptation in artificial and natural systems, p. 232. The University of Michigan Press, Ann Arbor (1975)"},{"key":"1138_CR11","doi-asserted-by":"crossref","unstructured":"Lotfi, A. Z.: \"Fuzzy logic, neural networks, and soft computing.\" In Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh, pp. 775-782 (1996)","DOI":"10.1142\/9789814261302_0040"},{"key":"1138_CR12","unstructured":"Moro, S., Laureano, R., Cortez, P.: \"Using data mining for bank direct marketing: An application of the crisp-dm methodology.\" In Proceedings of the European Simulation and Modelling Conference-ESM, vol. 2011. (2011)"},{"key":"1138_CR13","doi-asserted-by":"crossref","unstructured":"Jeffrey, R. S.: \"Adaptation in natural and artificial systems (John H. Holland).\" 529 (1976)","DOI":"10.1137\/1018105"},{"key":"1138_CR14","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Srikant, R.: \"Privacy-preserving data mining.\" In Proceedings of the 2000 ACM SIGMOD international conference on Management of data. 439-450. (2000)","DOI":"10.1145\/342009.335438"},{"key":"1138_CR15","unstructured":"Xu, R., Baracaldo, N., Joshi, J.: \"Privacy-preserving machine learning: Methods, challenges and directions.\" arXiv preprint arXiv:2108.04417 (2021)"},{"issue":"2","key":"1138_CR16","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1007\/s10207-023-00783-y","volume":"23","author":"K Ince","year":"2024","unstructured":"Ince, K.: Exploring the potential of deep learning and machine learning techniques for randomness analysis to enhance security on IoT. Int. J. Inf. Secur. 23(2), 1117\u20131130 (2024)","journal-title":"Int. J. Inf. Secur."},{"key":"1138_CR17","doi-asserted-by":"crossref","unstructured":"Sarhan, M., Layeghy, S., Gallagher, M., Portmann, M.: \"From Zero-Shot Machine Learning to Zero-Day Attack Detection. arXiv 2021.\" arXiv preprint arXiv:2109.14868","DOI":"10.21203\/rs.3.rs-2097775\/v1"},{"key":"1138_CR18","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1016\/j.ins.2019.05.053","volume":"527","author":"MA Chamikara","year":"2020","unstructured":"Chamikara, M.A., Pathum, P.B., Liu, D., Camtepe, S., Khalil, I.: Efficient privacy preservation of big data for accurate data mining. Inf. Sci. 527, 420\u2013443 (2020)","journal-title":"Inf. Sci."},{"issue":"3","key":"1138_CR19","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.1016\/j.ejor.2005.03.039","volume":"174","author":"SA Mingoti","year":"2006","unstructured":"Mingoti, S.A., Lima, J.O.: Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms. Eur. J. Oper. Res. 174(3), 1742\u20131759 (2006)","journal-title":"Eur. J. Oper. Res."},{"issue":"1","key":"1138_CR20","doi-asserted-by":"publisher","first-page":"e1480","DOI":"10.1002\/wics.1480","volume":"12","author":"Ferraro Maria Brigida","year":"2020","unstructured":"Maria Brigida, Ferraro: \u201cSoft clustering\u2019\u2019. Wiley Interdisciplinary Reviews: Computational Statistics 12(1), e1480 (2020)","journal-title":"Wiley Interdisciplinary Reviews: Computational Statistics"},{"issue":"1","key":"1138_CR21","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1007\/BF00337288","volume":"43","author":"T Kohonen","year":"1982","unstructured":"Kohonen, T.: Self-organized formation of topologically correct feature maps. Biol. Cybern. 43(1), 59\u201369 (1982)","journal-title":"Biol. Cybern."},{"key":"1138_CR22","doi-asserted-by":"crossref","unstructured":"Beyza, B., Canard, S., Ermis, O., M\u00f6llering, H., \u00d6nen, M., Schneider, T.: \"Privacy-preserving density-based clustering.\" In Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security, pp. 658-671. 2021","DOI":"10.1145\/3433210.3453104"},{"key":"1138_CR23","unstructured":"Gorgonio, F., Costa, J.: \"Privacy-preserving clustering on distributed databases: a review and some contributions.\" Self Organizing Maps-Applications and Novel Algorithm Design (2011)"},{"issue":"3","key":"1138_CR24","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1007\/s42979-021-00592-x","volume":"2","author":"Iqbal H Sarker","year":"2021","unstructured":"Sarker, Iqbal H.: Machine learning: Algorithms, real-world applications and research directions. SN computer science 2(3), 160 (2021)","journal-title":"SN computer science"},{"issue":"4","key":"1138_CR25","doi-asserted-by":"publisher","first-page":"2392","DOI":"10.1109\/COMST.2017.2727878","volume":"19","author":"Paulo Valente Klaine","year":"2017","unstructured":"Klaine, Paulo Valente, Imran, Muhammad Ali, Onireti, Oluwakayode, Souza, Richard Demo: A survey of machine learning techniques applied to self-organizing cellular networks. IEEE Communications Surveys & Tutorials 19(4), 2392\u20132431 (2017)","journal-title":"IEEE Communications Surveys & Tutorials"},{"key":"1138_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103605","volume":"137","author":"E Mestari","year":"2024","unstructured":"Mestari, E., Zohra, S., Lenzini, G., Demirci, H.: Preserving data privacy in machine learning systems. Computers & Security 137, 103605 (2024)","journal-title":"Computers & Security"},{"key":"1138_CR27","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.neucom.2019.11.041","volume":"384","author":"A Boulemtafes","year":"2020","unstructured":"Boulemtafes, A., Derhab, A., Challal, Y.: A review of privacy-preserving techniques for deep learning. Neurocomputing 384, 21\u201345 (2020)","journal-title":"Neurocomputing"},{"issue":"3","key":"1138_CR28","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1016\/S0957-4174(03)00067-8","volume":"25","author":"Tae Hyup Roh","year":"2003","unstructured":"Roh, Tae Hyup, Kyong Joo, Oh., Han, Ingoo: The collaborative filtering recommendation based on SOM cluster-indexing CBR. Expert systems with applications 25(3), 413\u2013423 (2003)","journal-title":"Expert systems with applications"},{"key":"1138_CR29","doi-asserted-by":"crossref","unstructured":"Han, S., Ng, W. K.: \"Privacy-preserving self-organizing map.\" In International Conference on Data Warehousing and Knowledge Discovery, pp. 428-437. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007","DOI":"10.1007\/978-3-540-74553-2_40"},{"key":"1138_CR30","doi-asserted-by":"crossref","unstructured":"Malik, M. B., Asger, M., Ali, R., Arif, T.:\"Preserving Privacy and Optimizing Neural Network Classification by using a Mix of Soft Computing Techniques.\" International Journal of Computer Applications 147, no. 10 (2016)","DOI":"10.5120\/ijca2016911188"},{"issue":"7453","key":"1138_CR31","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1038\/498255a","volume":"498","author":"V Marx","year":"2013","unstructured":"Marx, V.: The big challenges of big data. Nature 498(7453), 255\u2013260 (2013)","journal-title":"Nature"},{"issue":"6","key":"1138_CR32","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.1007\/s10207-022-00607-5","volume":"21","author":"M Templ","year":"2022","unstructured":"Templ, M., Sariyar, M.: A systematic overview on methods to protect sensitive data provided for various analyses. Int. J. Inf. Secur. 21(6), 1233\u20131246 (2022)","journal-title":"Int. J. Inf. Secur."},{"key":"1138_CR33","doi-asserted-by":"publisher","first-page":"3073","DOI":"10.1007\/s11227-015-1501-1","volume":"72","author":"Lisbeth Rodr\u00edguez-Mazahua","year":"2016","unstructured":"Rodr\u00edguez-Mazahua, Lisbeth, Rodr\u00edguez-Enr\u00edquez, Cristian-Aar\u00f3n., S\u00e1nchez-Cervantes, Jos\u00e9 Luis., Cervantes, Jair, Garc\u00eda-Alcaraz, Jorge Luis, Alor-Hern\u00e1ndez, Giner: A general perspective of Big Data: applications, tools, challenges and trends. The Journal of Supercomputing 72, 3073\u20133113 (2016)","journal-title":"The Journal of Supercomputing"},{"key":"1138_CR34","doi-asserted-by":"crossref","unstructured":"Haverkamp, I., Sarmah, D. K.: \"Evaluating the merits and constraints of cryptography-steganography fusion: a systematic analysis.\" International Journal of Information Security (2024): 1-29","DOI":"10.21203\/rs.3.rs-3167378\/v1"},{"key":"1138_CR35","unstructured":"Fatemeh, A., Quirchmayr, G.: \"Novel Model for Privacy Preserving in Data Mining using Meta Heuristic Techniques.\" (2019)"},{"key":"1138_CR36","unstructured":"Amiri, F., Quirchmayr, G., Kieseberg, P., Bertone, A., Weippl, E.: \"Efficiently Vectorized Anonymization in Data Mining using Genetic Algorithms.\" (2019)"},{"key":"1138_CR37","doi-asserted-by":"publisher","first-page":"10562","DOI":"10.1109\/ACCESS.2017.2706947","volume":"5","author":"R Mendes","year":"2017","unstructured":"Mendes, R., Vilela, J.P.: Privacy-preserving data mining: methods, metrics, and applications. IEEE Access 5, 10562\u201310582 (2017)","journal-title":"IEEE Access"},{"issue":"2","key":"1138_CR38","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1093\/jamia\/ocv063","volume":"23","author":"Hesha J Duggirala","year":"2016","unstructured":"Duggirala, Hesha J., Tonning, Joseph M., Smith, Ella, Bright, Roselie A., Baker, John D., Ball, Robert, Bell, Carlos, et al.: Use of data mining at the Food and Drug Administration. Journal of the American Medical Informatics Association 23(2), 428\u2013434 (2016)","journal-title":"Journal of the American Medical Informatics Association"},{"key":"1138_CR39","doi-asserted-by":"publisher","first-page":"10562","DOI":"10.1109\/ACCESS.2017.2706947","volume":"5","author":"R Mendes","year":"2017","unstructured":"Mendes, R., Vilela, J.P.: Privacy-preserving data mining: methods, metrics, and applications. IEEE Access 5, 10562\u201310582 (2017)","journal-title":"IEEE Access"},{"issue":"1","key":"1138_CR40","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/791841","volume":"2014","author":"Y Feng","year":"2014","unstructured":"Feng, Y., Wang, Y., Guo, F., Hao, X.: Applications of data mining methods in the integrative medical studies of coronary heart disease: progress and prospect. Evidence-Based Complementary and Alternative Medicine 2014(1), 791841 (2014)","journal-title":"Evidence-Based Complementary and Alternative Medicine"},{"key":"1138_CR41","doi-asserted-by":"crossref","unstructured":"Mohit, D,: \"Machine learning approach to ids: A comprehensive review.\" In 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA), pp. 117-121. IEEE, (2019)","DOI":"10.1109\/ICECA.2019.8822120"},{"key":"1138_CR42","doi-asserted-by":"crossref","unstructured":"Fatemeh, A., Quirchmayr, G.: \"A comparative study on innovative approaches for privacy-preservation in knowledge discovery.\" In Proceedings of the 9th International Conference on Information Management and Engineering, pp. 120-127. (2017)","DOI":"10.1145\/3149572.3149586"},{"key":"1138_CR43","doi-asserted-by":"crossref","unstructured":"Sivanandam, S. N., Deepa, S. N.,Sivanandam, S. N., Deepa, S. N.: \"Genetic algorithm optimization problems\" Introduction to genetic algorithms, pp. 165\u2013209, (2008)","DOI":"10.1007\/978-3-540-73190-0_7"},{"issue":"1","key":"1138_CR44","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s00236-010-0131-6","volume":"48","author":"ME Kabir","year":"2011","unstructured":"Kabir, M.E., Wang, H., Bertino, E.: Efficient \u201csystematic clustering method for k-anonymization\u2019\u2019. Acta Informatica 48(1), 51\u201366 (2011)","journal-title":"Acta Informatica"},{"key":"1138_CR45","unstructured":"Pinot, R., Morvan, A., Yger, F., Gouy-Pailler, C., and Atif, J.: \"Graph-based Clustering under Differential Privacy.\" arXiv preprint arXiv:1803.03831(2018)"},{"key":"1138_CR46","doi-asserted-by":"crossref","unstructured":"Bezdek, J.C.: \"Pattern Recognition with Fuzzy Objective Function Algorithms.\" Springer Science and Business Media, (1981)","DOI":"10.1007\/978-1-4757-0450-1"},{"issue":"9","key":"1138_CR47","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1016\/S0031-3203(99)00137-5","volume":"33","author":"U Maulik","year":"2000","unstructured":"Maulik, U., Bandyopadhyay, S.: Genetic algorithm-based clustering technique. Pattern Recogn. 33(9), 1455\u20131465 (2000)","journal-title":"Pattern Recogn."},{"key":"1138_CR48","doi-asserted-by":"crossref","unstructured":"Liu, J., Liu, Y., Zhang, Y.: \"A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices.\" Security and Communication Networks, Article ID 4945152, (2018)","DOI":"10.1155\/2018\/4945152"},{"key":"1138_CR49","doi-asserted-by":"crossref","unstructured":"Rieke, N., et al.: \u201cThe future of digital health with federated learning. Nature Machine Intelligence\u201d 2(6), 305\u2013311 (2020)","DOI":"10.1038\/s42256-020-0186-1"},{"key":"1138_CR50","unstructured":"ong, T.-P., Yang, K.-T., Lin, C.-W., Wang, S.-L.: \"Evolutionary privacy-preserving data mining.\" 2010 World Automation Congress, IEEE, pp. 1\u20137,"},{"key":"1138_CR51","doi-asserted-by":"crossref","unstructured":"Wu, Yi-Hung., Chiang, Chia-Ming., Chen, Arbee LP.: Hiding sensitive association rules with limited side effects. IEEE Transactions on Knowledge and Data engineering 19(1), 29\u201342 (2006)","DOI":"10.1109\/TKDE.2007.250583"},{"key":"1138_CR52","doi-asserted-by":"crossref","unstructured":"Ahmed G. G.: \"Particle swarm optimization algorithm and its applications: A systematic review.\" Archives of computational methods in engineering, 29, 5, (2022)","DOI":"10.1007\/s11831-021-09694-4"},{"key":"1138_CR53","doi-asserted-by":"publisher","first-page":"10031","DOI":"10.1109\/ACCESS.2022.3142859","volume":"10","author":"TM Shami","year":"2022","unstructured":"Shami, T.M., El-Saleh, A.A., Alswaitti, M., Al-Tashi, Q., Summakieh, M.A., Mirjalili, S.: Particle swarm optimization: A comprehensive survey. IEEE Access 10, 10031\u201310061 (2022)","journal-title":"IEEE Access"},{"key":"1138_CR54","doi-asserted-by":"publisher","first-page":"22991","DOI":"10.1109\/ACCESS.2023.3304889","volume":"12","author":"SN Makhadmeh","year":"2023","unstructured":"Makhadmeh, S.N., Al-Betar, M.A., Doush, I.A., Awadallah, M.A., Kassaymeh, S., Mirjalili, S., Zitar, R.A.: Recent advances in Grey Wolf Optimizer, its versions and application.s. IEEE access 12, 22991\u201323028 (2023)","journal-title":"IEEE access"},{"issue":"18","key":"1138_CR55","doi-asserted-by":"publisher","first-page":"3767","DOI":"10.3390\/electronics12183767","volume":"12","author":"L Zhu","year":"2023","unstructured":"Zhu, L., Lei, T., Mu, J., Mu, J., Cai, Z., Zhang, J.: Differential privacy-based spatial-temporal trajectory clustering scheme for LBSNs. Electronics 12(18), 3767 (2023)","journal-title":"Electronics"},{"key":"1138_CR56","doi-asserted-by":"crossref","unstructured":"Zhou, J., Chen, S., Wu, Y., Li, H., Zhang, B., Zhou, L., Yan, H., Zihang, X., Zhongxiao, L., Ningning, C. and others.: \"PPML-Omics: A privacy-preserving federated machine learning method protects patients\u2019 privacy in omic data\" Science Advances, vol. 10, no. 5, pp. eadh8601, merican Association for the Advancement of Science (2024)","DOI":"10.1126\/sciadv.adh8601"},{"key":"1138_CR57","doi-asserted-by":"crossref","unstructured":"Sarmin, F. J., Sarkar, A. R., Wang, Y., Mohammed, N.: \"Synthetic data: Revisiting the privacy-utility trade-off\" arXiv preprint arXiv:2407.07926, (2024)","DOI":"10.1007\/s10207-025-01072-6"},{"key":"1138_CR58","doi-asserted-by":"crossref","unstructured":"Shamsinejad, E., Banirostam, H., BaniRostam, T., Pedram, M. M., Rahmani, A. M.: \"Providing and evaluating a model for big data anonymization streams by using in-memory processing\" Knowledge and Information Systems, Springer, pp. 1\u201334, (2025)","DOI":"10.1007\/s40745-024-00556-x"},{"issue":"1","key":"1138_CR59","first-page":"253","volume":"12","author":"E Shamsinejad","year":"2025","unstructured":"Shamsinejad, E., Banirostam, T., Pedram, M.M., Rahmani, A.M.: A review of anonymization algorithms and methods in big data. Springer 12(1), 253\u2013279 (2025)","journal-title":"Springer"},{"issue":"1","key":"1138_CR60","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/s40745-024-00556-x","volume":"12","author":"E Shamsinejad","year":"2025","unstructured":"Shamsinejad, E., Banirostam, T., Pedram, M.M., Rahmani, A.M.: Representing a model for the anonymization of big data stream using in-memory processing. Annals of Data Science 12(1), 223\u2013252 (2025)","journal-title":"Annals of Data Science"}],"container-title":["International Journal of Information Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10207-025-01138-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10207-025-01138-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10207-025-01138-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T06:56:23Z","timestamp":1764572183000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10207-025-01138-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":60,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["1138"],"URL":"https:\/\/doi.org\/10.1007\/s10207-025-01138-5","relation":{},"ISSN":["1615-5262","1615-5270"],"issn-type":[{"type":"print","value":"1615-5262"},{"type":"electronic","value":"1615-5270"}],"subject":[],"published":{"date-parts":[[2025,10,15]]},"assertion":[{"value":"3 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 October 2025","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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"223"}}