{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T12:35:01Z","timestamp":1769949301550,"version":"3.49.0"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"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":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-025-04154-3","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T11:46:51Z","timestamp":1753357611000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Phishing Detection and Zero-Trust Verification with Spiking Neural Networks Auto Encoder and Selu Activation"],"prefix":"10.1007","volume":"6","author":[{"given":"Rahul","family":"Jadon","sequence":"first","affiliation":[]},{"given":"Venkata Surya Teja","family":"Gollapalli","sequence":"additional","affiliation":[]},{"given":"Rajababu","family":"Budda","sequence":"additional","affiliation":[]},{"given":"Kannan","family":"Srinivasan","sequence":"additional","affiliation":[]},{"given":"Guman Singh","family":"Chauhan","sequence":"additional","affiliation":[]},{"given":"Joseph Bamidele","family":"Awotunde","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"issue":"37","key":"4154_CR1","first-page":"50","volume":"27","author":"P Baldi","year":"2023","unstructured":"Baldi P. Autoencoders, unsupervised learning, and deep architectures. J Mach Learn Res 2023;27:37\u201350.","journal-title":"J Mach Learn Res"},{"key":"4154_CR2","unstructured":"Klambauer G, Unterthiner T, Mayr A, Hochreiter S. Self-normalizing neural networks. In: Advances in neural information processing systems (NeurIPS). 2023."},{"key":"4154_CR3","unstructured":"Malcolm K, Casco-Rodriguez J. A comprehensive review of spiking neural networks: interpretation, optimization, efficiency, and best practices. 2023. arXiv preprint arXiv:2303.10780."},{"key":"4154_CR4","doi-asserted-by":"crossref","unstructured":"Birthriya SK, Ahlawat P, Jain AK. Enhanced phishing website detection using dual-layer CNN and GRU with attention mechanism and lexical NLP features. SN Computer. 2024.","DOI":"10.1007\/s42979-024-03282-6"},{"issue":"14","key":"4154_CR5","doi-asserted-by":"publisher","first-page":"10086","DOI":"10.3390\/app142210086","volume":"2024","author":"QEU Haq","year":"2024","unstructured":"Haq QEU, Faheem MH, Ahmad I. Detecting phishing URLs based on a deep learning approach to prevent cyber-attacks. Appl Sci. 2024;2024(14):10086.","journal-title":"Appl Sci"},{"key":"4154_CR6","unstructured":"Garikipati V, Dyavani NR, Jayaprakasam BS, Ubagaram C, Mandala RR, Kumar VKR. Leveraging deep neural networks for cloud-based network traffic anomaly detection and security enhancement. J Sci Technol. 2021;6(6). https:\/\/jst.org.in\/index.php\/pub\/article\/view\/1208\/967"},{"issue":"2","key":"4154_CR7","doi-asserted-by":"publisher","first-page":"248","DOI":"10.3390\/sym16020248","volume":"16","author":"S Aslam","year":"2024","unstructured":"Aslam S, Aslam H, Manzoor A, Chen H, Rasool A. AntiPhishStack: LSTM-based stacked generalization model for optimized phishing URL detection. Symmetry. 2024;16(2):248.","journal-title":"Symmetry"},{"key":"4154_CR8","doi-asserted-by":"publisher","first-page":"8373","DOI":"10.1109\/ACCESS.2024.3351946","volume":"12","author":"FS Alsubaei","year":"2024","unstructured":"Alsubaei FS, Almazroi AA, Ayub N. Enhancing phishing detection: a novel hybrid deep learning framework for cybercrime forensics. IEEE Access. 2024;12:8373\u201389.","journal-title":"IEEE Access."},{"key":"4154_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.csa.2024.100036","volume":"2","author":"ES Shombot","year":"2024","unstructured":"Shombot ES, Dusserre G, Bestak R, Ahmed NB. An application for predicting phishing attacks: a case of implementing a support vector machine learning model. Cyber Secur Appl. 2024;2: 100036.","journal-title":"Cyber Secur Appl"},{"issue":"14","key":"4154_CR10","doi-asserted-by":"publisher","first-page":"6081","DOI":"10.3390\/app14146081","volume":"14","author":"E Kocyigit","year":"2024","unstructured":"Kocyigit E, Korkmaz M, Sahingoz OK, Diri B. Enhanced feature selection using genetic algorithm for machine-learning-based phishing URL detection. Appl Sci. 2024;14(14):6081.","journal-title":"Appl Sci"},{"issue":"4","key":"4154_CR11","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1007\/s41965-024-00166-9","volume":"6","author":"MI Ple\u1e63a","year":"2024","unstructured":"Ple\u1e63a MI, Gheorghe M, Ipate F, Zhang G. Applications of spiking neural P systems in cybersecurity. J Membr Comput. 2024;6(4):310\u20137.","journal-title":"J Membr Comput"},{"issue":"2","key":"4154_CR12","doi-asserted-by":"publisher","first-page":"2165","DOI":"10.11591\/ijai.v13.i2.pp2165-2172","volume":"13","author":"JK Sasi","year":"2024","unstructured":"Sasi JK, Balakrishnan A. Generative adversarial network-based phishing URL detection with variational autoencoder and transformer. Int J Artif Intell. 2024;13(2):2165\u201372.","journal-title":"Int J Artif Intell"},{"issue":"1","key":"4154_CR13","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s42454-024-00053-9","volume":"6","author":"MK Pandey","year":"2024","unstructured":"Pandey MK, Pal R, Pal S, Kumar A, Shukla AK, Yadav DC. Intelligent analysis to detect phishing websites using machine learning ensemble techniques. Human-Intell Syst Integr. 2024;6(1):39\u201347.","journal-title":"Human-Intell Syst Integr"},{"issue":"4","key":"4154_CR14","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1007\/s11235-024-01229-z","volume":"87","author":"C Kondaiah","year":"2024","unstructured":"Kondaiah C, Pais AR, Rao RS. An ensemble learning approach for detecting phishing URLs in encrypted TLS traffic. Telecommun Syst. 2024;87(4):1015\u201331.","journal-title":"Telecommun Syst"},{"key":"4154_CR15","doi-asserted-by":"publisher","first-page":"00059","DOI":"10.1051\/bioconf\/20249700059","volume":"97","author":"SY Mohammed","year":"2024","unstructured":"Mohammed SY, Aljanabi M, Mijwil MM, Ramadhan AJ, Abotaleb M, Alkattan H, Albadran Z. A two-stage hybrid approach for phishing attack detection using URL and content analysis in IoT. BIO Web Conf. 2024;97:00059.","journal-title":"BIO Web Conf"},{"issue":"06","key":"4154_CR16","first-page":"190","volume":"05","author":"NS Allur","year":"2020","unstructured":"Allur NS. Phishing website detection based on multidimensional features driven by deep learning: integrating stacked autoencoder and SVM. J Sci Technol. 2020;05(06):190\u2013204.","journal-title":"J Sci Technol"},{"issue":"4","key":"4154_CR17","doi-asserted-by":"publisher","first-page":"4543","DOI":"10.1007\/s10489-021-02550-9","volume":"52","author":"P Dhal","year":"2022","unstructured":"Dhal P, Azad C. A comprehensive survey on feature selection in the various fields of machine learning. Appl Intell. 2022;52(4):4543\u201381.","journal-title":"Appl Intell"},{"issue":"2","key":"4154_CR18","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.13803","volume":"42","author":"P Dhal","year":"2025","unstructured":"Dhal P, Azad C. Zone oriented binary multi-objective charged system search based feature selection approach for multi-label classification. Expert Syst. 2025;42(2): e13803.","journal-title":"Expert Syst"},{"key":"4154_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2024.103540","volume":"162","author":"D Javeed","year":"2024","unstructured":"Javeed D, Saeed MS, Adil M, Kumar P, Jolfaei A. A federated learning-based zero trust intrusion detection system for Internet of Things. Ad Hoc Netw. 2024;162: 103540.","journal-title":"Ad Hoc Netw"},{"key":"4154_CR20","unstructured":"Rathee H. Malware Profiling and Classification using machine learning algorithms. Doctoral dissertation, Dublin Business School. 2024."},{"key":"4154_CR21","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.procs.2023.12.067","volume":"230","author":"K Omari","year":"2023","unstructured":"Omari K. Phishing detection using gradient boosting classifier. Procedia Comput Sci. 2023;230:120\u20137.","journal-title":"Procedia Comput Sci"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04154-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-025-04154-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04154-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T21:55:31Z","timestamp":1757282131000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-025-04154-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"references-count":21,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["4154"],"URL":"https:\/\/doi.org\/10.1007\/s42979-025-04154-3","relation":{},"ISSN":["2661-8907"],"issn-type":[{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,24]]},"assertion":[{"value":"3 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 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":"There is no conflict of interest between the authors. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Yes, you can reproduce.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Permission to reproduce material from other sources"}},{"value":"We have not harmed any human person with our research data collection, which was gathered from an already-published article.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical trial registration"}}],"article-number":"676"}}