{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T19:00:52Z","timestamp":1785006052821,"version":"3.55.0"},"reference-count":30,"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\/s10586-026-06129-2","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T10:35:08Z","timestamp":1781692508000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Vanet security reinvented: hierarchical stacked CNNS and attention-driven BILSTM optimization"],"prefix":"10.1007","volume":"29","author":[{"given":"Saleha","family":"Saudagar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gayatri","family":"Jagnade","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geetika","family":"Narang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rupali","family":"Maske","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sneha","family":"Tirth","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"issue":"1","key":"6129_CR1","doi-asserted-by":"publisher","first-page":"4","DOI":"10.63180\/jjic.thestap.2025.1.2","volume":"2025","author":"H Albinhamad","year":"2025","unstructured":"Albinhamad, H., Alotibi, A., Alagnam, A., Almaiah, M., Salloum, S.: Vehicular ad-hoc networks (VANETs): A key enabler for smart transportation systems and challenges. Jordanian J. Inf. Comput. 2025(1), 4\u201315 (2025). https:\/\/doi.org\/10.63180\/jjic.thestap.2025.1.2","journal-title":"Jordanian J. Inf. Comput."},{"issue":"1","key":"6129_CR2","doi-asserted-by":"publisher","first-page":"e0296331","DOI":"10.1371\/journal.pone.0296331","volume":"19","author":"S Yerrathi","year":"2024","unstructured":"Yerrathi, S., Pakala, V.: Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system. PLoS ONE. 19(1), e0296331 (2024). https:\/\/doi.org\/10.1371\/journal.pone.0296331","journal-title":"PLoS ONE"},{"issue":"13","key":"6129_CR3","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.3390\/electronics13132673","volume":"13","author":"MA Naeem","year":"2024","unstructured":"Naeem, M.A., Chaudhary, S., Meng, Y.: Road to efficiency: V2V enabled intelligent transportation system. Electronics. 13(13), 2673 (2024). https:\/\/doi.org\/10.3390\/electronics13132673","journal-title":"Electronics"},{"issue":"1","key":"6129_CR4","doi-asserted-by":"publisher","first-page":"34170","DOI":"10.1038\/s41598-025-15215-1","volume":"15","author":"N Jayakrishna","year":"2025","unstructured":"Jayakrishna, N., Prasanth, N.N.: A hybrid deep learning model for detection and mitigation of DDoS attacks in VANETs. Sci. Rep. 15(1), 34170 (2025). https:\/\/doi.org\/10.1038\/s41598-025-15215-1","journal-title":"Sci. Rep."},{"key":"6129_CR5","doi-asserted-by":"publisher","first-page":"113371","DOI":"10.1016\/j.knosys.2025.113371","volume":"317","author":"K Bagirathan","year":"2025","unstructured":"Bagirathan, K., Saravanan, N., Vijayabhaskar, K., C, S.: An intelligent recurrent neural network driven secured routing protocol for vehicular ad hoc networks. Knowl. Based Syst. 317, 113371 (2025). https:\/\/doi.org\/10.1016\/j.knosys.2025.113371","journal-title":"Knowl. Based Syst."},{"key":"6129_CR6","doi-asserted-by":"publisher","first-page":"79030","DOI":"10.1109\/access.2025.3566172","volume":"13","author":"A Surayya","year":"2025","unstructured":"Surayya, A., Hussain, M.M., Reddy, V.D., Abdul, A., Gazi, F.: Evolutionary algorithms for edge server placement in vehicular edge computing. IEEE Access. 13, 79030\u201379052 (2025). https:\/\/doi.org\/10.1109\/access.2025.3566172","journal-title":"IEEE Access."},{"key":"6129_CR7","doi-asserted-by":"publisher","first-page":"100037","DOI":"10.1016\/j.csa.2024.100037","volume":"2","author":"H Setia","year":"2024","unstructured":"Setia, H., Chhabra, A., Singh, S.K., Kumar, S., Sharma, S., Arya, V., Gupta, B.B., Wu, J.: Securing the road ahead: Machine learning-driven DDoS attack detection in VANET cloud environments. Cyber Secur. Appl. 2, 100037 (2024). https:\/\/doi.org\/10.1016\/j.csa.2024.100037","journal-title":"Cyber Secur. Appl."},{"issue":"1","key":"6129_CR8","doi-asserted-by":"publisher","first-page":"43912","DOI":"10.1038\/s41598-025-27682-7","volume":"15","author":"GV Goud","year":"2025","unstructured":"Goud, G.V., Arunachalam, R., Shukla, S.K., Saranya, K., Venugopal, S., Palanisamy, P.: Blockchain-based secure MEC model for VANETs using hybrid networks. Sci. Rep. 15(1), 43912 (2025). https:\/\/doi.org\/10.1038\/s41598-025-27682-7","journal-title":"Sci. Rep."},{"issue":"5","key":"6129_CR9","doi-asserted-by":"publisher","first-page":"7023","DOI":"10.1007\/s10586-024-04322-9","volume":"27","author":"RS Sumit, Chhillar","year":"2024","unstructured":"Sumit, Chhillar, R.S., Dalal, S., Dalal, S., Lilhore, U.K., Samiya, S.: A dynamic and optimized routing approach for VANET communication in smart cities to secure intelligent transportation system via a chaotic multi-verse optimization algorithm. Cluster Comput. 27(5), 7023\u20137048 (2024). https:\/\/doi.org\/10.1007\/s10586-024-04322-9","journal-title":"Cluster Comput."},{"issue":"8","key":"6129_CR10","doi-asserted-by":"publisher","first-page":"e0328829","DOI":"10.1371\/journal.pone.0328829","volume":"20","author":"BK Mekonen","year":"2025","unstructured":"Mekonen, B.K., Bane, L., Fite, N.B.: Detection of false position attacks in VANETs through bagging ensemble learning. PLoS ONE. 20(8), e0328829 (2025). https:\/\/doi.org\/10.1371\/journal.pone.0328829","journal-title":"PLoS ONE"},{"issue":"1","key":"6129_CR11","doi-asserted-by":"publisher","first-page":"31780","DOI":"10.1038\/s41598-024-82313-x","volume":"14","author":"TK Venkatasamy","year":"2024","unstructured":"Venkatasamy, T.K., Hossen, M.J., Ramasamy, G., Aziz, N.H.B.A.: Intrusion detection system for V2X communication in VANET networks using machine learning-based cryptographic protocols. Sci. Rep. 14(1), 31780 (2024). https:\/\/doi.org\/10.1038\/s41598-024-82313-x","journal-title":"Sci. Rep."},{"key":"6129_CR12","doi-asserted-by":"publisher","first-page":"103845","DOI":"10.1016\/j.csi.2024.103845","volume":"90","author":"MA Setitra","year":"2024","unstructured":"Setitra, M.A., Fan, M.: Detection of DDoS attacks in SDN-based VANET using optimized TabNet. Comput. Stand. Interfaces. 90, 103845 (2024). https:\/\/doi.org\/10.1016\/j.csi.2024.103845","journal-title":"Comput. Stand. Interfaces"},{"key":"6129_CR13","doi-asserted-by":"publisher","unstructured":"Gupta, M., Karthikeyan, M.P., Sahu, P.K., Reddy, N.H., Alli, A., Jadhav, Y.: A hybrid machine learning approach for real-time threat classification in VANET-based transportation systems. SN Comput. Sci. 7(1) (2025). https:\/\/doi.org\/10.1007\/s42979-025-04508-x","DOI":"10.1007\/s42979-025-04508-x"},{"key":"6129_CR14","doi-asserted-by":"publisher","first-page":"127295","DOI":"10.1016\/j.eswa.2025.127295","volume":"279","author":"A BKathole","year":"2025","unstructured":"BKathole, A., Lonare, S., Katti, J., Vhatkar, K., Dharmale, G.: Efficient fuzzy ranking with ensemble machine learning network for attack detection and classification in VANET. Expert Syst. Appl. 279, 127295 (2025). https:\/\/doi.org\/10.1016\/j.eswa.2025.127295","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"6129_CR15","doi-asserted-by":"publisher","first-page":"4705","DOI":"10.32604\/cmc.2025.067733","volume":"85","author":"B Muktar","year":"2025","unstructured":"Muktar, B., Fono, V., Nouboukpo, A.: Machine learning-based detection of DDoS attacks in VANETs for emergency vehicle communication. Computers Mater. Continua. 85(3), 4705\u20134727 (2025). https:\/\/doi.org\/10.32604\/cmc.2025.067733","journal-title":"Computers Mater. Continua"},{"issue":"1","key":"6129_CR16","doi-asserted-by":"publisher","first-page":"40068","DOI":"10.1038\/s41598-025-28212-1","volume":"15","author":"WK Wong","year":"2025","unstructured":"Wong, W.K., Baskar, S., Abubeker, K.M., Ng, P.K.: Sustainable cyber-physical VANETs with AI-driven anomaly detection and energy-efficient multi-criteria routing using machine learning algorithms. Sci. Rep. 15(1), 40068 (2025). https:\/\/doi.org\/10.1038\/s41598-025-28212-1","journal-title":"Sci. Rep."},{"key":"6129_CR17","doi-asserted-by":"publisher","first-page":"100830","DOI":"10.1016\/j.ijcip.2026.100830","volume":"52","author":"M Murshed","year":"2026","unstructured":"Murshed, M., Wickramasurendra, N., Jubaida, A., De Grande, R.E., Carvalho, G.H.: Novel RF-jamming IDS for vehicular networks: LSTM, XGBoost, and meta-model approaches. Int. J. Crit. Infrastruct. Prot. 52, 100830 (2026). https:\/\/doi.org\/10.1016\/j.ijcip.2026.100830","journal-title":"Int. J. Crit. Infrastruct. Prot."},{"key":"6129_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/tce.2025.3634753","author":"H Naeem","year":"2025","unstructured":"Naeem, H., Alsirhani, A., Alserhani, F.M., Althobaiti, M.M., Alabdulkreem, E.: Adaptive federated reinforcement learning with temporal hybrid deep model for consumer internet of vehicles intrusion detection. IEEE Trans. Consum. Electron. (2025). https:\/\/doi.org\/10.1109\/tce.2025.3634753","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"2","key":"6129_CR19","doi-asserted-by":"publisher","first-page":"37","DOI":"10.3390\/jsan14020037","volume":"14","author":"LIB L\u00f3pez","year":"2025","unstructured":"L\u00f3pez, L.I.B., Saltos, T.B.: Heterogeneity challenges of federated learning for future wireless communication networks. J. Sens. Actuator Networks. 14(2), 37 (2025). https:\/\/doi.org\/10.3390\/jsan14020037","journal-title":"J. Sens. Actuator Networks"},{"issue":"1","key":"6129_CR20","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/tce.2024.3475823","volume":"71","author":"P Suman","year":"2024","unstructured":"Suman, P., Padhy, S., Kumar, N., Suman, A., Singh, A., Singh, K.K., Castilla, \u00c1.K., Al-Zahrani, T.S.S.: An improved deep learning-based intrusion detection for reliable communication in VANET. IEEE Trans. Consum. Electron. 71(1), 209\u2013217 (2024). https:\/\/doi.org\/10.1109\/tce.2024.3475823","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"2","key":"6129_CR21","doi-asserted-by":"publisher","first-page":"e0312752","DOI":"10.1371\/journal.pone.0312752","volume":"20","author":"F Hassan","year":"2025","unstructured":"Hassan, F., Syed, Z.S., Memon, A.A., Alqahtany, S.S., Ahmed, N., Reshan, M.S.A., Asiri, Y., Shaikh, A.: A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. PLoS ONE. 20(2), e0312752 (2025). https:\/\/doi.org\/10.1371\/journal.pone.0312752","journal-title":"PLoS ONE"},{"key":"6129_CR22","doi-asserted-by":"publisher","unstructured":"Ara\u00fajo, A.R.C., Rosa, R.L., Rodr\u00edguez, D.Z., Maidin, S.S., Awotunde, J.B., Saadi, M.: LightBiOptimum: An intrusion detection system based on bio-inspired algorithm for VANET. Trans. Emerg. Telecommunications Technol. 36(10) (2025). https:\/\/doi.org\/10.1002\/ett.70254","DOI":"10.1002\/ett.70254"},{"issue":"1","key":"6129_CR23","doi-asserted-by":"publisher","first-page":"27058","DOI":"10.1038\/s41598-025-96303-0","volume":"15","author":"C Christy","year":"2025","unstructured":"Christy, C., Nirmala, A., Teena, A.M.O., Amali, A.I.: Machine learning-based multi-stage intrusion detection system and feature selection ensemble security in cloud-assisted vehicular ad hoc networks. Sci. Rep. 15(1), 27058 (2025). https:\/\/doi.org\/10.1038\/s41598-025-96303-0","journal-title":"Sci. Rep."},{"issue":"1","key":"6129_CR24","doi-asserted-by":"publisher","first-page":"35604","DOI":"10.1038\/s41598-025-17699-3","volume":"15","author":"S Almansour","year":"2025","unstructured":"Almansour, S., Yadav, K., Alkwai, L.M., Alghamdi, N.S., Viriyasitavat, W., Dhiman, G.: Adaptive personalized federated learning with lightweight depthwise convolutional bottleneck network for novel intrusion detection system in internet of vehicles. Sci. Rep. 15(1), 35604 (2025). https:\/\/doi.org\/10.1038\/s41598-025-17699-3","journal-title":"Sci. Rep."},{"key":"6129_CR25","doi-asserted-by":"publisher","first-page":"5522431","DOI":"10.1155\/2024\/5522431","volume":"2024","author":"K Sundaram","year":"2024","unstructured":"Sundaram, K., Natarajan, Y., Perumalsamy, A., Yusuf Ali, A.A.: A novel hybrid feature selection with cascaded LSTM: Enhancing security in IoT networks. Wirel. Commun. Mob. Comput. 2024, 5522431 (2024)","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"6129_CR26","doi-asserted-by":"publisher","unstructured":"Kumari,A., Chaturvedi, P., Bishnoi, D., Gandhi, P.: Deep learning driven detection and classification of attacks in vehicular communication systems. In: Deep learning based solutions for vehicular adhoc networks. Springer Nat. Singap. 285\u2013301 (2025). https:\/\/doi.org\/10.1007\/978-981-96-5190-0_12","DOI":"10.1007\/978-981-96-5190-0_12"},{"key":"6129_CR27","doi-asserted-by":"publisher","unstructured":"Mehmood, S., Amin, R., Mustafa, J., Hussain, M., Alsubaei, F.S., Zakaria, M.D.: Distributed denial of service (DDoS) attack detection in SDN using optimizer-equipped CNN-MLP. PLoS ONE, 20(1), e0312425. (2025). https:\/\/doi.org\/10.1371\/journal.pone.0312425","DOI":"10.1371\/journal.pone.0312425"},{"issue":"10s","key":"6129_CR28","doi-asserted-by":"publisher","first-page":"90","DOI":"10.52783\/jisem.v10i10s.1357","volume":"10","author":"S Telang","year":"2025","unstructured":"Telang, S.: Revolutionizing network security with hybrid deep learning models for intrusion detection. J. Inform. Syst. Eng. Manage. 10(10s), 90\u2013117 (2025). https:\/\/doi.org\/10.52783\/jisem.v10i10s.1357","journal-title":"J. Inform. Syst. Eng. Manage."},{"issue":"2","key":"6129_CR29","doi-asserted-by":"publisher","first-page":"69","DOI":"10.3390\/a18020069","volume":"18","author":"H Kamal","year":"2025","unstructured":"Kamal, H., Mashaly, M.: Enhanced hybrid deep learning models-based anomaly detection method for two-stage binary and multi-class classification of attacks in intrusion detection systems. Algorithms. 18(2), 69 (2025). https:\/\/doi.org\/10.3390\/a18020069","journal-title":"Algorithms"},{"issue":"10","key":"6129_CR30","doi-asserted-by":"publisher","first-page":"e0332752","DOI":"10.1371\/journal.pone.0332752","volume":"20","author":"A Alqhatani","year":"2025","unstructured":"Alqhatani, A., Mehmood, S., Amin, R., Alshehri, M.S., Alshehri, A.H., Asiri, F.: Deep memory for deep threats: A novel architecture combining GRUs and deep learning models for IDS. PLoS ONE. 20(10), e0332752 (2025). https:\/\/doi.org\/10.1371\/journal.pone.0332752","journal-title":"PLoS ONE"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06129-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-026-06129-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-026-06129-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T18:32:23Z","timestamp":1785004343000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-026-06129-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":30,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["6129"],"URL":"https:\/\/doi.org\/10.1007\/s10586-026-06129-2","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":"29 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 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":"All contributors agreed and gave consent to Publish.","order":1,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Institutional Review Board approval was not required.","order":3,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"359"}}