{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T16:49:11Z","timestamp":1783183751741,"version":"3.54.6"},"reference-count":45,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T00:00:00Z","timestamp":1753056000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University\u2013Industry Collaborative Education Program of the Ministry of Education of China","award":["231101020130957"],"award-info":[{"award-number":["231101020130957"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The development of 5G environments has several advantages, including accelerated data transfer speeds, reduced latency, and improved energy efficiency. Nevertheless, it also increases the risk of severe cybersecurity issues, including a complex and enlarged attack surface, privacy concerns, and security threats to 5G core network functions. A 5G core network DDoS attack detection model is been proposed which utilizes a binary improved non-Bald Eagle optimization algorithm (Sin-Cos-bIAVOA) originally designed for IoT DDoS detection to select effective features for DDoS attacks. This approach employs a novel composite transfer function (Sin-Cos) to enhance exploration. The proposed method\u2019s performance is compared with classical algorithms on the 5G Core PFCP DDoS attacks dataset. After rigorous testing across a spectrum of attack scenarios, the proposed detection model exhibits superior performance compared to traditional DDoS detection algorithms. This is a significant finding, as it suggests that the model achieves a higher degree of detection accuracy, meaning it is better equipped to identify and mitigate DDoS attacks. This is particularly noteworthy in the context of 5G core networks, as it offers a novel solution to the problem of DDoS attack detection for this critical infrastructure.<\/jats:p>","DOI":"10.3390\/a18070449","type":"journal-article","created":{"date-parts":[[2025,7,21]],"date-time":"2025-07-21T11:44:05Z","timestamp":1753098245000},"page":"449","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9920-6993","authenticated-orcid":false,"given":"Zheng","family":"Ma","sequence":"first","affiliation":[{"name":"Informatization Office, China University of Geosciences, Wuhan 430074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7634-0992","authenticated-orcid":false,"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Informatization Office, China University of Geosciences, Wuhan 430074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-9435-3355","authenticated-orcid":false,"given":"Lang","family":"Gao","sequence":"additional","affiliation":[{"name":"Human Resources Department, China University of Geosciences, Wuhan 430074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1007\/s11416-024-00529-x","article-title":"Next gen cybersecurity paradigm towards artificial general intelligence: Russian market challenges and future global technological trends","volume":"20","author":"Pleshakova","year":"2024","journal-title":"J. Comput. Virol. Hacking Tech."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Park, S., Kim, D., Park, Y., Cho, H., Kim, D., and Kwon, S. (2021). 5G Security Threat Assessment in Real Networks. Sensors, 21.","DOI":"10.3390\/s21165524"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"8169","DOI":"10.1109\/JIOT.2019.2927379","article-title":"Physical-Layer Security of 5G Wireless Networks for IoT: Challenges and Opportunities","volume":"6","author":"Wang","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107982","DOI":"10.1016\/j.comcom.2024.107982","article-title":"5G core network control plane: Network security challenges and solution requirements","volume":"229","author":"Patil","year":"2025","journal-title":"Comput. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"72","DOI":"10.4218\/etrij.2017-0236","article-title":"Agile Management and Interoperability Testing of SDN\/NFV-Enriched 5G Core Networks","volume":"40","author":"Choi","year":"2018","journal-title":"ETRI J."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kim, E., and Choi, Y.I. (2019, January 2\u20135). Traffic monitoring system for 5G core network. Proceedings of the 11th International Conference on Ubiquitous and Future Networks (ICUFN), Zagreb, Croatia.","DOI":"10.1109\/ICUFN.2019.8806155"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1587\/transfun.2021EAP1011","article-title":"Deployment and Reconfiguration for Balanced 5G Core Network Slices","volume":"104","author":"Lu","year":"2021","journal-title":"IEICE Trans. Fundam. Electron. Commun. Comput. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Pell, R., Shojafar, M., Kosmanos, D., and Moschoyiannis, S. (2023, January 2\u20138). Service Classification of Network Traffic in 5G Core Networks using Machine Learning. Proceedings of the 7th IEEE International Conference on Edge Computing and Communications (IEEE EDGE)\/IEEE World Congress on Services (SERVICES), Chicago, IL, USA.","DOI":"10.1109\/EDGE60047.2023.00053"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Oh, B.H., Vural, S., Rahulan, Y., Wang, N., and Tafazolli, R. (2018, January 19\u201321). Performance Evaluation of a Virtualized 5G Core Network in Indoor Environments. Proceedings of the International Symposium on Networks, Computers and Communications (ISNCC), Rome, Italy.","DOI":"10.1109\/ISNCC.2018.8530923"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Pinto, A., Santaromita, G., Fiandrino, C., Giustiniano, D., and Esposito, F. (2022, January 14\u201316). Characterizing Location Management Function Performance in 5G Core Networks. Proceedings of the IEEE Conference on Network Function Virtualization and Software Defined Networks (IEEE NFV-SDN), Chandler, AZ, USA.","DOI":"10.1109\/NFV-SDN56302.2022.9974927"},{"key":"ref_11","unstructured":"Zhu, X.T., and Qu, X.M. (July, January 28). Research on 5G Lightweight Core Network Technology for Vertical Industries. Proceedings of the 17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC), Harbin City, China."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Vanichchanunt, P., Yamyuan, I., Sasithong, P., Wuttisittikulkij, L., and Paripurana, S. (2023, January 11\u201314). Implementation of Edge Servers on an Open 5G Core Network. Proceedings of the 37th International Conference on Information Networking (ICOIN), Bangkok, Thailand.","DOI":"10.1109\/ICOIN56518.2023.10049000"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zieba, M., Natkaniec, M., and Borylo, P. (2024). Cloud-Enabled Deployment of 5G Core Network with Analytics Features. Appl. Sci., 14.","DOI":"10.3390\/app14167018"},{"key":"ref_14","unstructured":"Le, T.N.L., Salem, B.A., Ahad, E.A., Aitsaadi, N., and Du, X. (2023, January 4\u20138). 5G-IoT-IDS: Intrusion Detection System for CIoT as Network Function in 5G Core Network. Proceedings of the IEEE Conference on Global Communications (IEEE GLOBECOM)\u2014Intelligent Communications for Shared Prosperity, Kuala Lumpur, Malaysia."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Huang, H.O., Chu, J.F., and Cheng, X.C. (2021, January 8\u201310). Trend Analysis and Countermeasure Research of Ddos Attack under 5g Network. Proceedings of the 5th IEEE International Conference on Cryptography, Beijing Normal University, Zhuhai, China.","DOI":"10.1109\/CSP51677.2021.9357499"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Onoja, D., Hitchens, M., and Shankaran, R. (2022, January 21\u201323). Security Policy to Manage Responses to Ddos Attacks on 5g Iot Enabled Devices. Proceedings of the 13th International Conference on Information and Communication Systems (ICICS), Irbid, Jordan.","DOI":"10.1109\/ICICS55353.2022.9811193"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mamolar, A.S., Pervez, Z., Wang, Q., and Alcaraz-Calero, J.M. (2019, January 18\u201321). Towards the Detection of Mobile Ddos Attacks in 5g Multi-Tenant Networks. Proceedings of the 28th European Conference on Networks and Communications (EuCNC), Valencia, Spain.","DOI":"10.1109\/EuCNC.2019.8801975"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"102416","DOI":"10.1016\/j.jnca.2019.102416","article-title":"Autonomic Protection of Multi-Tenant 5g Mobile Networks against Udp Flooding Ddos Attacks","volume":"145","author":"Mamolar","year":"2019","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ramezan, G., Abdelnasser, A., Liu, B.Y., Jiang, W.Y., and Yang, F. (2021, January 13\u201315). Eap-Zkp: A Zero-Knowledge Proof Based Authentication Protocol to Prevent Ddos Attacks a the Edge in Beyond 5g. Proceedings of the IEEE 4th 5G World Forum (5GWF), Montreal, QC, Canada.","DOI":"10.1109\/5GWF52925.2021.00052"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Park, S., Cho, B., Kim, D., and You, I. (2022). Machine Learning Based Signaling Ddos Detection System for 5g Stand Alone Core Network. Appl. Sci., 12.","DOI":"10.3390\/app122312456"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Peng, C., Fan, W., Huang, W.Q., and Zhu, D.L. (2023, January 26\u201329). A Novel Approach Based on Improved Naive Bayes for 5g Air Interface Ddos Detection. Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC), Glasgow, UK.","DOI":"10.1109\/WCNC55385.2023.10118854"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"108561","DOI":"10.1109\/ACCESS.2023.3318176","article-title":"Modified Equilibrium Optimization Algorithm with Deep Learning-Based Ddos Attack Classification in 5g Networks","volume":"11","author":"Aljebreen","year":"2023","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3930","DOI":"10.1109\/TNSM.2023.3254581","article-title":"Reinforcement Learning-Based Slice Isolation against Ddos Attacks in Beyond 5g Networks","volume":"20","author":"Javadpour","year":"2023","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Bousalem, B., Silva, V.F., Langar, R., and Cherrier, S. (2022, January 4\u20138). Ddos Attacks Detection and Mitigation in 5g and Beyond Networks: A Deep Learning-Based Approach. Proceedings of the IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil.","DOI":"10.1109\/NetSoft54395.2022.9844053"},{"key":"ref_25","unstructured":"Bousalem, B., Silva, V.F., Langar, R., and Cherrier, S. (July, January 27). Deep Learning-Based Approach for Ddos Attacks Detection and Mitigation in 5g and Beyond Mobile Networks. Proceedings of the 8th IEEE International Conference on Network Softwarization (NetSoft)\u2014Network Softwarization Coming of Age\u2014New Challenges and Opportunities, Politecnico Milano, Dipartimento Elettronica, Informazione & Bioingegneria, Milan, Italy."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3337","DOI":"10.1007\/s13042-021-01323-7","article-title":"Ddos Detection in 5g-Enabled Iot Networks Using Deep Kalman Backpropagation Neural Network","volume":"12","author":"Almiani","year":"2021","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Sheikhi, S., and Kostakos, P. (2023, January 6\u20139). Ddos Attack Detection Using Unsupervised Federated Learning for 5g Networks and Beyond. Proceedings of the Joint European Conference on Networks and Communications\/6G Summit (EuCNC\/6G Summit), Gothenburg, Sweden.","DOI":"10.1109\/EuCNC\/6GSummit58263.2023.10188245"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MNET.021.1900614","article-title":"Countermeasure Based on Smart Contracts and Ai against Dos\/Ddos Attack in 5g Circumstances","volume":"34","author":"Fang","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kuang, X., Hou, J., Liu, X., Lin, C., Wang, Z., and Wang, T. (2024). Improved African Vulture Optimization Algorithm Based on Random Opposition-Based Learning Strategy. Electronics, 13.","DOI":"10.3390\/electronics13163329"},{"key":"ref_30","first-page":"142","article-title":"African Vulture Optimization-Based Decision Tree (AVO-DT): An Innovative Method for Malware Identification and Evaluation through the Application of Meta-Heuristic Optimization Algorithm","volume":"24","author":"Kaithal","year":"2024","journal-title":"Cybern. Inf. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kholidy, H.A., Karam, A., Sidoran, J.L., and Rahman, M.A. (2021, January 5\u20138). 5G Core Security in Edge Networks: A Vulnerability Assessment Approach. Proceedings of the 26th IEEE Symposium on Computers and Communications (IEEE ISCC), Athens, Greece.","DOI":"10.1109\/ISCC53001.2021.9631531"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Amponis, G., Radoglou-Grammatikis, P., Nakas, G., Goudos, S., Argyriou, V., Lagkas, T., and Sarigiannidis, P. (2023, January 28\u201330). 5G Core PFCP Intrusion Detection Dataset. Proceedings of the 2023 12th International Conference on Modern Circuits and Systems Technologies (MOCAST), Athens, Greece.","DOI":"10.1109\/MOCAST57943.2023.10176693"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"154913","DOI":"10.1016\/j.aeue.2023.154913","article-title":"Generating full-stack 5G security datasets: IP-layer and core network persistent PDU session attacks","volume":"171","author":"Amponis","year":"2023","journal-title":"AEU Int. J. Electron. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ock, J., No, H., and Kim, S. (2023, January 18\u201321). Poster: Exploring Synthetic Data Generation for Anomaly Detection in the 5G NWDAF Architecture. Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems, ICDCS 2023, Hong Kong, China.","DOI":"10.1109\/ICDCS57875.2023.00129"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/978-3-030-72802-1_9","article-title":"NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems","volume":"Volume 371","author":"Sarhan","year":"2024","journal-title":"Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering"},{"key":"ref_36","unstructured":"Samarakoon, S., Siriwardhana, Y., Porambage, P., Liyanage, M., Chang, S.-Y., Kim, J., Kim, J., and Ylianttila, M. (2022). 5G-NIDD: A Comprehensive Network Intrusion Detection Dataset Generated over 5G Wireless Network. arXiv."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"113420","DOI":"10.1016\/j.asoc.2025.113420","article-title":"Transforming security in internet of medical things with advanced deep learning-based intrusion detection frameworks","volume":"180","author":"Sharma","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Moubayed, A. (2024). A Complete EDA and DL Pipeline for Softwarized 5G Net Moubayed, A.work Intrusion Detection. Future Internet, 16.","DOI":"10.3390\/fi16090331"},{"key":"ref_39","first-page":"470","article-title":"CoSen-IDS: A Novel Cost-Sensitive Intrusion Detection System on Imbalanced Data in 5G Networks","volume":"Volume 14869","author":"Yuan","year":"2024","journal-title":"Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"},{"key":"ref_40","unstructured":"Civciss, A., Ravihansa, V., Sandeepa, C., and Liyanage, M. (2025, June 11). Netslab-5G-ORAN-IDD [Data Set]. Kaggle. Available online: https:\/\/www.kaggle.com\/datasets\/netslabdemo\/netslab-5g-oran-idd."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"107408","DOI":"10.1016\/j.cie.2021.107408","article-title":"African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems","volume":"158","author":"Abdollahzadeh","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"16929","DOI":"10.1007\/s11042-023-16300-1","article-title":"An improved African vultures optimization algorithm using different fitness functions for multi-level thresholding image segmentation","volume":"83","author":"Gharehchopogh","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"10963","DOI":"10.3934\/mbe.2022512","article-title":"IHAOAVOA: An improved hybrid aquila optimizer and African vultures optimization algorithm for global optimization problems","volume":"19","author":"Xiao","year":"2022","journal-title":"Math. Biosci. Eng."},{"key":"ref_44","first-page":"329","article-title":"A multi-strategy enhanced African vultures optimization algorithm for global optimization problems","volume":"10","author":"Zheng","year":"2023","journal-title":"J. Comput. Des. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"120404","DOI":"10.1016\/j.eswa.2023.120404","article-title":"Sin-Cos-bIAVOA A new feature selection method based on improved African vulture optimization algorithm and a novel transfer function to DDoS attack detection","volume":"228","author":"Sharifian","year":"2023","journal-title":"Expert Syst. 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