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Erschienen in:

01.04.2025

Distributed denial of service attack detection and mitigation strategy in 5G-enabled internet of things networks with adaptive cascaded gated recurrent unit

verfasst von: Md. Mobin Akhtar, Sultan Ali Alasmari, Sk Wasim Haidar, Ali Abdulaziz Alzubaidi

Erschienen in: Peer-to-Peer Networking and Applications | Ausgabe 2/2025

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Abstract

Der Artikel untersucht die wachsende Bedrohung durch DDoS-Angriffe in 5G-fähigen IoT-Netzwerken und die Notwendigkeit effektiver Erkennungs- und Abschwächungsstrategien. Es führt ein adaptives kaskadiertes Recurrent-Unit-Modell (ACGRU) und einen innovativen EEPCO-Algorithmus ein, um die Genauigkeit der DDoS-Erkennung zu erhöhen und die Datenübertragungswege zu optimieren. Die Forschung unterstreicht die Bedeutung der Sicherung von 5G-Netzwerken, um Dienstunterbrechungen zu verhindern und die Zuverlässigkeit und Verfügbarkeit von IoT-Anwendungen zu gewährleisten. Die Studie vergleicht die Leistung des vorgeschlagenen Modells mit bestehenden Methoden und zeigt eine überlegene Genauigkeit und Effizienz bei der Erkennung und Abschwächung von DDoS-Angriffen.

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Literatur
1.
Zurück zum Zitat Aljebreen M, Mengash HA, Arasi MA, Aljameel SS, Salama AS, Hamza MA (2023) Enhancing DDoS attack detection using snake optimizer with ensemble learning on internet of things environment. IEEE Access 11:104745–104753 Aljebreen M, Mengash HA, Arasi MA, Aljameel SS, Salama AS, Hamza MA (2023) Enhancing DDoS attack detection using snake optimizer with ensemble learning on internet of things environment. IEEE Access 11:104745–104753
2.
Zurück zum Zitat Ahmim A, Maazouzi F, Ahmim M, Namane S, Dhaou IB (2023) Distributed Denial of Service Attack Detection for the Internet of Things Using Hybrid Deep Learning Mode. IEEE Access 11:119862–119875 Ahmim A, Maazouzi F, Ahmim M, Namane S, Dhaou IB (2023) Distributed Denial of Service Attack Detection for the Internet of Things Using Hybrid Deep Learning Mode. IEEE Access 11:119862–119875
3.
Zurück zum Zitat Liu Z, Guo C, Liu D, Yin X (2023) An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection. IEEE Access 11:18448–18460 Liu Z, Guo C, Liu D, Yin X (2023) An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection. IEEE Access 11:18448–18460
4.
Zurück zum Zitat Huang H, Ye P, Hu M, Wu J (2023) A multi-point collaborative DDoS defense mechanism for IIoT environment. Digital Commun Networks 9(2):590–601 Huang H, Ye P, Hu M, Wu J (2023) A multi-point collaborative DDoS defense mechanism for IIoT environment. Digital Commun Networks 9(2):590–601
5.
Zurück zum Zitat Sivanesan N, Archana KS (2023) Detecting distributed denial of service (DDoS) in SD-IoT environment with enhanced firefly algorithm and convolution neural network. Opt Quantum Electron 55(5):393 Sivanesan N, Archana KS (2023) Detecting distributed denial of service (DDoS) in SD-IoT environment with enhanced firefly algorithm and convolution neural network. Opt Quantum Electron 55(5):393
6.
Zurück zum Zitat Alashhab AA, Zahid MSM, Muneer A and Abdullahi M. (2022) Low-rate DDoS attack Detection using Deep Learning for SDN-enabled IoT Networks. Int J Adv Comput Sci Appl 13(11). Alashhab AA, Zahid MSM, Muneer A and Abdullahi M. (2022) Low-rate DDoS attack Detection using Deep Learning for SDN-enabled IoT Networks. Int J Adv Comput Sci Appl 13(11).
7.
Zurück zum Zitat Aswad FM, Ahmed AMS, Alhammadi NAM, Khalaf BA, Mostafa SA (2023) Deep learning in distributed denial-of-service attacks detection method for Internet of Things networks. J Intell Syst 32(1):20220155 Aswad FM, Ahmed AMS, Alhammadi NAM, Khalaf BA, Mostafa SA (2023) Deep learning in distributed denial-of-service attacks detection method for Internet of Things networks. J Intell Syst 32(1):20220155
8.
Zurück zum Zitat Alshunaifi SY, Mishra S and Alshehri M (2022) Cyber-Attack Detection and Mitigation Using SVM for 5G Network. Intell Autom Soft Comput 31(1). Alshunaifi SY, Mishra S and Alshehri M (2022) Cyber-Attack Detection and Mitigation Using SVM for 5G Network. Intell Autom Soft Comput 31(1).
9.
Zurück zum Zitat Aslam M, Ye D, Tariq A, Asad M, Hanif M, Ndzi D, Chelloug SA, Al-Qaness EMA, MAA and Jilani SF, (2022) Adaptive machine learning based distributed denial-of-services attacks detection and mitigation system for SDN-enabled IoT. Sensors 22(7):2697 Aslam M, Ye D, Tariq A, Asad M, Hanif M, Ndzi D, Chelloug SA, Al-Qaness EMA, MAA and Jilani SF, (2022) Adaptive machine learning based distributed denial-of-services attacks detection and mitigation system for SDN-enabled IoT. Sensors 22(7):2697
10.
Zurück zum Zitat Alzhrani RM and Alliheedi MA (2023) 5G Networks and IoT Devices: Mitigating DDoS Attacks with Deep Learning Techniques, arXiv, Cryptography and Security. 2311–06938. Alzhrani RM and Alliheedi MA (2023) 5G Networks and IoT Devices: Mitigating DDoS Attacks with Deep Learning Techniques, arXiv, Cryptography and Security. 2311–06938.
11.
Zurück zum Zitat Badamasi UM, Khaliq S, Babalola O, Musa S, Iqbal T (2020) A deep learning based approach for DDoS attack detection in IoT-enabled smart environments. Int J Comput Netw Commun Secur 8(10):93–99 Badamasi UM, Khaliq S, Babalola O, Musa S, Iqbal T (2020) A deep learning based approach for DDoS attack detection in IoT-enabled smart environments. Int J Comput Netw Commun Secur 8(10):93–99
12.
Zurück zum Zitat Khempetch T, Wuttidittachotti P (2021) DDoS attack detection using deep learning. IAES Int J Artif Intell 10(2):382 Khempetch T, Wuttidittachotti P (2021) DDoS attack detection using deep learning. IAES Int J Artif Intell 10(2):382
13.
Zurück zum Zitat Wang J, Liu Y, Feng H (2022) IFACNN: efficient DDoS attack detection based on improved firefly algorithm to optimize convolutional neural networks. Math Biosci Eng 19(2):1280–1303 Wang J, Liu Y, Feng H (2022) IFACNN: efficient DDoS attack detection based on improved firefly algorithm to optimize convolutional neural networks. Math Biosci Eng 19(2):1280–1303
14.
Zurück zum Zitat Coli GO, Aina S, Okegbile SD, Lawal AR, Oluwaranti AI (2022) DDoS Attacks Detection in the IoT Using Deep Gaussian-Bernoulli Restricted Boltzmann Machine. Mod Appl Sci 16(2):1–12 Coli GO, Aina S, Okegbile SD, Lawal AR, Oluwaranti AI (2022) DDoS Attacks Detection in the IoT Using Deep Gaussian-Bernoulli Restricted Boltzmann Machine. Mod Appl Sci 16(2):1–12
15.
Zurück zum Zitat Shurman MM, Khrais RM, Yateem AA (2020) DoS and DDoS attack detection using deep learning and IDS. Int Arab J Inf Technol 17(4A):655–661 Shurman MM, Khrais RM, Yateem AA (2020) DoS and DDoS attack detection using deep learning and IDS. Int Arab J Inf Technol 17(4A):655–661
16.
Zurück zum Zitat Lee SH, Shiue YL, Cheng CH, Li YH, Huang YF (2022) Detection and Prevention of DDoS Attacks on the IoT. Appl Sci 12(23):12407 Lee SH, Shiue YL, Cheng CH, Li YH, Huang YF (2022) Detection and Prevention of DDoS Attacks on the IoT. Appl Sci 12(23):12407
17.
Zurück zum Zitat Issa ASA, Albayrak Z (2023) Ddos attack intrusion detection system based on hybridization of cnn and lstm. Acta Polytech Hung 20(2):105–123 Issa ASA, Albayrak Z (2023) Ddos attack intrusion detection system based on hybridization of cnn and lstm. Acta Polytech Hung 20(2):105–123
18.
Zurück zum Zitat Caballero PB, Wang Q, Calero JMA (2023) Distributed dual-layer autonomous closed loops for self-protection of 5G/6G IoT networks from distributed denial of service attacks. Comput Networks 222:109526 Caballero PB, Wang Q, Calero JMA (2023) Distributed dual-layer autonomous closed loops for self-protection of 5G/6G IoT networks from distributed denial of service attacks. Comput Networks 222:109526
19.
Zurück zum Zitat Khedr WI, Gouda AE, Mohamed ER (2023) FMDADM: A Multi-Layer DDoS Attack Detection and Mitigation Framework Using Machine Learning for Stateful SDN-Based IoT Networks. IEEE Access 11:28934–28954 Khedr WI, Gouda AE, Mohamed ER (2023) FMDADM: A Multi-Layer DDoS Attack Detection and Mitigation Framework Using Machine Learning for Stateful SDN-Based IoT Networks. IEEE Access 11:28934–28954
20.
Zurück zum Zitat Hussain B, Du Q, Sun B, Han Z (2021) Deep Learning-Based DDoS-Attack Detection for Cyber-Physical System Over 5G Network. IEEE Trans Ind Inf 17(2):860–870 Hussain B, Du Q, Sun B, Han Z (2021) Deep Learning-Based DDoS-Attack Detection for Cyber-Physical System Over 5G Network. IEEE Trans Ind Inf 17(2):860–870
21.
Zurück zum Zitat Lawal MA, Shaikh RA, Hassan SR (2021) A DDoS attack mitigation framework for IoT networks using fog computing. Procedia Comput Sci 182:13–20 Lawal MA, Shaikh RA, Hassan SR (2021) A DDoS attack mitigation framework for IoT networks using fog computing. Procedia Comput Sci 182:13–20
22.
Zurück zum Zitat Bårli EM, Yazidi A, Viedma EH, Haugerud H (2021) DoS and DDoS mitigation using variational autoencoders. Comput Networks 199:108399 Bårli EM, Yazidi A, Viedma EH, Haugerud H (2021) DoS and DDoS mitigation using variational autoencoders. Comput Networks 199:108399
23.
Zurück zum Zitat Jmal R, Ghabri W, Guesmi R, Alshammari BM, Alshammari AS, Alsaif H (2023) Distributed Blockchain-SDN Secure IoT System Based on ANN to Mitigate DDoS Attacks. Appl Sci 13(8):4953 Jmal R, Ghabri W, Guesmi R, Alshammari BM, Alshammari AS, Alsaif H (2023) Distributed Blockchain-SDN Secure IoT System Based on ANN to Mitigate DDoS Attacks. Appl Sci 13(8):4953
24.
Zurück zum Zitat Aslam M, Ye D, Tariq A, Asad M, Hanif M, Ndzi D, Chelloug SA, Elaziz MA, Al-Qaness MAA, Jilani SF (2022) Adaptive machine learning based distributed denial-of-services attacks detection and mitigation system for SDN-enabled IoT. Sensors 22(7):2697 Aslam M, Ye D, Tariq A, Asad M, Hanif M, Ndzi D, Chelloug SA, Elaziz MA, Al-Qaness MAA, Jilani SF (2022) Adaptive machine learning based distributed denial-of-services attacks detection and mitigation system for SDN-enabled IoT. Sensors 22(7):2697
25.
Zurück zum Zitat Hassan KF, Manaa ME (2022) Detection and mitigation of DDoS attacks in internet of things using a fog computing hybrid approach. Bull Electr Eng Inf 11(3):1604–1613 Hassan KF, Manaa ME (2022) Detection and mitigation of DDoS attacks in internet of things using a fog computing hybrid approach. Bull Electr Eng Inf 11(3):1604–1613
26.
Zurück zum Zitat Khan IA, Keshk M, Pi D, Khan N, Hussain Y, Soliman H (2022) Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems. Ad Hoc Netw 134:102930 Khan IA, Keshk M, Pi D, Khan N, Hussain Y, Soliman H (2022) Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems. Ad Hoc Netw 134:102930
27.
Zurück zum Zitat Khan IA, Pi D, Abbas MZ, Zia U, Hussain Y, Soliman H (2022) Federated-SRUs: A Federated-Simple-Recurrent-Units-Based IDS for Accurate Detection of Cyber Attacks Against IoT-Augmented Industrial Control Systems. IEEE Internet Things J 10(10):8467–8476 Khan IA, Pi D, Abbas MZ, Zia U, Hussain Y, Soliman H (2022) Federated-SRUs: A Federated-Simple-Recurrent-Units-Based IDS for Accurate Detection of Cyber Attacks Against IoT-Augmented Industrial Control Systems. IEEE Internet Things J 10(10):8467–8476
28.
Zurück zum Zitat Khan IA, Moustafa N, Pi D, Sallam KM, Zomaya AY, Li B (2021) A New Explainable Deep Learning Framework for Cyber Threat Discovery in Industrial IoT Networks. IEEE Internet Things J 9(13):11604–11613 Khan IA, Moustafa N, Pi D, Sallam KM, Zomaya AY, Li B (2021) A New Explainable Deep Learning Framework for Cyber Threat Discovery in Industrial IoT Networks. IEEE Internet Things J 9(13):11604–11613
29.
Zurück zum Zitat Singh A, Gupta BB Distributed Denial-of-Service (DDoS) Attacks and Defense Mechanisms in Various Web-Enabled Computing Platforms: Issues, Challenges, and Future Research Directions. Int J Semant Web Inf Syst (IJSWIS) 18(1): 43(2022). Singh A, Gupta BB Distributed Denial-of-Service (DDoS) Attacks and Defense Mechanisms in Various Web-Enabled Computing Platforms: Issues, Challenges, and Future Research Directions. Int J Semant Web Inf Syst (IJSWIS) 18(1): 43(2022).
30.
Zurück zum Zitat Mishra A, Gupta N, Gupta BB (2021) Defense mechanisms against DDoS attack based on entropy in SDN-cloud using POX controller. Telecommun Syst 77:47–62 Mishra A, Gupta N, Gupta BB (2021) Defense mechanisms against DDoS attack based on entropy in SDN-cloud using POX controller. Telecommun Syst 77:47–62
31.
Zurück zum Zitat Mishra A, Joshi BK, Arya V, Gupta AK, Chui KT (2022) Detection of Distributed Denial of Service (DDoS) Attacks Using Computational Intelligence and Majority Vote-Based Ensemble Approach. Int J Software Sci Comput Intell (IJSSCI) 14(1):10 Mishra A, Joshi BK, Arya V, Gupta AK, Chui KT (2022) Detection of Distributed Denial of Service (DDoS) Attacks Using Computational Intelligence and Majority Vote-Based Ensemble Approach. Int J Software Sci Comput Intell (IJSSCI) 14(1):10
32.
Zurück zum Zitat Badis H, Munaretto, A, Aghal, KA, and Pujolle G (2004) Optimal path selection in a link state QoS routing protocol, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514), Milan, Italy. Badis H, Munaretto, A, Aghal, KA, and Pujolle G (2004) Optimal path selection in a link state QoS routing protocol, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514), Milan, Italy.
33.
Zurück zum Zitat Yazdinejad A, Dehghantanha A, Parizi RM, Hammoudeh M, Karimipour H, Srivastava G (2022) Block hunter: Federated learning for cyber threat hunting in blockchain-based iiot networks. IEEE Trans Ind Inf 18(11):8356–8366 Yazdinejad A, Dehghantanha A, Parizi RM, Hammoudeh M, Karimipour H, Srivastava G (2022) Block hunter: Federated learning for cyber threat hunting in blockchain-based iiot networks. IEEE Trans Ind Inf 18(11):8356–8366
34.
Zurück zum Zitat Srivastava G (2022) Block Hunter: Federated Learning for Cyber Threat Hunting in Blockchain-Based IIoT Networks. IEEE Trans Ind Inf 18(11):8356–8366 Srivastava G (2022) Block Hunter: Federated Learning for Cyber Threat Hunting in Blockchain-Based IIoT Networks. IEEE Trans Ind Inf 18(11):8356–8366
35.
Zurück zum Zitat Namakshenas D, Yazdinejad A, Dehghantanha A, & Srivastava G (2024) Federated quantum-based privacy-preserving threat detection model for consumer internet of things. IEEE Trans Consum Electron. Namakshenas D, Yazdinejad A, Dehghantanha A, & Srivastava G (2024) Federated quantum-based privacy-preserving threat detection model for consumer internet of things. IEEE Trans Consum Electron.
36.
Zurück zum Zitat Yazdinejad A, Dehghantanha A, Srivastava G, Karimipour H, Parizi RM (2024) Hybrid privacy preserving federated learning against irregular users in next-generation Internet of Things. J Syst Archit 148:103088 Yazdinejad A, Dehghantanha A, Srivastava G, Karimipour H, Parizi RM (2024) Hybrid privacy preserving federated learning against irregular users in next-generation Internet of Things. J Syst Archit 148:103088
37.
Zurück zum Zitat Yazdinejad A, Dehghantanha A, Karimipour H, Srivastava G, & Parizi RM (2024) A robust privacy-preserving federated learning model against model poisoning attacks. IEEE Trans Inf Forensics Secur. Yazdinejad A, Dehghantanha A, Karimipour H, Srivastava G, & Parizi RM (2024) A robust privacy-preserving federated learning model against model poisoning attacks. IEEE Trans Inf Forensics Secur.
38.
Zurück zum Zitat Akhtar MM, Shatat ASA, Al-Hashimi M, Zamani AS, Rizwanullah M, Mohamed SSI, Ayub R (2023) MapReduce with deep learning framework for student health monitoring system using IoT technology for big data. J Grid Comput 21(4):67 Akhtar MM, Shatat ASA, Al-Hashimi M, Zamani AS, Rizwanullah M, Mohamed SSI, Ayub R (2023) MapReduce with deep learning framework for student health monitoring system using IoT technology for big data. J Grid Comput 21(4):67
39.
Zurück zum Zitat Zamani AS, Shatat ASA, Khan IA, Akhtar MM, Ayub R, Samdani F (2022) Cloud Network Design and Requirements for the Virtualization System for IoT Networks. IJCSNS 22(11):727 Zamani AS, Shatat ASA, Khan IA, Akhtar MM, Ayub R, Samdani F (2022) Cloud Network Design and Requirements for the Virtualization System for IoT Networks. IJCSNS 22(11):727
40.
Zurück zum Zitat Shatat ASA, Akhtar MM, Zamani AS, Dilshad S, & Samdani F (2022) Big Data Driven Map Reduce Framework for Automated Flood Disaster Detection Based on Heuristic-Based Ensemble Learning. Cybern Syst 1–35. Shatat ASA, Akhtar MM, Zamani AS, Dilshad S, & Samdani F (2022) Big Data Driven Map Reduce Framework for Automated Flood Disaster Detection Based on Heuristic-Based Ensemble Learning. Cybern Syst 1–35.
41.
Zurück zum Zitat Akhtar MM, Shatat RSA, Shatat ASA, Hameed SA, Alnajdawi SI (2023) IoMT-based smart healthcare monitoring system using adaptive wavelet entropy deep feature fusion and improved RNN. Multimedia Tools Appl 82(11):17353–17390 Akhtar MM, Shatat RSA, Shatat ASA, Hameed SA, Alnajdawi SI (2023) IoMT-based smart healthcare monitoring system using adaptive wavelet entropy deep feature fusion and improved RNN. Multimedia Tools Appl 82(11):17353–17390
42.
Zurück zum Zitat Anaraki MV, Farzin S (2024) The Pine Cone Optimization Algorithm (PCOA). Biomimetics 9(2):91 Anaraki MV, Farzin S (2024) The Pine Cone Optimization Algorithm (PCOA). Biomimetics 9(2):91
43.
Zurück zum Zitat Dabbaghjamanesh M, Moeini A, Kimball J, & Zhang J (2019) Using gated recurrent units for selective harmonic current mitigation-pwm in grid-tied cascaded h-bridge converters. IEEE Trans Ind Appl. Dabbaghjamanesh M, Moeini A, Kimball J, & Zhang J (2019) Using gated recurrent units for selective harmonic current mitigation-pwm in grid-tied cascaded h-bridge converters. IEEE Trans Ind Appl.
44.
Zurück zum Zitat Mezina A, Burget R, Travieso-González CM (2021) Network anomaly detection with temporal convolutional network and U-Net model. IEEE Access 9:143608–143622 Mezina A, Burget R, Travieso-González CM (2021) Network anomaly detection with temporal convolutional network and U-Net model. IEEE Access 9:143608–143622
45.
Zurück zum Zitat Singh H, Sharma S, Khurana M, Kaur M, Lee HN (2022) Binary Drone Squadron optimization approaches for feature selection. IEEE Access 10:87099–87114 Singh H, Sharma S, Khurana M, Kaur M, Lee HN (2022) Binary Drone Squadron optimization approaches for feature selection. IEEE Access 10:87099–87114
46.
Zurück zum Zitat Rao MR & Sundar S (2023) An Efficient Method for Optimal Allocation of Resources in LPWAN Using Hybrid Coati-Energy Valley Optimization Algorithm Based on Reinforcement Learning. IEEE Access. Rao MR & Sundar S (2023) An Efficient Method for Optimal Allocation of Resources in LPWAN Using Hybrid Coati-Energy Valley Optimization Algorithm Based on Reinforcement Learning. IEEE Access.
47.
Zurück zum Zitat Shi H, Li J, Zafetti N (2020) New optimized technique for unknown parameters selection of SOFC using converged grass fibrous root optimization algorithm. Energy Rep 6:1428–1437 Shi H, Li J, Zafetti N (2020) New optimized technique for unknown parameters selection of SOFC using converged grass fibrous root optimization algorithm. Energy Rep 6:1428–1437
48.
Zurück zum Zitat Saheed YK, Arowolo MO (2021) Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms. IEEE Access 9:161546–161554 Saheed YK, Arowolo MO (2021) Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms. IEEE Access 9:161546–161554
49.
Zurück zum Zitat Khan Z, Chowdhury M, Islam M, Huang CY, Rahman M (2020) Long short-term memory neural network-based attack detection model for in-vehicle network security. IEEE Sens Lett 4(6):1–4 Khan Z, Chowdhury M, Islam M, Huang CY, Rahman M (2020) Long short-term memory neural network-based attack detection model for in-vehicle network security. IEEE Sens Lett 4(6):1–4
50.
Zurück zum Zitat Gadallah WG, Ibrahim HM, Omar NM (2024) A deep learning technique to detect distributed denial of service attacks in software-defined networks. Comput Secur 137:103588 Gadallah WG, Ibrahim HM, Omar NM (2024) A deep learning technique to detect distributed denial of service attacks in software-defined networks. Comput Secur 137:103588
51.
Zurück zum Zitat Becerra-Suarez FL, Fernández-Roman I, Forero MG (2024) Improvement of Distributed Denial of Service Attack Detection through Machine Learning and Data Processing. Mathematics 12(9):1294 Becerra-Suarez FL, Fernández-Roman I, Forero MG (2024) Improvement of Distributed Denial of Service Attack Detection through Machine Learning and Data Processing. Mathematics 12(9):1294
52.
Zurück zum Zitat Abid YA, Wu J, Xu G, Fu S, Waqas M (2024) Multilevel Deep Neural Network Approach for Enhanced Distributed Denial-of-Service Attack Detection and Classification in Software-Defined Internet of Things Networks. IEEE Internet Things J 11(14):24715–24725 Abid YA, Wu J, Xu G, Fu S, Waqas M (2024) Multilevel Deep Neural Network Approach for Enhanced Distributed Denial-of-Service Attack Detection and Classification in Software-Defined Internet of Things Networks. IEEE Internet Things J 11(14):24715–24725
53.
Zurück zum Zitat Durairaj D, Venkatasamy TK, Mehbodniya A, Umar S, Alam T (2024) Intrusion detection and mitigation of attacks in microgrid using enhanced deep belief network. Energy Sources, Part A 46(1):1519–1541 Durairaj D, Venkatasamy TK, Mehbodniya A, Umar S, Alam T (2024) Intrusion detection and mitigation of attacks in microgrid using enhanced deep belief network. Energy Sources, Part A 46(1):1519–1541
54.
Zurück zum Zitat Paidipati KK, Kurangi C, Uthayakumar J, Padmanayaki S, Pradeepa D, Nithinsha S (2024) Ensemble of deep reinforcement learning with optimization model for DDoS attack detection and classification in cloud based software defined networks. Multimedia Tools Appl 83(11):32367–32385 Paidipati KK, Kurangi C, Uthayakumar J, Padmanayaki S, Pradeepa D, Nithinsha S (2024) Ensemble of deep reinforcement learning with optimization model for DDoS attack detection and classification in cloud based software defined networks. Multimedia Tools Appl 83(11):32367–32385
55.
Zurück zum Zitat Dora VRS & Lakshmi VN (2024) Smart network security using advanced ensemble-DDoS attack detection and hybrid JA-SLOA-linked optimal routing-based mitigation. Aust J Electr Electron Eng 1–23. Dora VRS & Lakshmi VN (2024) Smart network security using advanced ensemble-DDoS attack detection and hybrid JA-SLOA-linked optimal routing-based mitigation. Aust J Electr Electron Eng 1–23.
56.
Zurück zum Zitat Pandithurai O, Venkataiah C, Tiwari S, Ramanjaneyulu N (2024) DDoS attack prediction using a honey badger optimization algorithm based feature selection and Bi-LSTM in cloud environment. Expert Syst Appl 241:122544 Pandithurai O, Venkataiah C, Tiwari S, Ramanjaneyulu N (2024) DDoS attack prediction using a honey badger optimization algorithm based feature selection and Bi-LSTM in cloud environment. Expert Syst Appl 241:122544
57.
Zurück zum Zitat Wasserman L, and Wasserman Y (2022) Hospital cybersecurity risks and gaps: Review (for the non-cyber professional). Frontiers. Wasserman L, and Wasserman Y (2022) Hospital cybersecurity risks and gaps: Review (for the non-cyber professional). Frontiers.
58.
Zurück zum Zitat Bhunia SS, Gurusamy M (2017) Dynamic Attack Detection and Mitigation in IoT using SDN. 27th International Telecommunication Networks and Applications Conference (ITNAC). Bhunia SS, Gurusamy M (2017) Dynamic Attack Detection and Mitigation in IoT using SDN. 27th International Telecommunication Networks and Applications Conference (ITNAC).
Metadaten
Titel
Distributed denial of service attack detection and mitigation strategy in 5G-enabled internet of things networks with adaptive cascaded gated recurrent unit
verfasst von
Md. Mobin Akhtar
Sultan Ali Alasmari
Sk Wasim Haidar
Ali Abdulaziz Alzubaidi
Publikationsdatum
01.04.2025
Verlag
Springer US
Erschienen in
Peer-to-Peer Networking and Applications / Ausgabe 2/2025
Print ISSN: 1936-6442
Elektronische ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-024-01894-6