d0e4950c-6377-4f66-8458-767ea2506a1f beie director@blueeyesintelligence.org 10.35940/ijitee.B1032.14020125 10.1016/j.cose.2021.102580F. Khoda Parast, C. Sindhav, S. Nikam, H. Izadi Yekta, K. B. Kent, and S. Hakak, "Cloud computing security: A survey of service-based models," Comput. Secur., vol. 114, p. 102580, Mar. 2022, DOI: https://doi.org/10.1016/j.cose.2021.10258010.1016/j.compeleceng.2022.108466H. Lin, C. Wu, and M. Masdari, "A comprehensive survey of network traffic anomalies and DDoS attacks detection schemes using fuzzy techniques," Comput. Electr. Eng., vol. 104, p. 108466, 2022, DOI: https://doi.org/10.1016/j.compeleceng.2022.10846610.1109/COMST.2018.2863942X. Jing, Z. Yan, and W. Pedrycz, "Security Data Collection and Data Analytics in the Internet: A Survey," IEEE Commun. Surv. Tutorials, vol. 21, no. 1, pp. 586-618, 2019, DOI: https://doi.org/10.1109/COMST.2018.286394210.1016/j.cosrev.2019.05.002R. Kumar and R. Goyal, "On cloud security requirements, threats, vulnerabilities and countermeasures: A survey," Comput. Sci. Rev., vol. 33, pp. 1-48, 2019, DOI: https://doi.org/10.1016/j.cosrev.2019.05.00210.1007/s11227-020-03213-1H. Tabrizchi and M. Kuchaki Rafsanjani, "A survey on security challenges in cloud computing: issues, threats, and solutions," J. Supercomput., vol. 76, no. 12, pp.10.1007/s11227-020-03213-19493-9532, 2020, DOI: https://doi.org/10.1007/s11227-020-03213-110.1109/CSITSS.2018.8768551K. B. V., N. D. G., and P. S. Hiremath, "Detection of DDoS Attacks in Software Defined Networks," in 2018 3rd International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS), 2018, pp. 265-270. DOI: https://doi.org/10.1109/CSITSS.2018.876855110.1109/ICTC49870.2020.9289504J. Ali, B. Roh, B. Lee, J. Oh, and M. Adil, "A Machine Learning Framework for Prevention of Software-Defined Networking controller from DDoS Attacks and dimensionality reduction of big data," in 2020 International Conference on Information and Communication Technology Convergence (ICTC), 2020, pp. 515-519. DOI: https://doi.org/10.1109/ICTC49870.2020.928950410.1016/j.eswa.2020.114520A. E. Cil, K. Yildiz, and A. Buldu, "Detection of DDoS attacks with feed forward based deep neural network model," Expert Syst. Appl., vol. 169, p. 114520, 2021, DOI: https://doi.org/10.1016/j.eswa.2020.11452010.1016/j.future.2020.01.025M. Albanese, A. De Benedictis, D. D. J. de Macedo, and F. Messina, "Security and trust in cloud application life-cycle management," Futur. Gener. Comput. Syst., vol. 111, pp. 934-936, 2020, DOI: https://doi.org/10.1016/j.future.2020.01.02510.1109/ACCESS.2019.2896783T. V Phan and M. Park, "Efficient Distributed Denial-of-Service Attack Defense in SDN-Based Cloud," IEEE Access, vol. 7, pp. 18701-18714, 2019, DOI: https://doi.org/10.1109/ACCESS.2019.289678310.1109/ACCESS.2020.3028690A. Bhardwaj, V. Mangat, and R. Vig, "Hyperband Tuned Deep Neural Network With Well Posed Stacked Sparse AutoEncoder for Detection of DDoS Attacks in Cloud," IEEE Access, vol. 8, pp. 181916-181929, 2020, DOI: https://doi.org/10.1109/ACCESS.2020.302869010.1016/j.jisa.2020.102621J. David and C. Thomas, "Detection of distributed denial of service attacks based on information theoretic approach in time series models," J. Inf. Secur. Appl., vol. 55, p. 102621, 2020, DOI: https://doi.org/10.1016/j.jisa.2020.10262110.1007/s12065-019-00340-4D. J. Prathyusha and G. Kannayaram, "A cognitive mechanism for mitigating DDoS attacks using the artificial immune system in a cloud environment," Evol. Intell., vol. 14, no. 2, pp. 607-618, 2021, DOI: https://doi.org/10.1007/s12065-019-00340-410.1007/978-3-031-09484-2_2T.-H. Vuong, C.-V. N. Thi, and Q.-T. Ha, "N-Tier Machine Learning-Based Architecture for DDoS Attack Detection," in Intelligent Information and Database Systems, 2021, pp. 375-385, DOI: https://doi.org/10.1007/978-3-031-09484-2_210.1016/j.comnet.2021.108076N. Gupta, V. Jindal, and P. Bedi, "LIO-IDS: Handling class imbalance using LSTM and improved one-vs-one technique in intrusion detection system," Comput. Networks, vol. 192, p. 108076, 2021, DOI: https://doi.org/10.1016/j.comnet.2021.10807610.1109/ACCESS.2021.3123791Y. Wei, J. Jang-Jaccard, F. Sabrina, A. Singh, W. Xu, and S. Camtepe, "AE-MLP: A Hybrid Deep Learning Approach for DDoS Detection and Classification," IEEE Access, vol. 9, pp. 146810-146821, 2021, DOI: https://doi.org/10.1109/ACCESS.2021.312379110.11591/ijai.v10.i2.pp382-388T. Khempetch and P. Wuttidittachotti, "DDoS attack detection using deep learning," vol. 10, no. 2, pp. 382-388, 2021, DOI: https://doi.org/10.11591/ijai.v10.i2.pp382-38810.1007/s11277-021-08271-zA. Agarwal, M. Khari, and R. Singh, "Detection of DDOS Attack using Deep Learning Model in Cloud Storage Application," Wirel. Pers. Commun., vol. 127, no. 1, pp. 419-439, 2022, DOI: https://doi.org/10.1007/s11277-021-08271-z10.1016/j.comnet.2022.109269R. K. Batchu and H. Seetha, "An integrated approach explaining the detection of distributed denial of service attacks," Comput. Networks, vol. 216, p. 109269, 2022, DOI: https://doi.org/10.1016/j.comnet.2022.10926910.1007/978-981-10-8536-9_17D. H. Parekh and R. Sridaran, "Mitigating cloud security threats using public-key infrastructure," in Cyber Security: Proceedings of CSI 2015, 2018, pp. 165-177, doi: https://doi.org/10.1007/978-981-10-8536-9_1710.3390/electronics10212673S. Rehman, N. Talat Bajwa, M. A. Shah, A. O. Aseeri, and A. Anjum, "Hybrid AES-ECC Model for the Security of Data over Cloud Storage," Electronics, vol. 10, no. 21, 2021, DOI: https://doi.org/10.3390/electronics1021267310.1016/j.future.2018.05.065A. Nanda, P. Nanda, X. He, A. Jamdagni, and D. Puthal, "A hybrid encryption technique for Secure-GLOR: The adaptive secure routing protocol for dynamic wireless mesh networks," Futur. Gener. Comput. Syst., vol. 109, pp. 521-530, 2020, DOI: https://doi.org/10.1016/j.future.2018.05.06510.1109/ACCESS.2020.3035845H. Aliev and H.-W. Kim, "Matrix-Based Dynamic Authentication With Conditional Privacy-Preservation for Vehicular Network Security," IEEE Access, vol. 8, pp. 200883-200896, 2020, DOI: https://doi.org/10.1109/ACCESS.2020.303584510.1016/j.jisa.2021.102779B. Alaya and L. SELLAMI, "Clustering method and symmetric/asymmetric cryptography scheme adapted to securing urban VANET networks," J. Inf. Secur. Appl., vol. 58, p. 102779, 2021, DOI: https://doi.org/10.1016/j.jisa.2021.10277910.1016/j.matpr.2020.07.452D. K. R. Shukla, V. K. R. Dwivedi, and M. C. Trivedi, "Encryption algorithm in cloud computing," Mater. Today Proc., vol. 37, pp. 1869-1875, 2021, DOI: https://doi.org/10.1016/j.matpr.2020.07.45210.9734/ajrcos/2021/v8i230195H. S. Yahia et al., "Comprehensive survey for cloud computing based nature-inspired algorithms optimization scheduling," Asian J. Res. Comput. Sci., vol. 8, no. 2, pp. 1-16, 2021, DOI: https://doi.org/10.9734/ajrcos/2021/v8i23019510.1007/978-981-15-7345-3_46P. Chinnasamy, S. Padmavathi, R. Swathy, and S. Rakesh, "Efficient Data Security Using Hybrid Cryptography on Cloud Computing," in Inventive Communication and Computational Technologies, 2021, pp. 537-547, DOI: https://doi.org/10.1007/978-981-15-7345-3_4610.1007/978-3-030-49500-8_20V. K. Soman and V. Natarajan, "Analysis of Hybrid Data Security Algorithms for Cloud," in Second International Conference on Networks and Advances in Computational Technologies, 2021, pp. 231-242, DOI: https://doi.org/10.1007/978-3-030-49500-8_2010.1007/978-981-33-4543-0_48F. K. Mupila and H. Gupta, "An Innovative Authentication Model for the Enhancement of Cloud Security," in Innovations in Computer Science and Engineering, 2021, pp. 447-455, DOI: https://doi.org/10.1007/978-981-33-4543-0_4810.1109/JSYST.2021.3092521D. Saxena, I. Gupta, J. Kumar, A. K. Singh, and X. Wen, "A Secure and Multiobjective Virtual Machine Placement Framework for Cloud Data Center," IEEE Syst. J., vol. 16, no. 2, pp. 3163-3174, 2022, DOI: https://doi.org/10.1109/JSYST.2021.309252110.1016/j.ijin.2022.04.001F. Thabit, O. Can, S. Alhomdy, G. H. Al-Gaphari, and S. Jagtap, "A Novel Effective Lightweight Homomorphic Cryptographic Algorithm for data security in cloud computing," Int. J. Intell. Networks, vol. 3, pp. 16-30, 2022, DOI: https://doi.org/10.1016/j.ijin.2022.04.00110.1007/978-981-16-9416-5_22B. Thakkar and B. Thankachan, "An Approach for Enhancing Security of Data over Cloud Using Multilevel Algorithm," in Congress on Intelligent Systems, 2022, pp. 305-318, DOI: https://doi.org/10.1007/978-981-16-9416-5_2210.1016/j.compeleceng.2022.107947F. Pandey, P. Dash, D. Samanta, and M. Sarma, "Efficient and provably secure intelligent geometrical method of secret key generation for cryptographic applications," Comput. Electr. Eng., vol. 101, p. 107947, 2022, DOI: https://doi.org/10.1016/j.compeleceng.2022.10794710.1016/j.comnet.2021.108498R. K. Batchu and H. Seetha, "A generalized machine learning model for DDoS attacks detection using hybrid feature selection and hyperparameter tuning," Comput. Networks, vol. 200, p. 108498, 2021, DOI: https://doi.org/10.1016/j.comnet.2021.10849810.1016/j.cose.2022.102748D. Akgun, S. Hizal, and U. Cavusoglu, "A new DDoS attacks intrusion detection model based on deep learning for cybersecurity," Comput. Secur., vol. 118, p. 102748, 2022, DOI: https://doi.org/10.1016/j.cose.2022.10274810.1080/21642583.2019.1708830J. Xue and B. Shen, "A novel swarm intelligence optimization approach: sparrow search algorithm," Syst. Sci. & Control Eng., vol. 8, no. 1, pp. 22-34, 2020, DOI: https://doi.org/10.1080/21642583.2019.170883010.1109/ICAC3N53548.2021.9725640R. Kumar, M. Memoria, A. Gupta, and M. Awasthi, "Critical Analysis of Genetic Algorithm under Crossover and Mutation Rate," in 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), 2021, pp. 976-980. DOI:: https://doi.org/10.1109/ICAC3N53548.2021.972564010.1016/j.cose.2022.102815C. E. L. BALMANY, Z. TBATOU, A. ASIMI, and M. BAMAROUF, "Secure Virtual Machine Image Storage Process into a Trusted Zone-based Cloud Storage," Comput. Secur., vol. 120, p. 102815, 2022, DOI: https://doi.org/10.1016/j.cose.2022.10281510.1109/SSP53291.2023.10207927D. N. Tran, B. L. Vu, and X. N. Tien, "Improved Deterministic Usage of the Elliptic Curve Digital Signature Algorithm with Scrypt," in 2023 IEEE Statistical Signal Processing Workshop (SSP), 2023, pp. 611-615. DOI: https://doi.org/10.1109/SSP53291.2023.1020792710.1007/978-3-031-32959-3R. Banoth and R. Regar, Classical and Modern Cryptography for Beginners. Springer Nature, 2023, DOI: https://doi.org/10.1007/978-3-031-32959-310.1007/978-3-031-32959-3_2R. Banoth and R. Regar, "Security Standards for Classical and Modern Cryptography," in Classical and Modern Cryptography for Beginners, Cham: Springer Nature Switzerland, 2023, pp. 47-83. DOI: https://doi.org/10.1007/978-3-031-32959-3_210.1109/ICICT48043.2020.9112491V. S. Shetty, R. Anusha, D. Kumar M.J., and P. Hegde N., "A Survey on Performance Analysis of Block Cipher Algorithms," in 2020 International Conference on Inventive Computation Technologies (ICICT), 2020, pp. 167-174. DOI: https://doi.org/10.1109/ICICT48043.2020.911249110.1109/IWBIS56557.2022.9924954P. Oktivasari, M. Agustin, R. E. M. Akbar, A. Kurniawan, A. R. Zain, and F. A. Murad, "Analysis of ECG Image File Encryption using ECDH and AES-GCM Algorithm," in 2022 7th International Workshop on Big Data and Information Security (IWBIS), 2022, pp. 75-80. DOI: https://doi.org/10.1109/IWBIS56557.2022.992495410.1007/978-3-031-32959-3_4R. Banoth and R. Regar, "Asymmetric Key Cryptography," in Classical and Modern Cryptography for Beginners, Cham: Springer Nature Switzerland, 2023, pp. 109-165.10.1007/978-3-031-32959-3_4DOI: https://doi.org/10.1007/978-3-031-32959-3_410.1109/AINIT54228.2021.00129M. Ma, "Comparison between RSA and ECC," in 2021 2nd International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), 2021, pp. 642-645. DOI: https://doi.org/10.1109/AINIT54228.2021.0012910.1016/j.future.2021.06.047M. P. Novaes, L. F. Carvalho, J. Lloret, and M. L. Proença, "Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments," Futur. Gener. Comput. Syst., vol. 125, pp. 156-167, Dec. 2021, DOI: https://doi.org/10.1016/j.future.2021.06.04710.1016/j.jksuci.2019.04.010R. Priyadarshini and R. K. Barik, "A deep learning based intelligent framework to mitigate DDoS attack in fog environment," J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 3, pp. 825-831, 2022, DOI: https://doi.org/10.1016/j.jksuci.2019.04.01010.1016/j.cose.2019.101645M. Wang, Y. Lu, and J. Qin, "A dynamic MLP-based DDoS attack detection method using feature selection and feedback," Comput. Secur., vol. 88, p. 101645, 2020, DOI: https://doi.org/10.1016/j.cose.2019.10164510.1016/j.compeleceng.2020.106738M. V. O. de Assis, L. F. Carvalho, J. J. P. C. Rodrigues, J. Lloret, and M. L. Proença Jr, "Near real-time security system applied to SDN environments in IoT networks using convolutional neural network," Comput. Electr. Eng., vol. 86, p. 106738, 2020, DOI: https://doi.org/10.1016/j.compeleceng.2020.10673810.35940/ijitee.A8166.1110120Midha, S., & Kaur, G. (2020). Svm Implementation for Ddos Attacks in Software Defined Networks. In International Journal of Innovative Technology and Exploring Engineering (Vol. 10, Issue 1, pp. 205-212). DOI: https://doi.org/10.35940/ijitee.A8166.111012010.35940/ijrte.B3670.078219R, P., & M, P. (2019). Artificial Neural Network (ANN) Based DDoS Attack Detection Model on Software Defined Networking (SDN). In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 2, pp. 4887-4894). DOI: https://doi.org/10.35940/ijrte.B3670.07821910.35940/ijeat.B3736.129219Prasad, D. (2019). Improving Security for Internet of Things Devices using Software Defined Networking. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 2, pp. 2881-2884). DOI: https://doi.org/10.35940/ijeat.B3736.129219