Hybrid machine learning model for network traffic anomaly detection using time-series forecasting
Pratik Kumar Swainpratikkumarswain.official@gmail.comFaculty of Engineering and TechnologySri Sri UniversityCuttack, Odisha, 754006, India0009-0005-2577-0508View full profile → , Ansuman Patnaikansuman.patnaik@stellantis.comStellantis BangaloreBangalore, Karnataka, 560001, IndiaView full profile → , *Suneeta SatpathyCorresponding authorsuneeta1912@gmail.comCenter for Cyber SecuritySOA UniversityBhubaneswar, Odisha, 751030, India0000-0002-6943-171XView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 10 Dec 2024
- Published Online:
- 30 Sep 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2017
- Pages:
- 1881–1890
Abstract
Keywords
Subject Classifications
References
[1] A. K. Saini, M. L. Saini, D. K. Srivastava, S. Singh, P. Vats, and T. K. Tak, “Secure communication framework using lattice-based encryption and image steganography,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 5-B, pp. 1855–1864 (2025).
[2] S. Satpathy, P. K. Swain, S. N. Mohanty, and S. S. Basa, “Enhancing security: Federated learning against man-in-the-middle threats with gradient boosting machines and LSTM,” in 2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 1–8 (2024).
[3] P. R. Kumar and B. Shilpa, “An IoT-based smart healthcare system with edge intelligence computing,” in Reconnoitering the Landscape of Edge Intelligence in Healthcare, Apple Academic Press, pp. 31–46 (2024).
[4] K. Choi, J. Yi, C. Park, and S. Yoon, “Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines,” IEEE Access, vol. 9, pp. 120043–120065 (2021).
[5] K. H. Lai, D. Zha, J. Xu, Y. Zhao, G. Wang, and X. Hu, “Revisiting time series outlier detection: Definitions and benchmarks,” in Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track (Round 1) (2021).
[6] S. Kim, K. Choi, H.-S. Choi, B. Lee, and S. Yoon, “Towards a rigorous evaluation of time-series anomaly detection,” in Proc. AAAI Conf. Artificial Intelligence, vol. 36, no. 7, pp. 7194–7201 (2022).
[7] B. Shilpa, P. R. Kumar, and R. K. Jha, “LoRa DL: A deep learning model for enhancing the data transmission over LoRa using autoencoder,” J. Supercomput., vol. 79, no. 15, pp. 17079–17097 (2023).
[8] B. Bojarajulu and S. Tanwar, “Customized convolutional neural network model for IoT botnet attack detection,” Signal, Image Video Process., pp. 1–13 (2024).
[9] H. Garg, S. Jhunthra, R. Goel, S. Sharma, V. Gupta, R. Sharma, and P. Dass, “Understanding user polarisation regarding COVID-19 vaccines through social network analysis,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 27, no. 8, pp. 2301–2336 (2024).
[10] B. Shilpa, P. R. Kumar, and R. K. Jha, “Spreading factor optimization for interference mitigation in dense indoor LoRa networks,” in 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), pp. 1–5 (2023).
[11] G. B. Mohammad, Shitharth, and P. R. Kumar, “Integrated machine learning model for URL phishing detection,” International Journal of Grid and Distributed Computing, vol. 14, no. 1, pp. 513–529 (2021).
[12] N. Keerthana, H. M. A. Ghanimi, P. V. V. S. Srinivas, N. R. Pendli, F. T. Ayasrah, M. A. Bennet, S. Sengan, and P. Dadheech, “Blockchain-based cybersecurity: A predictive privacy and security of cyber-physical systems,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 5-B, pp. 1911–1922 (2025).
[13] P. R. Kumar, “Wireless mobile charger using inductive coupling,” J. Emerg. Technol. Innov. Res. (JETIR), vol. 5, no. 10, pp. 40–44 (2018).
[14] R. F. Fouladi, O. Ermiş, and E. Anarim, “A DDoS attack detection and defense scheme using time-series analysis for SDN,” J. Inf. Secur. Appl., vol. 54, no. 102587 (2020).
[15] S. Sharma, A. K. Patel, and N. Menaria, “Integral transform of product of generalized k-Bessel function and generalized Hurwitz-Lerch Zeta function,” Journal of Interdisciplinary Mathematics, vol. 27, no. 8, pp. 1757–1764 (2024).
