ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
Low Cost₹1501 / $59
CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks
Authors
Immaraju Priyanka , K. Samson Paul
Keywords
Machine Learning, Time Series Analysis, Server Health Monitoring, DDoS Attacks, Anomaly Detection, Network Security.
Abstract
The increasing frequency and sophistication of Distributed Denial-of-Service (DDoS) attacks pose serious challenges to maintaining server reliability and operational continuity in modern network infrastructures. Traditional monitoring systems often fail to detect early signs of performance degradation caused by such attacks due to their inability to handle dynamic, high-dimensional data streams. This research presents an intelligent time series monitoring framework leveraging machine learning techniques for proactive server health assessment and DDoS attack mitigation. The proposed model analyzes real-time performance indicators such as CPU utilization, memory consumption, network throughput, and latency to identify anomalous behavior patterns associated with DDoS activities. Using supervised and unsupervised learning algorithms, including Random Forest, Long Short-Term Memory (LSTM), and Autoencoders, the system performs both predictive forecasting and anomaly detection over time series data. Experimental evaluations demonstrate that the proposed approach achieves superior detection accuracy, low false alarm rates, and robust adaptability under varying attack intensities. The study highlights the potential of machine learning-based time series modeling as a reliable and scalable solution for enhancing server resilience and ensuring continuous service availability against evolving DDoS threats.
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How To Cite
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IJCRT — journal style
"Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.c540-c551, April 2026, Available :https://ijcrt.org/papers/IJCRT2604304.pdf
APA — 7th edition
Priyanka, I., & Paul, K. S. (2026). Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks. International Journal of Creative Research Thoughts, 14(4), c540-c551. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304
MLA — 9th edition
Priyanka, Immaraju, and K. Samson Paul. "Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. c540-c551, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304.
Chicago — 17th, bibliography
Priyanka, Immaraju, and K. Samson Paul. "Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks." International Journal of Creative Research Thoughts 14, no. 4 (2026): c540-c551. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304.
Harvard — author–date
Priyanka, I. and Paul, K.S. (2026) 'Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks', International Journal of Creative Research Thoughts, 14(4), pp. c540-c551. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304
IEEE — numbered reference
I. Priyanka and K. S. Paul, "Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks," IJCRT, vol. 14, no. 4, pp. c540-c551, Apr. 2026.
Vancouver — biomedical
Priyanka I, Paul KS. Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks. IJCRT. 2026 Apr;14(4):c540-c551.
AMA — 11th edition
Priyanka I, Paul KS. Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks. IJCRT. 2026;14(4):c540-c551. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2604304,
author = {Immaraju Priyanka and K. Samson Paul},
title = {Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {c540-c551},
year = {2026},
month = {April},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Priyanka, Immaraju
AU - Paul, K. Samson
TI - Intelligent Time Series Monitoring for Server Reliability Using Machine Learning Against DDoS Attacks
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304
SP - c540-c551
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : c540-c551
Article Information
- Pages
- c540-c551
- Published
- April 2026
- Registration ID
- IJCRT_305262
- Published Paper ID
- IJCRT2604304
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Kurnool, Andhra Pradesh, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 167
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604304
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2604304.pdf
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International Journal of Creative Research Thoughts
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2320-2882
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The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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