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ARIMA Based Network Anomaly Detection
Abstract
An early warning system on potential attacks from networks will enable network administrators or even automated network management software to take preventive measures. This is needed as we move towards maximizing the utilization of the network with new paradigms such as Web Services and Software As A Service. This paper introduces a novel approach through using Auto-Regressive Integrated Moving Average (ARIMA) technique to detect potential attacks that may occur in the network. The solution is able to provide feedback through its predictive capabilities and hence provide an early warning system. With the affirmative results, this technique can serve beyond the detection of Denial of Service (DoS) and with sufficient development; an automated defensive solution can be achieved.
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Cited by
Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks
Liu, P., Xu, H., Ouyang, Q., Jiao, R., Chen, Z., Zhang, S., Yang, J., Mo, L., Zeng, J., Xue, W., et al. (2020) · 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE) · doi:10.1109/issre5003.2020.00014 · Cited by 252
Vehicle operating state anomaly detection and results virtual reality interpretation
Alizadeh, M., Hamilton, M., Jones, P., Ma, J., & Jaradat, R. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.114928 · Cited by 18
Metadata
- Authors
- Yaacob, A. H., Tan, I. K. T., Chien, S. F., & Tan, H. K.
- Venue
- 2010 Second International Conference on Communication Software and Networks
- Publisher
- IEEE
- Published
- 2010
- Pages
- 205-209
- OpenAlex
- W2080099070
- Cited by
- 168
- References
- 0
- FWCI
- 2.89
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: ARIMA Based Network Anomaly Detection. https://app.cochat.ai/papers/10.1109/iccsn.2010.55
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- Yaacob, A. H., Tan, I. K. T., Chien, S. F., & Tan, H. K. (2010). ARIMA Based Network Anomaly Detection. 2010 Second International Conference on Communication Software and Networks. https://doi.org/10.1109/iccsn.2010.55
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