基于 C-LSTM 的复杂网络数据流中连续异常值的检测方法

IF 1.6 Q2 ENGINEERING, MULTIDISCIPLINARY International Journal of System Assurance Engineering and Management Pub Date : 2024-08-29 DOI:10.1007/s13198-024-02475-9
Zhinian Shu, Xiaorong Li
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引用次数: 0

摘要

为了加强对复杂网络数据流中异常点的有效检测,进行多维动态检测,建立更加稳定可靠的数据流异常检测方法,提出了一种基于 C-LSTM 的复杂网络数据流连续异常点检测方法。提取复杂网络数据流中连续异常值的特征,并根据特征建立数据异常检测模型。将复杂网络数据流中连续异常值的输入特征定性定量地转化为多尺度异常值,实现了基于 C-LSTM 的异常值检测。实验结果表明,所提方法的灵敏度最高可达 42%,平均路由开销小于 24 Mb。无论任何场景下的数据,检测准确率都高于 0.92,召回率高于 0.81,F1 值高于 0.62。虽然由于噪声的影响,可能会有一些误判或遗漏,但总体检测性能良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The detection method of continuous outliers in complex network data streams based on C-LSTM

To enhance the effective detection of abnormal points in complex network data flow, perform multi-dimensional dynamic detection, and establish a more stable and reliable data flow abnormal detection method, a continuous abnormal point detection method for complex network data flow based on C-LSTM is proposed. The features of continuous outliers in complex network data streams are extracted, and a data anomaly detection model is established according to the features. The input features of continuous outliers in complex network data streams are qualitatively and quantitatively transformed into multi-scale anomalies, and the outlier detection based on C-LSTM is realized. The experimental results show that the maximum sensitivity of the proposed method reaches 42%, and the average routing overhead is less than 24 Mb. Regardless of the data in any scenario, the detection accuracy is higher than 0.92, the recall is higher than 0.81, and the F1 value is higher than 0.62. Although there may be some misjudgments or omissions due to noise, the overall detection performance is good.

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来源期刊
CiteScore
4.30
自引率
10.00%
发文量
252
期刊介绍: This Journal is established with a view to cater to increased awareness for high quality research in the seamless integration of heterogeneous technologies to formulate bankable solutions to the emergent complex engineering problems. Assurance engineering could be thought of as relating to the provision of higher confidence in the reliable and secure implementation of a system’s critical characteristic features through the espousal of a holistic approach by using a wide variety of cross disciplinary tools and techniques. Successful realization of sustainable and dependable products, systems and services involves an extensive adoption of Reliability, Quality, Safety and Risk related procedures for achieving high assurancelevels of performance; also pivotal are the management issues related to risk and uncertainty that govern the practical constraints encountered in their deployment. It is our intention to provide a platform for the modeling and analysis of large engineering systems, among the other aforementioned allied goals of systems assurance engineering, leading to the enforcement of performance enhancement measures. Achieving a fine balance between theory and practice is the primary focus. The Journal only publishes high quality papers that have passed the rigorous peer review procedure of an archival scientific Journal. The aim is an increasing number of submissions, wide circulation and a high impact factor.
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