In the last few years, detection has become a powerful methodology for network protection and security. This paper presents a new detection scheme for data recorded over a computer network. This approach is applicable to the broad scientific field of information security, including intrusion detection and prevention. The proposed method employs bidimensional (time‐frequency) data representations of the forms of the short‐time Fourier transform, as well as the Wigner distribution. Moreover, the method applies matrix factorization using singular value decomposition and principal component analysis of the two‐dimensional data representation matrices to detect intrusions. The current scheme was evaluated using numerous tests on network activities, which were recorded and presented in the KDD‐NSL and UNSW‐NB15 datasets. The efficiency and robustness of the technique have been experimentally proved.

中文翻译：

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基于时间和频率表示的矩阵分解的网络入侵检测方法

在过去的几年中，检测已成为网络保护和安全性的强大方法。本文提出了一种对计算机网络上记录的数据的新检测方案。这种方法适用于广泛的信息安全科学领域，包括入侵检测和预防。所提出的方法采用了短时傅立叶变换以及维格纳分布形式的二维（时频）数据表示。此外，该方法使用奇异值分解和二维数据表示矩阵的主成分分析来应用矩阵分解，以检测入侵。目前的方案已通过对网络活动的大量测试进行了评估，这些测试已记录并呈现在KDD‐NSL和UNSW‐NB15数据集中。