Data anomaly detection method and device, readable storage medium and electronic device

Abstract

The invention relates to a data anomaly detection method and device, a readable storage medium and an electronic device. The method comprises steps as follows: acquiring current index data; acquiring a time sequence set corresponding to the current index data; as for each time sequence in the time sequence set, whether a memory neuron for recording the time sequence exists is judged; when the memory neuron is judged to exist, the memory neuron is activated; when the memory neuron is judged not to exist, one memory neuron is allocated for the time sequence to record the time sequence, and the allocated memory neuron is activated; whether the current index data are abnormal is determined at least according to the activated memory neuron. Accordingly, the anomaly monitoring system has higher adaptability to different types of index data and complex change index data, the larger the scale of the acquired index data is, the higher the study capability and judgement capability is, and the higher the accuracy of anomaly detection is.

Description

Technical field [0001] The present disclosure relates to the field of abnormality detection, and in particular, to a data abnormality detection method, device, readable storage medium, and electronic equipment. Background technique [0002] Data anomaly detection technology plays an extremely important role in all walks of life. For example, discovering small changes in patients’ heartbeat, blood pressure, breathing and other indicators, locating suspicious operating behaviors of key system administrators, and detecting abnormal stock price changes in the stock market. Detect the instability of key indicators such as CPU, memory, HTTP response time of the application system, etc. The realization of these functions is inseparable from fast and accurate data anomaly detection methods. [0003] However, with the rapid development of computer software technology, the implementation of monitoring systems, especially abnormal monitoring systems, becomes more and more difficult. The mai...

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Problems solved by technology

[0003] However, with the rapid development of computer software technology, it becomes more and more difficult to realize the monitoring system, especially the abnormal monitoring system.

The main reasons are as follows: (1) Due to the increasing scale of monitored applications, more and more indicators are included in the monitoring; (2) The complexity of the monitoring system is getting higher and higher, and the regularity of indicator changes (3) The traditional time series analysis model used for anomaly detection is becoming less and less adaptable to highly complex index changes, which not only leads to increased computational complexity, but also reduces the effectiveness of anomaly detection. also affected

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