n-INCLOF: A dynamic local outlier detection algorithm for data streams

With the development of the data stream technology, The way to detect anomalies in data streams accurately has been widespreadly concerned. According to the problem that the distribution of the number of the outliers in data streams is unstable, in this paper, the n-IncLOF incremental outlier detection algorithm is proposed which could adjust the n-threshold automaticly. The experiment of oultlier detection of the data stream proves that n-IncLOF algorithm could adjust to the change of the number of outliers effectively and it not only improves the detection rate greatly but also lowers the false alarm rate compared to the original incremental algorithm.