AD(2)S: Adaptive anomaly detection on sporadic data streams

doi:10.1016/j.comcom.2023.06.027

	AD(2)S: Adaptive anomaly detection on sporadic data streams
	Liu, Fengrui 1,2; Wang, Yang 1,2; Li, Zhenyu 1,2; Guan, Hongtao 1,2; Xie, Gaogang 2,3
	2023-09-01
发表期刊	COMPUTER COMMUNICATIONS
ISSN	0140-3664
卷号	209 页码:151-162
摘要	With the widespread use of Internet applications, ensuring the quality and reliability of online services has become increasingly important. Therefore, anomaly detection methods play a critical role in identifying potential anomalies in the data streams of infrastructure systems and service applications. However, most of known detection methods have an underlying assumption that the data streams are continuous. In practice, we learn that many real-world data streams can be sporadic. It incurs particular challenges for the task of anomaly detection, for which the common preprocessing of downsampling on sporadic data can omit potential anomalies and delay alarms. In this paper, we propose an ensemble learning-based anomaly detection method on sporadic data streams named AD2S. It consists of two modules: a monitor module to continuously and adaptively determine the measure windows for observations, and a detection module that utilizes an isolation partition strategy to estimate the anomaly degree of each incoming observation. Based on experimental results on eight synthetic and public real-world datasets, our method outperforms other state-of-the-art methods with an average AUC score of 0.923. Additionally, our analysis demonstrates that the proposed method has constant amortized time and space complexity, enabling once detection within an average of 9.9 ms and maximum memory usage of 26.14 KB. The code of AD2S is open-sourced for further research.
关键词	Anomaly detection Sporadic data Data streams Quality of service
DOI	10.1016/j.comcom.2023.06.027
收录类别	SCI
语种	英语
资助项目	National Key Ramp;D Program of China[2020YFB1805603] ; CAS-Austria Joint Project[171111KYSB20200001]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001040198100001
出版者	ELSEVIER
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21314
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xie, Gaogang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Fengrui,Wang, Yang,Li, Zhenyu,et al. AD(2)S: Adaptive anomaly detection on sporadic data streams[J]. COMPUTER COMMUNICATIONS,2023,209:151-162.
APA	Liu, Fengrui,Wang, Yang,Li, Zhenyu,Guan, Hongtao,&Xie, Gaogang.(2023).AD(2)S: Adaptive anomaly detection on sporadic data streams.COMPUTER COMMUNICATIONS,209,151-162.
MLA	Liu, Fengrui,et al."AD(2)S: Adaptive anomaly detection on sporadic data streams".COMPUTER COMMUNICATIONS 209(2023):151-162.