A Bayesian LSTM Based Active Anomaly Detection Service for Large Online Systems (Internetware 2024 - Research Track) - Internetware 2024

Wed 24 - Fri 26 July 2024 Macau, China

Who

Chen Wang, Tao Huang, Min Li, Pengfei Chen, Zhiwen Chen

Track

Internetware 2024 Research Track

Time Zone

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When

Fri 26 Jul 2024 11:50 - 12:05 at Main Conference Room - Session 11: Anomaly Detection and Security Chair(s): Yang Feng

Chen Wang

Tao Huang

Min Li

Pengfei Chen

Sun Yat-sen University

Zhiwen Chen

Time Zone

The program is currently displayed in (GMT+08:00) Beijing, Chongqing, Hong Kong, Urumqi.

Use conference time zone: (GMT+08:00) Beijing, Chongqing, Hong Kong, UrumqiSelect other time zone

The GMT offsets shown reflect the offsets at the moment of the conference.

Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
The time band will also limit the events that are included in the personal iCalendar subscription service.

Display full programSpecify a time band

Session Program

Fri 26 Jul
Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

	11:20 - 12:20	Session 11: Anomaly Detection and SecurityResearch Track at Main Conference Room Chair(s): Yang Feng Nanjing University

	11:20 15m Full-paper		LSTD-MTS: Anomaly Detection with Capturing Long-Term Spatio-Temporal Dependence for Multi-dimensional Time Series Research Track Haoyang Zeng , Ningjiang Chen Guangxi University, Tao Deng
	11:35 15m Full-paper		CIDF:Combined Intrusion Detection Framework in Industrial Control Systems based on Packet Signature and Enhanced FSFDP Research Track Jianwen Xiang , Xuemin Zhang , Qianrong Zheng , longmin Deng , Dongdong Zhao , Junwei Zhou
	11:50 15m Full-paper		A Bayesian LSTM Based Active Anomaly Detection Service for Large Online Systems Research Track Chen Wang , Tao Huang , Min Li , Pengfei Chen Sun Yat-sen University, Zhiwen Chen
	12:05 15m Full-paper		LateBA: Latent Backdoor Attack on Deep Bug Search via Infrequent Execution Codes Research Track Xiaoyu Yi , Guolei Li Shanghai Jiao Tong University, Wenkai Huang Shanghai Jiao Tong University, Xi Lin Shanghai Jiao Tong University, Jianhua Li Shanghai JiaoTong University, Yuchen Liu North Carolina State University