MatsVD: Boosting Statement-Level Vulnerability Detection via Dependency-Based Attention (Internetware 2024 - Research Track) - Internetware 2024

Wed 24 - Fri 26 July 2024 Macau, China

Who

Cheng Weng, Yihao Qin, Bo Lin, Pei Liu, Liqian Chen

Track

Internetware 2024 Research Track

This program is tentative and subject to change.

Time Zone

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When

Wed 24 Jul 2024 17:05 - 17:20 at Main Conference Room - Session 3: Software Vulnerability and Security Chair(s): Cuiyun Gao

Cheng Weng

Yihao Qin

Bo Lin

National University of Defense Technology

China

Pei Liu

Liqian Chen

National University of Defense Technology, China

China

This program is tentative and subject to change.

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

Wed 24 Jul
Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

	16:50 - 18:05	Session 3: Software Vulnerability and SecurityResearch Track at Main Conference Room Chair(s): Cuiyun Gao Harbin Institute of Technology

	16:50 15m Full-paper		Inside Bug Report Templates: An Empirical Study on Bug Report Templates in Open-Source Software Research Track Junwei Zhang Zhejiang University, Zhongxin Liu Zhejiang University, Lingfeng Bao Zhejiang University, Zhenchang Xing CSIRO’s Data61; Australian National University, Xing Hu Zhejiang University, Xin Xia Huawei Technologies
	17:05 15m Full-paper		MatsVD: Boosting Statement-Level Vulnerability Detection via Dependency-Based Attention Research Track Cheng Weng , Yihao Qin , Bo Lin National University of Defense Technology, Pei Liu , Liqian Chen National University of Defense Technology, China
	17:20 15m Full-paper		Enhancing Deep Learning Vulnerability Detection through Imbalance Loss Functions: An Empirical Study Research Track Yanzhong He Wuhan University of Technology, Guancheng Lin , Xiaoxue Ma City University of Hong Kong, Jacky Keung City University of Hong Kong, Cheng Tan Wuhan University of Technology, Wenhua Hu , Fuyang Li Wuhan University of Technology
	17:35 15m Full-paper		DFEPT: Data Flow Embedding for Enhancing Pre-Trained Model Based Vulnerability Detection Research Track Zhonghao Jiang , Weifeng Sun , Xiaoyan Gu , Jiaxin Wu , Tao Wen , Haibo Hu , Meng Yan Chongqing University
	17:50 15m Full-paper		T-RAP: A Template-guided Retrieval-Augmented Vulnerability Patch Generation Approach Research Track Pei Liu , Bo Lin National University of Defense Technology, Yihao Qin National University of Defense Technology, Cheng Weng , Liqian Chen National University of Defense Technology, China