BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks
Fri 2 May 2025 10:30 - 11:00 at Canada Hall 3 Poster Area - Fri Morning Break Posters 10:30-11
Pre-trained large deep learning models are now serving as the dominant component for downstream middleware users and have revolutionized the learning paradigm, replacing the traditional approach of training from scratch locally. To reduce development costs, developers often integrate third-party pre-trained deep neural networks (DNNs) into their intelligent software systems. However, utilizing untrusted DNNs presents significant security risks, as these models may contain intentional backdoor defects resulting from the black-box training process. These backdoor defects can be activated by hidden triggers, allowing attackers to maliciously control the model and compromise the overall reliability of the intelligent software. To ensure the safe adoption of DNNs in critical software systems, it is crucial to establish a backdoor defect database for localization studies. This paper addresses this research gap by introducing \emph{BDefects4NN}, the first backdoor defect database, which provides labeled backdoor-defected DNNs at the neuron granularity and enables controlled localization studies of defect root causes.
In \emph{BDefects4NN}, we define three defect injection rules and employ four representative backdoor attacks across four popular network architectures and three widely adopted datasets, yielding a comprehensive database of 1,654 backdoor-defected DNNs with four defect quantities and varying infected neurons. Based on \emph{BDefects4NN}, we conduct extensive experiments on evaluating six fault localization criteria and two defect repair techniques, which show limited effectiveness for backdoor defects. Additionally, we investigate backdoor-defected models in practical scenarios, specifically in lane detection for autonomous driving and large language models (LLMs), revealing potential threats and highlighting current limitations in precise defect localization. This paper aims to raise awareness of the threats brought by backdoor defects in our community and inspire future advancements in fault localization methods.
Thu 1 MayDisplayed time zone: Eastern Time (US & Canada) change
13:00 - 13:30 | Thu Lunch Posters 13:00-13:30Research Track / SE in Society (SEIS) / Journal-first Papers / SE In Practice (SEIP) at Canada Hall 3 Poster Area | ||
13:00 30mTalk | BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Research Track Yisong Xiao Beihang University, Aishan Liu Beihang University; Institute of Dataspace, Xinwei Zhang Beihang University, Tianyuan Zhang Beihang University, Li Tianlin NTU, Siyuan Liang National University of Singapore, Xianglong Liu Beihang University; Institute of Dataspace; Zhongguancun Laboratory, Yang Liu Nanyang Technological University, Dacheng Tao Nanyang Technological University | ||
13:00 30mTalk | Ethical Issues in Video Games: Insights from Reddit Discussions SE in Society (SEIS) | ||
13:00 30mTalk | An Empirical Study on Developers' Shared Conversations with ChatGPT in GitHub Pull Requests and Issues Journal-first Papers Huizi Hao Queen's University, Canada, Kazi Amit Hasan Queen's University, Canada, Hong Qin Queen's University, Marcos Macedo Queen's University, Yuan Tian Queen's University, Kingston, Ontario, Ding Steven, H., H. Queen’s University at Kingston, Ahmed E. Hassan Queen’s University | ||
13:00 30mTalk | QuanTest: Entanglement-Guided Testing of Quantum Neural Network SystemsQuantum Journal-first Papers Jinjing Shi Central South University, Zimeng Xiao Central South University, Heyuan Shi Central South University, Yu Jiang Tsinghua University, Xuelong LI China Telecom Link to publication | ||
13:00 30mPoster | FlatD: Protecting Deep Neural Network Program from Reversing Attacks SE In Practice (SEIP) Jinquan Zhang The Pennsylvania State University, Zihao Wang Penn State University, Pei Wang Independent Researcher, Rui Zhong Palo Alto Networks, Dinghao Wu Pennsylvania State University | ||
13:00 30mTalk | Building Domain-Specific Machine Learning Workflows: A Conceptual Framework for the State-of-the-PracticeSE for AI Journal-first Papers Bentley Oakes Polytechnique Montréal, Michalis Famelis Université de Montréal, Houari Sahraoui DIRO, Université de Montréal DOI Pre-print File Attached | ||
13:00 30mTalk | On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair tools.Security Journal-first Papers Aurora Papotti Vrije Universiteit Amsterdam, Ranindya Paramitha University of Trento, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam | ||
13:00 30mTalk | Automating Explanation Need Management in App Reviews: A Case Study from the Navigation App Industry SE In Practice (SEIP) Martin Obaidi Leibniz Universität Hannover, Nicolas Voß Graphmasters GmbH, Hannah Deters Leibniz University Hannover, Jakob Droste Leibniz Universität Hannover, Marc Herrmann Leibniz University Hannover, Jannik Fischbach Netlight Consulting GmbH and fortiss GmbH, Kurt Schneider Leibniz Universität Hannover, Software Engineering Group |
Fri 2 MayDisplayed time zone: Eastern Time (US & Canada) change
10:30 - 11:00 | Fri Morning Break Posters 10:30-11Journal-first Papers / SE In Practice (SEIP) / Research Track / SE in Society (SEIS) / New Ideas and Emerging Results (NIER) at Canada Hall 3 Poster Area | ||
10:30 30mTalk | An Empirical Study on Developers' Shared Conversations with ChatGPT in GitHub Pull Requests and Issues Journal-first Papers Huizi Hao Queen's University, Canada, Kazi Amit Hasan Queen's University, Canada, Hong Qin Queen's University, Marcos Macedo Queen's University, Yuan Tian Queen's University, Kingston, Ontario, Ding Steven, H., H. Queen’s University at Kingston, Ahmed E. Hassan Queen’s University | ||
10:30 30mTalk | Automating Explanation Need Management in App Reviews: A Case Study from the Navigation App Industry SE In Practice (SEIP) Martin Obaidi Leibniz Universität Hannover, Nicolas Voß Graphmasters GmbH, Hannah Deters Leibniz University Hannover, Jakob Droste Leibniz Universität Hannover, Marc Herrmann Leibniz University Hannover, Jannik Fischbach Netlight Consulting GmbH and fortiss GmbH, Kurt Schneider Leibniz Universität Hannover, Software Engineering Group | ||
10:30 30mTalk | On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair tools.Security Journal-first Papers Aurora Papotti Vrije Universiteit Amsterdam, Ranindya Paramitha University of Trento, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam | ||
10:30 30mTalk | Relevant information in TDD experiment reporting Journal-first Papers Fernando Uyaguari Instituto Superior Tecnológico Wissen, Silvia Teresita Acuña Castillo Universidad Autónoma de Madrid, John W. Castro Universidad de Atacama, Davide Fucci Blekinge Institute of Technology, Oscar Dieste Universidad Politécnica de Madrid, Sira Vegas Universidad Politecnica de Madrid | ||
10:30 30mTalk | BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks Research Track Yisong Xiao Beihang University, Aishan Liu Beihang University; Institute of Dataspace, Xinwei Zhang Beihang University, Tianyuan Zhang Beihang University, Li Tianlin NTU, Siyuan Liang National University of Singapore, Xianglong Liu Beihang University; Institute of Dataspace; Zhongguancun Laboratory, Yang Liu Nanyang Technological University, Dacheng Tao Nanyang Technological University | ||
10:30 30mTalk | Ethical Issues in Video Games: Insights from Reddit Discussions SE in Society (SEIS) | ||
10:30 30mTalk | SusDevOps: Promoting Sustainability to a First Principle in Software Delivery New Ideas and Emerging Results (NIER) Istvan David McMaster University / McMaster Centre for Software Certification (McSCert) |