{"total":23,"rows":[{"id":"2405.09786","title":"IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency","created":"2024-05-16","cited_by_count":39,"area":null},{"id":"2407.19845","title":"BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning","created":"2024-07-29","cited_by_count":19,"area":null},{"id":"2312.08890","title":"Defenses in Adversarial Machine Learning: A Survey","created":"2023-12-13","cited_by_count":14,"area":null},{"id":"2503.15293","title":"Test-Time Backdoor Detection for Object Detection Models","created":"2025-03-19","cited_by_count":14,"area":null},{"id":"2312.12724","title":"Progressive Poisoned Data Isolation for Training-time Backdoor Defense","created":"2023-12-20","cited_by_count":10,"area":null},{"id":"2406.15093","title":"ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification","created":"2024-06-21","cited_by_count":9,"area":null},{"id":"2402.17465","title":"Model X-ray:Detecting Backdoored Models via Decision Boundary","created":"2024-02-27","cited_by_count":3,"area":null},{"id":"2402.16926","title":"On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem","created":"2024-02-26","cited_by_count":2,"area":null},{"id":"2404.11357","title":"Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving","created":"2024-04-17","cited_by_count":2,"area":null},{"id":"2510.14299","title":"TED++: Submanifold-Aware Backdoor Detection via Layerwise Tubular-Neighbourhood Screening","created":"2025-10-16","cited_by_count":2,"area":null},{"id":"2402.08695","title":"Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors","created":"2024-02-12","cited_by_count":1,"area":null},{"id":"2603.18103","title":"STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling","created":"2026-03-18","cited_by_count":1,"area":null},{"id":"2401.15002","title":"BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning","created":"2024-01-26","cited_by_count":0,"area":null},{"id":"2407.10180","title":"Defending Against Repetitive Backdoor Attacks on Semi-supervised Learning through Lens of Rate-Distortion-Perception Trade-off","created":"2024-07-14","cited_by_count":0,"area":null},{"id":"2410.14723","title":"BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2506.10722","title":"TED-LaST: Towards Robust Backdoor Defense Against Adaptive Attacks","created":"2025-06-12","cited_by_count":0,"area":null},{"id":"2511.09252","title":"Unveiling Hidden Threats: Using Fractal Triggers to Boost Stealthiness of Distributed Backdoor Attacks in Federated Learning","created":"2025-11-12","cited_by_count":0,"area":null},{"id":"2511.11625","title":"MedFedPure: A Medical Federated Framework with MAE-based Detection and Diffusion Purification for Inference-Time Attacks","created":"2025-11-07","cited_by_count":0,"area":null},{"id":"2512.10402","title":"The Eminence in Shadow: Exploiting Feature Boundary Ambiguity for Robust Backdoor Attacks","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2605.18908","title":"Fast and Lightweight Backdoor Detection via Head Random Probing","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2605.22365","title":"TimeGuard: Channel-wise Pool Training for Backdoor Defense in Time Series Forecasting","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2607.26099","title":"Lilith: Backdoor Generalization under Training-Inference Trigger Shift","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2609.03139","title":"Beyond Small Patches: Black-Box Detection and Purification of Diverse Backdoor Triggers","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}