A Backdoor Approach With Inverted Labels Using Dirty Label-Flipping Attacks

A Backdoor Approach With Inverted Labels Using Dirty Label-Flipping Attacks

Audio-based machine learning systems frequently use public or third-party data, which might be inaccurate. This exposes deep neural network (DNN) models trained on such data to potential data poisoning attacks. In this type of assault, attackers can train the DNN model using poisoned data, potential...

Full description

Saved in:

Bibliographic Details
Main Author:	Orson Mengara
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Poisoning attacks backdoor attacks adversarial machine learning
Online Access:	https://ieeexplore.ieee.org/document/10483076/
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Effective defense against physically embedded backdoor attacks via clustering-based filtering
by: Mohammed Kutbi
Published: (2025-04-01)

FLARE: A Backdoor Attack to Federated Learning with Refined Evasion
by: Qingya Wang, et al.
Published: (2024-11-01)

A4FL: Federated Adversarial Defense via Adversarial Training and Pruning Against Backdoor Attack
by: Saeed-Uz-Zaman, et al.
Published: (2025-01-01)

A Backdoor Attack Against LSTM-Based Text Classification Systems
by: Jiazhu Dai, et al.
Published: (2019-01-01)

Improved Distributed Backdoor Attacks in Federated Learning by Density-Adaptive Data Poisoning and Projection-Based Gradient Updating
by: Jian Wang, et al.
Published: (2025-01-01)

Adversarial Training for Mitigating Insider-Driven XAI-Based Backdoor Attacks
by: R. G. Gayathri, et al.
Published: (2025-05-01)

CleanSheet: Advancing backdoor attack techniques for deep neural networks with stealthy trigger embedding
by: Ahmed Bensaoud, et al.
Published: (2025-12-01)

Clean-label backdoor attack on link prediction task
by: Junming Mo, et al.
Published: (2025-08-01)

Multi-Targeted Textual Backdoor Attack: Model-Specific Misrecognition via Trigger Position and Word Choice
by: Taehwa Lee, et al.
Published: (2025-01-01)

Text Select-Backdoor: Selective Backdoor Attack for Text Recognition Systems
by: Hyun Kwon, et al.
Published: (2024-01-01)

EarlyExodus: Leveraging early exits to mitigate backdoor vulnerability in deep learning
by: Salmane Douch, et al.
Published: (2025-09-01)

Survey on Backdoor Attacks on Deep Learning: Current Trends, Categorization, Applications, Research Challenges, and Future Prospects
by: Muhammad Abdullah Hanif, et al.
Published: (2025-01-01)

Data Poisoning Attack on Black-Box Neural Machine Translation to Truncate Translation
by: Lingfang Li, et al.
Published: (2024-12-01)

A sparse and invisible targeted backdoor attack in federated learning
by: Qikun Zhang, et al.
Published: (2025-07-01)

Backdoor defense method in federated learning based on contrastive training
by: Jiale ZHANG, et al.
Published: (2024-03-01)

A survey of backdoor attacks and defences: From deep neural networks to large language models
by: Ling-Xin Jin, et al.
Published: (2025-09-01)

Backdoor Attack Based on Lossy Image Compression Using Discrete Cosine Transform
by: Yuting Liu, et al.
Published: (2024-01-01)

Backdoor Attack to Giant Model in Fragment-Sharing Federated Learning
by: Senmao Qi, et al.
Published: (2024-12-01)

Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data
by: Donik Vrsnak, et al.
Published: (2025-01-01)

Label flipping adversarial attack on graph neural network
by: Yiteng WU, et al.
Published: (2021-09-01)

Backdoor Attack Against Dataset Distillation in Natural Language Processing
by: Yuhao Chen, et al.
Published: (2024-12-01)

Natural Occlusion-Based Backdoor Attacks: A Novel Approach to Compromising Pedestrian Detectors
by: Qiong Li, et al.
Published: (2025-07-01)

CLB-Defense: based on contrastive learning defense for graph neural network against backdoor attack
by: Jinyin CHEN, et al.
Published: (2023-04-01)

Stealthy graph backdoor attack based on feature trigger
by: Yang Chen, et al.
Published: (2025-06-01)

Edge-Assisted Label-Flipping Attack Detection in Federated Learning
by: Nourah S. AlOtaibi, et al.
Published: (2024-01-01)

Defending Deep Neural Networks Against Backdoor Attack by Using De-Trigger Autoencoder
by: Hyun Kwon
Published: (2025-01-01)

A Novel and Efficient Multi-Target Backdoor Attack for Deep Learning-Based Wireless Signal Classifiers
by: Nayan Moni Baishya, et al.
Published: (2025-01-01)

Survey on vertical federated learning: algorithm, privacy and security
by: Jinyin CHEN, et al.
Published: (2023-04-01)

Trustworthiness of Deep Learning Under Adversarial Attacks in Power Systems
by: Dowens Nicolas, et al.
Published: (2025-05-01)

Light Attack: A Physical World Real-Time Attack Against Object Classifiers
by: Ruizhe Hu, et al.
Published: (2025-01-01)

Securing federated learning: a defense strategy against targeted data poisoning attack
by: Ansam Khraisat, et al.
Published: (2025-02-01)

Breaking and Healing: GAN-Based Adversarial Attacks and Post-Adversarial Recovery for 5G IDSs
by: Yasmeen Alslman, et al.
Published: (2025-01-01)

FedG2L: a privacy-preserving federated learning scheme base on “G2L” against poisoning attack
by: Mengfan Xu, et al.
Published: (2023-12-01)

Survey of optical-based physical domain adversarial attacks and defense
by: CHEN Jinyin, et al.
Published: (2024-04-01)

Disruptive attacks on artificial neural networks: A systematic review of attack techniques, detection methods, and protection strategies
by: Ahmad Alobaid, et al.
Published: (2025-06-01)

Investigating the Transferability of TOG Adversarial Attacks in YOLO Models in the Maritime Domain
by: Phornphawit Manasut, et al.
Published: (2025-01-01)

Detecting Black-Box Model Probing Attacks Through Probability Scores
by: Yongzhi Wang, et al.
Published: (2025-01-01)

Defense against Adversarial Attacks in Image Recognition Based on Multilayer Filters
by: Mingde Wang, et al.
Published: (2024-09-01)

A Meta-Reinforcement Learning-Based Poisoning Attack Framework Against Federated Learning
by: Wei Zhou, et al.
Published: (2025-01-01)

Empirical study of privacy inference attack against deep reinforcement learning models
by: Huaicheng Zhou, et al.
Published: (2023-12-01)