Bit Flip

Bit-flip attacks (BFAs) exploit the vulnerability of deep neural networks (DNNs) by subtly altering their parameters, specifically targeting bits within model weights or even executable code. Current research focuses on developing more effective BFAs, including those tailored to specific DNN architectures like graph neural networks, and exploring attack strategies that require minimal bit modifications, even down to single-bit flips. These attacks highlight significant security risks in deploying DNNs, prompting investigations into robust defense mechanisms and secure compilation techniques for improved resilience against such manipulations.

Papers

November 12, 2024

Impactful Bit-Flip Search on Full-precision Models
Nadav Benedek, Matan Levy, Mahmood Sharif
Search Query Latent Vulnerability Accurate Model Bit Flip Attack Bit Flip

November 2, 2023

Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent
Lorenz Kummer, Samir Moustafa, Nils N. Kriege, Wilfried N. Gansterer
Graph Neural Network Weisfeiler Leman Bit Flip Attack Bit Flip Flip Attack Fault Injection Attack

September 12, 2023

Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces in DNN Executables
Yanzuo Chen (1), Zhibo Liu (1), Yuanyuan Yuan (1), Sihang Hu (2), Tianxiang Li (2), Shuai Wang (1) ((1) The Hong Kong University of Science and Technology, (2) Huawei Technologies)
DNN Framework Bit Flip Attack Bit Flip

August 12, 2023

One-bit Flip is All You Need: When Bit-flip Attack Meets Model Training
Jianshuo Dong, Han Qiu, Yiming Li, Tianwei Zhang, Yuanjie Li, Zeqi Lai, Chao Zhang, Shu-Tao Xia
Model Training Malicious Model Bit Flip Attack Bit Flip Flip Attack Bit Training

April 14, 2023

A Byte Sequence is Worth an Image: CNN for File Fragment Classification Using Bit Shift and n-Gram Embeddings
Wenyang Liu, Yi Wang, Kejun Wu, Kim-Hui Yap, Lap-Pui Chau
CNN Network N Gram Sub Byte Bit Flip File Classification Aware Fragment Intra Byte

July 27, 2022

Hardly Perceptible Trojan Attack against Neural Networks with Bit Flips
Jiawang Bai, Kuofeng Gao, Dihong Gong, Shu-Tao Xia, Zhifeng Li, Wei Liu
Neural Network Attack Performance Trojan Attack Bit Flip

July 25, 2022

Versatile Weight Attack via Flipping Limited Bits
Jiawang Bai, Baoyuan Wu, Zhifeng Li, Shu-tao Xia
Adversarial Attack Backdoor Poisoning Attack Bit Flip Attack Paradigm

February 1, 2022

Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Georgii Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Dimitrov, Ivan Oseledets
Back Propagation Neural Network Training Memory Reduction Bit Flip

December 7, 2021

BDFA: A Blind Data Adversarial Bit-flip Attack on Deep Neural Networks
Behnam Ghavami, Mani Sadati, Mohammad Shahidzadeh, Zhenman Fang, Lesley Shannon
Deep Neural Network Feedback Alignment Accuracy Loss Bit Flip Attack Bit Flip Flip Attack