Cover Image

Attacking Attention of Foundation Models Disrupts Downstream Tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Silva, Hondamunige Prasanna, Becattini, Federico, Seidenari, Lorenzo
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adversarial Attacks on Downstream Weather Forecasting Models: Application to Tropical Cyclone Trajectory Prediction
by: Deng, Yue, et al.
Published: (2025)

How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?
by: Liu, Meiqi, et al.
Published: (2025)

Mitigating Downstream Model Risks via Model Provenance
by: Wang, Keyu, et al.
Published: (2024)

A Systematic Study of Model Extraction Attacks on Graph Foundation Models
by: Xu, Haoyan, et al.
Published: (2025)

Preliminary Investigation into Uncertainty-Aware Attack Stage Classification
by: Gaudenzi, Alessandro, et al.
Published: (2025)

Membership Inference Attacks on Sequence Models
by: Rossi, Lorenzo, et al.
Published: (2025)

Transferable Adversarial Attacks on SAM and Its Downstream Models
by: Xia, Song, et al.
Published: (2024)

Attack Smarter: Attention-Driven Fine-Grained Webpage Fingerprinting Attacks
by: Yuan, Yali, et al.
Published: (2025)

Low-Cost Hard-Label Adversarial Attack with Theoretical Foundations
by: Liu, Jun, et al.
Published: (2026)

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets
by: Zhang, Yechao, et al.
Published: (2025)

Learning to Poison Large Language Models for Downstream Manipulation
by: Zhou, Xiangyu, et al.
Published: (2024)

Using Graph Theory for Improving Machine Learning-based Detection of Cyber Attacks
by: Zonneveld, Giacomo, et al.
Published: (2024)

Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services
by: Fu, Shaopeng, et al.
Published: (2024)

Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
by: Zizzo, Giulio, et al.
Published: (2025)

Blind Baselines Beat Membership Inference Attacks for Foundation Models
by: Das, Debeshee, et al.
Published: (2024)

Task-Agnostic Attacks Against Vision Foundation Models
by: Pulfer, Brian, et al.
Published: (2025)

FedRecAttack: Model Poisoning Attack to Federated Recommendation
by: Rong, Dazhong, et al.
Published: (2022)

Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidence
by: Obadinma, Stephen, et al.
Published: (2024)

Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
by: Shi, Lijia, et al.
Published: (2024)

Model Extraction Attacks Revisited
by: Liang, Jiacheng, et al.
Published: (2023)

Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version]
by: Cortellazzi, Jacopo, et al.
Published: (2019)

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput
by: Pesoli, Alfredo, et al.
Published: (2026)

Model Hijacking Attack in Federated Learning
by: Li, Zheng, et al.
Published: (2024)

Diffusion-aided Task-oriented Semantic Communications with Model Inversion Attack
by: Wang, Xuesong, et al.
Published: (2025)

Attention Augmented GNN RNN-Attention Models for Advanced Cybersecurity Intrusion Detection
by: Biradar, Jayant, et al.
Published: (2025)

Unveiling ECC Vulnerabilities: LSTM Networks for Operation Recognition in Side-Channel Attacks
by: Battistello, Alberto, et al.
Published: (2025)

Backdoor Attacks on Discrete Graph Diffusion Models
by: Wang, Jiawen, et al.
Published: (2025)

RAPID: Robust APT Detection and Investigation Using Context-Aware Deep Learning
by: Amaru, Yonatan, et al.
Published: (2024)

GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation Models
by: Luo, Haozheng, et al.
Published: (2025)

TrojFM: Resource-efficient Backdoor Attacks against Very Large Foundation Models
by: Nie, Yuzhou., et al.
Published: (2024)

Attribute Inference Attacks for Federated Regression Tasks
by: Diana, Francesco, et al.
Published: (2024)

Model Inversion Attacks Meet Cryptographic Fuzzy Extractors
by: Prabhakar, Mallika, et al.
Published: (2025)

Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
by: Bertran, Martin, et al.
Published: (2024)

BadMerging: Backdoor Attacks Against Model Merging
by: Zhang, Jinghuai, et al.
Published: (2024)

Remote Timing Attacks on Efficient Language Model Inference
by: Carlini, Nicholas, et al.
Published: (2024)

UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models
by: Han, Yuning, et al.
Published: (2024)

Attention Tracker: Detecting Prompt Injection Attacks in LLMs
by: Hung, Kuo-Han, et al.
Published: (2024)

Towards Building Non-Fine-Tunable Foundation Models
by: Wang, Ziyao, et al.
Published: (2026)

Membership Inference Attacks on Large-Scale Models: A Survey
by: Wu, Hengyu, et al.
Published: (2025)

Ensembling Membership Inference Attacks Against Tabular Generative Models
by: Ward, Joshua, et al.
Published: (2025)