Cover Image

MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Hyo Seo, Luo, Gang, Chen, Can, Wang, Binghui, Duan, Yue, Wang, Ren
Format:	Preprint
Published:	2026
Subjects:	Cryptography and Security Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SilentDrift: Exploiting Action Chunking for Stealthy Backdoor Attacks on Vision-Language-Action Models
by: Xu, Bingxin, et al.
Published: (2026)

Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
by: Hong, Hanbin, et al.
Published: (2023)

Exploiting AI for Attacks: On the Interplay between Adversarial AI and Offensive AI
by: Schröer, Saskia Laura, et al.
Published: (2025)

Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
by: Noorbakhsh, Sayedeh Leila, et al.
Published: (2024)

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)

Co-Evolutionary Multi-Modal Alignment via Structured Adversarial Evolution
by: Shi, Guoxin, et al.
Published: (2026)

Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses
by: Yang, Yuxin, et al.
Published: (2024)

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

GraphAttack: Exploiting Representational Blindspots in LLM Safety Mechanisms
by: He, Sinan, et al.
Published: (2025)

Provably Robust Explainable Graph Neural Networks against Graph Perturbation Attacks
by: Li, Jiate, et al.
Published: (2025)

AGNNCert: Defending Graph Neural Networks against Arbitrary Perturbations with Deterministic Certification
by: Li, Jiate, et al.
Published: (2025)

Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack
by: Xue, Jing, et al.
Published: (2025)

Practicable Black-box Evasion Attacks on Link Prediction in Dynamic Graphs -- A Graph Sequential Embedding Method
by: Li, Jiate, et al.
Published: (2024)

Practical, Generalizable and Robust Backdoor Attacks on Text-to-Image Diffusion Models
by: Dai, Haoran, et al.
Published: (2025)

A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
by: Luo, Xuan, et al.
Published: (2025)

A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
by: Yang, Yuxin, et al.
Published: (2024)

Misrouter: Exploiting Routing Mechanisms for Input-Only Attacks on Mixture-of-Experts LLMs
by: Fei, Zekun, et al.
Published: (2026)

Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
by: Nie, Chenfei, et al.
Published: (2024)

Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations
by: Li, Jiate, et al.
Published: (2025)

PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models
by: Zou, Wei, et al.
Published: (2024)

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

Co-Evolutionary Defence of Active Directory Attack Graphs via GNN-Approximated Dynamic Programming
by: Goel, Diksha, et al.
Published: (2025)

A Comprehensive Analysis of Adversarial Attacks against Spam Filters
by: Hotoğlu, Esra, et al.
Published: (2025)

CAN-Trace Attack: Exploit CAN Messages to Uncover Driving Trajectories
by: Lin, Xiaojie, et al.
Published: (2025)

Adversarial Attack Based Countermeasures against Deep Learning Side-Channel Attacks
by: Gu, Ruizhe, et al.
Published: (2020)

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs
by: Chen, Yunhao, et al.
Published: (2025)

Quantization Aware Attack: Enhancing Transferable Adversarial Attacks by Model Quantization
by: Yang, Yulong, et al.
Published: (2023)

Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective
by: Wang, Zifan, et al.
Published: (2024)

Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
by: Wang, Yujing, et al.
Published: (2024)

Exploiting Leakage in Password Managers via Injection Attacks
by: Fábrega, Andrés, et al.
Published: (2024)

MoEcho: Exploiting Side-Channel Attacks to Compromise User Privacy in Mixture-of-Experts LLMs
by: Ding, Ruyi, et al.
Published: (2025)

SwitchPatch: Physical Adversarial Attack Strategy with Switchable Adversarial Objectives
by: Jiang, Hanrui, et al.
Published: (2025)

Off-Path TCP Exploits: PMTUD Breaks TCP Connection Isolation in IP Address Sharing Scenarios
by: Feng, Xuewei, et al.
Published: (2025)

Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2026)

Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
by: Luo, Xinjian, et al.
Published: (2020)

Specific Emitter Identification Based on Joint Variational Mode Decomposition
by: Chen, Xiaofang, et al.
Published: (2024)

RECTor: Robust and Efficient Correlation Attack on Tor
by: Wu, Binghui, et al.
Published: (2025)

Towards Understanding and Characterizing Vulnerabilities in Intelligent Connected Vehicles through Real-World Exploits
by: Wang, Yuelin, et al.
Published: (2026)

"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages
by: Yuan, Ying, et al.
Published: (2024)

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