Papers Adversarial Attack
“Adversarial Attack” 태그가 달린 논문 1,998편 · 필터 해제
Large-scale Testing Global Optimization Methods with Black-box Adversarial Attacks
Existing global optimization benchmark suites are of a moderate size and are based on a small number of analytical functions that date back even to the 1970s. This causes a risk of biasing the development of global optim…
Adversarial AttackUniversal Concept Disruption for SAM3 Image Segmentation
SAM3 extends promptable segmentation from geometry-driven mask prediction to open-vocabulary concept segmentation, where a text-conditioned grounding model decides whether a concept is present and segments all matching i…
Adversarial RobustnessImage SegmentationAdversarial AttackMissClick: Exploiting Digit-Serialized Coordinates to Attack GUI Grounding Models
Recent GUI visual grounding models generate screen coordinates as sequences of digit tokens that are parsed into numerical values and mapped to executable clicks. The security implications of this coordinate generation p…
Adversarial AttackVisual GroundingAdversarial Deepfake Generation and an Investigation of Purification-Based Adversarial Detection
This paper describes the participation of team "Go To Germany" in the ImageCLEF 2026 Deepfake Detection and Generation Task. For the image generation task, we employ FLUX.1-dev with PuLID for identity-preserving face syn…
DeepFake DetectionAdversarial AttackImage GenerationGeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation
Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic understanding. Existing studies mainly focus on corrupting visual inputs …
Adversarial AttackGuardianAgentBench: Where Agents Fail and How to Guard Them
As large language model agents increasingly operate autonomously with access to tools and external environments, ensuring their safe and reliable behavior becomes critical. We present GuardianAgentBench (GABench), a benc…
Adversarial AttackEGRNet: A Lightweight Semantic Segmentation Network with Edge-Gated Refinement and Adversarial Sensing
As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semantic segmentation plays a key role in enabling autonomous vehicles to …
Real-Time Semantic SegmentationScene UnderstandingAutonomous VehiclesAdversarial AttackBadWAM: When World-Action Models Dream Right but Act Wrong
World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representations that couple action generation with future world prediction. This co…
Adversarial AttackAdversarial Attacks on Online Handwriting using Salience-based Temporal Editing
Deep learning models for online handwriting recognition have been shown effective and are increasingly deployed in practical applications. However, their vulnerability to adversarial attacks is still a challenge. Existin…
Handwriting RecognitionAdversarial AttackFormal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study
Self-interested agents, left unconstrained, tend toward defection in repeated social dilemmas, causing cooperative gains from trade to collapse. This paper investigates what formal mechanisms, layered on top of unrestric…
Adversarial RobustnessAdversarial AttackAirflowAttack: Thermal-Airflow Adversarial Perturbations against Infrared Remote-Sensing Vision-Language Models
Vision-language models (VLMs) are increasingly deployed on infrared (IR) remote sensing imagery in security-critical settings, yet their adversarial robustness remains unexamined. We present AirflowAttack, to our knowled…
Adversarial RobustnessAdversarial AttackBinary Iterative Method for Non-targeted Adversarial Attack
Adversarial attacks guide and provide additional training and test data for both adversarial training and adversarial robustness validation, and expose the 'piecewise linearity' of deep learning based models. Since adver…
Adversarial RobustnessAdversarial AttackDefending from GeoLocalization through Adversarial Road Trips
Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large, geotagged database. The success of deep learning based approaches ha…
Adversarial AttackA Classifier-Agnostic Zero-Shot Adversarial Attack Detection via CLIP
Adversarial attacks pose a challenge to the reliability of deep learning models, motivating effective detection methods. Existing techniques often rely on attack-specific assumptions, access to adversarial samples, or kn…
Adversarial AttackPLAA: Packet-level Adversarial Attacks in Network Traffic Detection
Deep neural networks (DNNs) are widely applied in Network-based Intrusion Detection System (NIDS) due to their high accuracy. However, DNNs are highly susceptible to adversarial attacks, which generate malicious traffic …
Intrusion DetectionAdversarial AttackSingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
Vision-language models (VLMs) are increasingly deployed in consumer, medical, financial, and enterprise applications. This broad deployment expands the safety surface: risks can arise from multimodal question answering, …
Reinforcement LearningAdversarial AttackQuestion AnsweringOne Year Later...The Harms Persist, But So Do We!
General-purpose large language models (LLMs) are increasingly used for mental health-related conversations, yet safety guardrails remain inadequate and inconsistent across clinical conditions. This study evaluates eight …
Adversarial AttackQuality-Preserving Imperceptible Adversarial Attack on Skeleton-based Human Action Recognition
Adversarial attacks on skeletal human action recognition have received significant attention. However, existing methods typically introduce noise-like perturbations that degrade motion quality post-attack, and thereby ar…
Adversarial AttackAction RecognitionAdversarial Attacks on Learned Policies for Surgical Robotic Tasks
Learning-based policies are being considered to augment the dexterity of human surgeons in robot-assisted surgery. Can the end-to-end mapping from visual observations to robot actions be vulnerable to adversarial attacks…
Adversarial AttackAdv-TGD: Adversarial Text-Guided Diffusion for Face Recognition Impersonation Attacks
The widespread adoption of face recognition (FR) technologies raises serious privacy concerns, as facial data can be exploited without consent. To address this challenge, we propose Adv-TGD, a generative adversarial atta…
Adversarial AttackFace Recognition