Cover Image

INTARG: Informed Real-Time Adversarial Attack Generation for Time-Series Regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tokgoz, Gamze Kirman, Gungor, Onat, Rosing, Tajana, Aksanli, Baris
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ReLATE: Resilient Learner Selection for Multivariate Time-Series Classification Against Adversarial Attacks
by: Kocal, Cagla Ipek, et al.
Published: (2025)

ReLATE+: Unified Framework for Adversarial Attack Detection, Classification, and Resilient Model Selection in Time-Series Classification
by: Kocal, Cagla Ipek, et al.
Published: (2025)

CND-IDS: Continual Novelty Detection for Intrusion Detection Systems
by: Fuhrman, Sean, et al.
Published: (2025)

CyberMaskQA: A Privacy-Aware Benchmark for Evaluating Large Language Models in Cybersecurity Question Answering
by: Gaddi, Matilda, et al.
Published: (2026)

CAN-QA: A Question-Answering Benchmark for Reasoning over In-Vehicle CAN Traffic
by: Chen, Jing, et al.
Published: (2026)

SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection
by: Li, Elvin, et al.
Published: (2025)

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
by: Chen, Jing, et al.
Published: (2025)

ACORN-IDS: Adaptive Continual Novelty Detection for Intrusion Detection Systems
by: Fuhrman, Sean, et al.
Published: (2026)

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks
by: Chen, Jing, et al.
Published: (2025)

AQUA-LLM: Evaluating Accuracy, Quantization, and Adversarial Robustness Trade-offs in LLMs for Cybersecurity Question Answering
by: Gungor, Onat, et al.
Published: (2025)

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
by: Li, Elvin, et al.
Published: (2025)

EAGER: Edge-Aligned LLM Defense for Robust, Efficient, and Accurate Cybersecurity Question Answering
by: Gungor, Onat, et al.
Published: (2025)

LIGHT-HIDS: A Lightweight and Effective Machine Learning-Based Framework for Robust Host Intrusion Detection
by: Gungor, Onat, et al.
Published: (2025)

TS-OOD: Evaluating Time-Series Out-of-Distribution Detection and Prospective Directions for Progress
by: Gungor, Onat, et al.
Published: (2025)

Correlation Analysis of Adversarial Attack in Time Series Classification
by: Li, Zhengyang, et al.
Published: (2024)

Test-time Adversarial Defense with Opposite Adversarial Path and High Attack Time Cost
by: Yeh, Cheng-Han, et al.
Published: (2024)

Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment
by: Fink, Xaver, et al.
Published: (2026)

Real-World Adversarial Attacks on RF-Based Drone Detectors
by: Gazit, Omer, et al.
Published: (2025)

VFLGAN-TS: Vertical Federated Learning-based Generative Adversarial Networks for Publication of Vertically Partitioned Time-Series Data
by: Yuan, Xun, et al.
Published: (2024)

Generalization Properties of Adversarial Training for $\ell_0$-Bounded Adversarial Attacks
by: Delgosha, Payam, et al.
Published: (2024)

Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
by: Jin, Zhibo, et al.
Published: (2024)

Keep the Lights On, Keep the Lengths in Check: Plug-In Adversarial Detection for Time-Series LLMs in Energy Forecasting
by: Ma, Hua, et al.
Published: (2025)

BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
by: Lin, Xiao, et al.
Published: (2024)

Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
by: Shahgir, Haz Sameen, et al.
Published: (2023)

Optimal Defenses Against Gradient Reconstruction Attacks
by: Chen, Yuxiao, et al.
Published: (2024)

Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
by: Huang, Yuanmin, et al.
Published: (2025)

Trading Inference-Time Compute for Adversarial Robustness
by: Zaremba, Wojciech, et al.
Published: (2025)

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

Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes
by: Hamidi, Shayan Mohajer, et al.
Published: (2024)

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

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

Adversarial Contrastive Learning for LLM Quantization Attacks
by: Song, Dinghong, et al.
Published: (2026)

Temporal Analysis of Adversarial Attacks in Federated Learning
by: Mapakshi, Rohit, et al.
Published: (2025)

Efficient Adversarial Training in LLMs with Continuous Attacks
by: Xhonneux, Sophie, et al.
Published: (2024)

TrojanTime: Backdoor Attacks on Time Series Classification
by: Dong, Chang, et al.
Published: (2025)

Adversarial Attacks on Locally Private Graph Neural Networks
by: Varun, Matta, et al.
Published: (2026)

Evaluating Adversarial Attacks on Federated Learning for Temperature Forecasting
by: Chichifoi, Karina, et al.
Published: (2025)

Adversarial Inception Backdoor Attacks against Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2024)

The Relationship Between Network Similarity and Transferability of Adversarial Attacks
by: Klause, Gerrit, et al.
Published: (2025)

Differentiable Adversarial Attacks for Marked Temporal Point Processes
by: Chakraborty, Pritish, et al.
Published: (2025)