Copertina

A Survey on Adversarial Machine Learning for Code Data: Realistic Threats, Countermeasures, and Interpretations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Yulong, Fan, Haoran, Lin, Chenhao, Li, Qian, Zhao, Zhengyu, Shen, Chao, Guan, Xiaohong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Privacy on the Fly: A Predictive Adversarial Transformation Network for Mobile Sensor Data
di: Song, Tianle, et al.
Pubblicazione: (2025)

Systematic Categorization, Construction and Evaluation of New Attacks against Multi-modal Mobile GUI Agents
di: Yang, Yulong, et al.
Pubblicazione: (2024)

Survey of Privacy Threats and Countermeasures in Federated Learning
di: Hayashitani, Masahiro, et al.
Pubblicazione: (2024)

Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples
di: Han, Sicong, et al.
Pubblicazione: (2025)

Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
di: Zheng, Junhao, et al.
Pubblicazione: (2024)

LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection
di: Tian, Jiwei, et al.
Pubblicazione: (2024)

Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement
di: Ren, Yuchen, et al.
Pubblicazione: (2025)

Emerging Threats and Countermeasures in Neuromorphic Systems: A Survey
di: Sorrentino, Pablo, et al.
Pubblicazione: (2026)

Taxonomy for Cybersecurity Threat Attributes and Countermeasures in Smart Manufacturing Systems
di: Rahman, Md Habibor, et al.
Pubblicazione: (2023)

Revisiting Training-Inference Trigger Intensity in Backdoor Attacks
di: Lin, Chenhao, et al.
Pubblicazione: (2025)

Modern DDoS Threats and Countermeasures: Insights into Emerging Attacks and Detection Strategies
di: Wang, Jincheng, et al.
Pubblicazione: (2025)

Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path
di: Ren, Yuchen, et al.
Pubblicazione: (2024)

Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights
di: Zheng, Junhao, et al.
Pubblicazione: (2025)

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

Privacy Threats and Countermeasures in Federated Learning for Internet of Things: A Systematic Review
di: ElZemity, Adel, et al.
Pubblicazione: (2024)

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
di: Ghosh, Archisman, et al.
Pubblicazione: (2025)

Concerned with Data Contamination? Assessing Countermeasures in Code Language Model
di: Cao, Jialun, et al.
Pubblicazione: (2024)

Adversarial Machine Learning Threats to Spacecraft
di: Thummala, Rajiv, et al.
Pubblicazione: (2024)

ExplainableGuard: Interpretable Adversarial Defense for Large Language Models Using Chain-of-Thought Reasoning
di: Guan, Shaowei, et al.
Pubblicazione: (2025)

A Review of the Duality of Adversarial Learning in Network Intrusion: Attacks and Countermeasures
di: Saini, Shalini, et al.
Pubblicazione: (2024)

Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Models
di: Liu, Yugeng, et al.
Pubblicazione: (2023)

Generalizable Targeted Data Poisoning against Varying Physical Objects
di: Chen, Zhizhen, et al.
Pubblicazione: (2024)

Application-Specific Power Side-Channel Attacks and Countermeasures: A Survey
di: Sanjaya, Sahan, et al.
Pubblicazione: (2025)

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures
di: Kong, Dezhang, et al.
Pubblicazione: (2025)

FRAME : Comprehensive Risk Assessment Framework for Adversarial Machine Learning Threats
di: Shapira, Avishag, et al.
Pubblicazione: (2025)

A Survey of AI-Related Cyber Security Risks and Countermeasures in Mobility-as-a-Service
di: Chu, Kai-Fung, et al.
Pubblicazione: (2024)

Enterprise Security Incident Analysis and Countermeasures Based on the T-Mobile Data Breach
di: Cui, Zhuohan, et al.
Pubblicazione: (2025)

SoK: A Systems Perspective on Compound AI Threats and Countermeasures
di: Banerjee, Sarbartha, et al.
Pubblicazione: (2024)

Practical Spoofing Attacks on Galileo Open Service Navigation Message Authentication
di: Wang, Haiyang, et al.
Pubblicazione: (2025)

Joint Universal Adversarial Perturbations with Interpretations
di: Ning, Liang-bo, et al.
Pubblicazione: (2024)

Logit Poisoning Attack in Distillation-based Federated Learning and its Countermeasures
di: Yu, Yonghao, et al.
Pubblicazione: (2024)

Threats, Attacks, and Defenses in Machine Unlearning: A Survey
di: Liu, Ziyao, et al.
Pubblicazione: (2024)

Selection-Based Vulnerabilities: Clean-Label Backdoor Attacks in Active Learning
di: Zhi, Yuhan, et al.
Pubblicazione: (2025)

An LLM Agent-based Framework for Whaling Countermeasures
di: Miyamoto, Daisuke, et al.
Pubblicazione: (2026)

TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models
di: Zhang, Chaoshuo, et al.
Pubblicazione: (2026)

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

Evaluating LLM-based Personal Information Extraction and Countermeasures
di: Liu, Yupei, et al.
Pubblicazione: (2024)

Differential Area Analysis for Ransomware: Attacks, Countermeasures, and Limitations
di: Venturini, Marco, et al.
Pubblicazione: (2023)

Privacy-Preserving Federated Learning Scheme with Mitigating Model Poisoning Attacks: Vulnerabilities and Countermeasures
di: Wu, Jiahui, et al.
Pubblicazione: (2025)