From Attack to Defense: Insights into Deep Learning Security Measures in Black-Box Settings
Fuente:
arXiv
Saved in:
| Main Authors: | Juraev, Firuz, Abuhamad, Mohammed, Chan-Tin, Eric, Thiruvathukal, George K., Abuhmed, Tamer |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Impact of Architectural Modifications on Deep Learning Adversarial Robustness
by: Juraev, Firuz, et al.
Published: (2024)
by: Juraev, Firuz, et al.
Published: (2024)
Attacking interpretable NLP systems
by: Abdukhamidov, Eldor, et al.
Published: (2025)
by: Abdukhamidov, Eldor, et al.
Published: (2025)
Breaking the Illusion of Security via Interpretation: Interpretable Vision Transformer Systems under Attack
by: Abdukhamidov, Eldor, et al.
Published: (2025)
by: Abdukhamidov, Eldor, et al.
Published: (2025)
A Deep Dive into Function Inlining and its Security Implications for ML-based Binary Analysis
by: Abusabha, Omar, et al.
Published: (2025)
by: Abusabha, Omar, et al.
Published: (2025)
Enhanced MLLM Black-Box Jailbreaking Attacks and Defenses
by: Zhong, Xingwei, et al.
Published: (2025)
by: Zhong, Xingwei, et al.
Published: (2025)
ICL-EVADER: Zero-Query Black-Box Evasion Attacks on In-Context Learning and Their Defenses
by: He, Ningyuan, et al.
Published: (2026)
by: He, Ningyuan, et al.
Published: (2026)
Can Drift-Adaptive Malware Detectors Be Made Robust? Attacks and Defenses Under White-Box and Black-Box Threats
by: Li, Adrian Shuai, et al.
Published: (2026)
by: Li, Adrian Shuai, et al.
Published: (2026)
Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
by: Zhang, Yiwei, et al.
Published: (2024)
by: Zhang, Yiwei, et al.
Published: (2024)
A Signal Injection Attack Against Zero Involvement Pairing and Authentication for the Internet of Things
by: Ahlgren, Isaac, et al.
Published: (2024)
by: Ahlgren, Isaac, et al.
Published: (2024)
System Password Security: Attack and Defense Mechanisms
by: Shi, Chaofang, et al.
Published: (2025)
by: Shi, Chaofang, et al.
Published: (2025)
Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning
by: Domico, Kyle, et al.
Published: (2025)
by: Domico, Kyle, et al.
Published: (2025)
Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
by: Hong, Hanbin, et al.
Published: (2023)
by: Hong, Hanbin, et al.
Published: (2023)
BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
by: Li, Ye, et al.
Published: (2025)
by: Li, Ye, et al.
Published: (2025)
Behavior-Aware and Generalizable Defense Against Black-Box Adversarial Attacks for ML-Based IDS
by: Ennaji, Sabrine, et al.
Published: (2025)
by: Ennaji, Sabrine, et al.
Published: (2025)
Investigating Privacy Attacks in the Gray-Box Setting to Enhance Collaborative Learning Schemes
by: Mazzone, Federico, et al.
Published: (2024)
by: Mazzone, Federico, et al.
Published: (2024)
Smart Contract Security Beyond Detection
by: Abdelaziz, Tamer
Published: (2026)
by: Abdelaziz, Tamer
Published: (2026)
Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey
by: Yang, Wencheng, et al.
Published: (2025)
by: Yang, Wencheng, et al.
Published: (2025)
EvoDefense: Co-Evolving Black-Box Defense with Large Language Models
by: Li, Yu, et al.
Published: (2026)
by: Li, Yu, et al.
Published: (2026)
Learning from the Good Ones: Risk Profiling-Based Defenses Against Evasion Attacks on DNNs
by: Elnawawy, Mohammed, et al.
Published: (2025)
by: Elnawawy, Mohammed, et al.
Published: (2025)
AntiFLipper: A Secure and Efficient Defense Against Label-Flipping Attacks in Federated Learning
by: Rahman, Aashnan, et al.
Published: (2025)
by: Rahman, Aashnan, et al.
Published: (2025)
FlexLLM: Exploring LLM Customization for Moving Target Defense on Black-Box LLMs Against Jailbreak Attacks
by: Chen, Bocheng, et al.
Published: (2024)
by: Chen, Bocheng, et al.
Published: (2024)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
by: Paracha, Anum, et al.
Published: (2025)
by: Paracha, Anum, et al.
Published: (2025)
Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
by: Shi, Lijia, et al.
Published: (2024)
by: Shi, Lijia, et al.
Published: (2024)
Black-Box Privacy Attacks on Shared Representations in Multitask Learning
by: Abascal, John, et al.
Published: (2025)
by: Abascal, John, et al.
Published: (2025)
Data-free Defense of Black Box Models Against Adversarial Attacks
by: Nayak, Gaurav Kumar, et al.
Published: (2022)
by: Nayak, Gaurav Kumar, et al.
Published: (2022)
FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
by: Han, Shanshan, et al.
Published: (2023)
by: Han, Shanshan, et al.
Published: (2023)
SpecMon: Modular Black-Box Runtime Monitoring of Security Protocols
by: Morio, Kevin, et al.
Published: (2024)
by: Morio, Kevin, et al.
Published: (2024)
Detection and Defense Against Prominent Attacks on Preconditioned LLM-Integrated Virtual Assistants
by: Chan, Chun Fai, et al.
Published: (2024)
by: Chan, Chun Fai, et al.
Published: (2024)
Federated Learning: Attacks, Defenses, Opportunities, and Challenges
by: Shirvani, Ghazaleh, et al.
Published: (2024)
by: Shirvani, Ghazaleh, et al.
Published: (2024)
Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)
by: Yichao, Wu, et al.
Published: (2025)
Black-Box Guardrail Reverse-engineering Attack
by: Yao, Hongwei, et al.
Published: (2025)
by: Yao, Hongwei, et al.
Published: (2025)
PolyJailbreak: Cross-Modal Jailbreaking Attacks on Black-Box Multimodal LLMs
by: Wang, Xinkai, et al.
Published: (2025)
by: Wang, Xinkai, et al.
Published: (2025)
"Someone Hid It": Query-Agnostic Black-Box Attacks on LLM-Based Retrieval
by: Li, Jiate, et al.
Published: (2026)
by: Li, Jiate, et al.
Published: (2026)
Operationalizing Research Software for Supply Chain Security
by: Kalu, Kelechi G., et al.
Published: (2026)
by: Kalu, Kelechi G., et al.
Published: (2026)
Deep Learning Model Security: Threats and Defenses
by: Wang, Tianyang, et al.
Published: (2024)
by: Wang, Tianyang, et al.
Published: (2024)
Adversarial Machine Learning: Attacks, Defenses, and Open Challenges
by: Jha, Pranav K
Published: (2025)
by: Jha, Pranav K
Published: (2025)
Black-Box Skill Stealing Attack from Proprietary LLM Agents: An Empirical Study
by: Wang, Zihan, et al.
Published: (2026)
by: Wang, Zihan, et al.
Published: (2026)
Discovering New Shadow Patterns for Black-Box Attacks on Lane Detection of Autonomous Vehicles
by: MohajerAnsari, Pedram, et al.
Published: (2024)
by: MohajerAnsari, Pedram, et al.
Published: (2024)
Cyber-Physical Security Vulnerabilities Identification and Classification in Smart Manufacturing -- A Defense-in-Depth Driven Framework and Taxonomy
by: Rahman, Md Habibor, et al.
Published: (2024)
by: Rahman, Md Habibor, et al.
Published: (2024)
Distributional Black-Box Model Inversion Attack with Multi-Agent Reinforcement Learning
by: Bao, Huan, et al.
Published: (2024)
by: Bao, Huan, et al.
Published: (2024)
Similar Items
-
Impact of Architectural Modifications on Deep Learning Adversarial Robustness
by: Juraev, Firuz, et al.
Published: (2024) -
Attacking interpretable NLP systems
by: Abdukhamidov, Eldor, et al.
Published: (2025) -
Breaking the Illusion of Security via Interpretation: Interpretable Vision Transformer Systems under Attack
by: Abdukhamidov, Eldor, et al.
Published: (2025) -
A Deep Dive into Function Inlining and its Security Implications for ML-based Binary Analysis
by: Abusabha, Omar, et al.
Published: (2025) -
Enhanced MLLM Black-Box Jailbreaking Attacks and Defenses
by: Zhong, Xingwei, et al.
Published: (2025)