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Adversarial AI Testcases for Maritime Autonomous Systems

https://doi.org/10.5772/acrt.15
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-00470-5_13openalex-snapshot
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_23openalex-snapshot
Towards Robust Neural Networks via Random Self-ensemble
inferredcites →https://doi.org/10.1007/978-3-030-58574-7_41openalex-snapshot
PatchAttack: A Black-Box Texture-Based Attack with Reinforcement Learning
inferredcites →https://doi.org/10.1016/j.cose.2019.04.014openalex-snapshot
POBA-GA: Perturbation optimized black-box adversarial attacks via genetic algorithm
inferredcites →https://doi.org/10.1016/j.cose.2022.103006openalex-snapshot
The Threat of Offensive AI to Organizations
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1016/j.neucom.2012.09.019openalex-snapshot
Robot path planning in uncertain environment using multi-objective particle swarm optimization
inferredcites →https://doi.org/10.1016/j.oceaneng.2017.07.040openalex-snapshot
A study on path optimization method of an unmanned surface vehicle under environmental loads using genetic algorithm
inferredcites →https://doi.org/10.1016/j.oceaneng.2020.107188openalex-snapshot
A framework to identify factors influencing navigational risk for Maritime Autonomous Surface Ships
inferredcites →https://doi.org/10.1016/j.rtbm.2017.06.002openalex-snapshot
Analyzing the economic benefit of unmanned autonomous ships: An exploratory cost-comparison between an autonomous and a conventional bulk carrier
inferredcites →https://doi.org/10.1057/s41278-022-00216-yopenalex-snapshot
Creating value through autonomous shipping: an ecosystem perspective
inferredcites →https://doi.org/10.1080/16258312.2019.1631714openalex-snapshot
Autonomous ships: a review, innovative applications and future maritime business models
inferredcites →https://doi.org/10.1080/25725084.2021.1982637openalex-snapshot
Towards utilizing autonomous ships: A viable advance in industry 4.0
inferredcites →https://doi.org/10.1098/rsif.2009.0495openalex-snapshot
The complex network of global cargo ship movements
inferredcites →https://doi.org/10.1109/access.2018.2807385openalex-snapshot
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
inferredcites →https://doi.org/10.1109/access.2020.3044040openalex-snapshot
A Survey of Technologies for Unmanned Merchant Ships
inferredcites →https://doi.org/10.1109/access.2021.3054879openalex-snapshot
Zero-Centered Fixed-Point Quantization With Iterative Retraining for Deep Convolutional Neural Network-Based Object Detectors
inferredcites →https://doi.org/10.1109/cvpr.2016.282openalex-snapshot
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00191openalex-snapshot
Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser
inferredcites →https://doi.org/10.1109/cvpr.2019.00509openalex-snapshot
Knockoff Nets: Stealing Functionality of Black-Box Models
inferredcites →https://doi.org/10.1109/cvpr.2019.00624openalex-snapshot
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00582openalex-snapshot
On the Detection of Digital Face Manipulation
inferredcites →https://doi.org/10.1109/eurosp.2016.36openalex-snapshot
The Limitations of Deep Learning in Adversarial Settings
inferredcites →https://doi.org/10.1109/eurosp.2019.00044openalex-snapshot
PRADA: Protecting Against DNN Model Stealing Attacks
inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9534016openalex-snapshot
ADVERSARIALuscator: An Adversarial-DRL based Obfuscator and Metamorphic Malware Swarm Generator
inferredcites →https://doi.org/10.1109/iv55152.2023.10186608openalex-snapshot
Adversarial Detection: Attacking Object Detection in Real Time
inferredcites →https://doi.org/10.1109/mspec.2020.8946308openalex-snapshot
Bon voyage for the autonomous ship Mayflower
inferredcites →https://doi.org/10.1109/sp.2016.41openalex-snapshot
Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks
inferredcites →https://doi.org/10.1109/sp.2018.00038openalex-snapshot
Stealing Hyperparameters in Machine Learning
inferredcites →https://doi.org/10.1109/sp.2018.00057openalex-snapshot
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
inferredcites →https://doi.org/10.1109/spw.2018.00020openalex-snapshot
Adversarial Deep Learning for Robust Detection of Binary Encoded Malware
inferredcites →https://doi.org/10.1109/tevc.2019.2890858openalex-snapshot
One Pixel Attack for Fooling Deep Neural Networks
inferredcites →https://doi.org/10.1109/tifs.2020.3003571openalex-snapshot
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection
inferredcites →https://doi.org/10.1109/tits.6979openalex-snapshot
IEEE Transactions on Intelligent Transportation Systems
inferredcites →https://doi.org/10.1109/wacv45572.2020.9093310openalex-snapshot
Adversarial Defense based on Structure-to-Signal Autoencoders
inferredcites →https://doi.org/10.1145/1128817.1128824openalex-snapshot
Can machine learning be secure?
inferredcites →https://doi.org/10.1145/2783258.2788613openalex-snapshot
Intelligible Models for HealthCare
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-snapshot
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
inferredcites →https://doi.org/10.1145/3133956.3134057openalex-snapshot
MagNet
inferredcites →https://doi.org/10.1145/3144592.3144598openalex-snapshot
Why we should have seen that coming
inferredcites →https://doi.org/10.1145/3332184openalex-snapshot
Towards Adversarial Malware Detection
inferredcites →https://doi.org/10.1145/3439723openalex-snapshot
Generative Adversarial Networks in Computer Vision
inferredcites →https://doi.org/10.1145/3484491openalex-snapshot
Arms Race in Adversarial Malware Detection: A Survey
inferredcites →https://doi.org/10.1155/2021/4907754openalex-snapshot
A Survey on Adversarial Attack in the Age of Artificial Intelligence
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-demos.16openalex-snapshot
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
inferredcites →https://doi.org/10.18653/v1/d19-1221openalex-snapshot
Universal Adversarial Triggers for Attacking and Analyzing NLP
inferredcites →https://doi.org/10.23919/eusipco.2018.8553214openalex-snapshot
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables
inferredcites →https://doi.org/10.24868/icmet.oman.2019.028openalex-snapshot
Autonomous Ship Navigation Methods: A Review
inferredcites →https://doi.org/10.24963/ijcai.2018/543openalex-snapshot
Generating Adversarial Examples with Adversarial Networks
inferredcites →https://doi.org/10.3390/app11104553openalex-snapshot
Costs and Benefits of Autonomous Shipping—A Literature Review
inferredcites →https://doi.org/10.3390/app9050909openalex-snapshot
Review of Artificial Intelligence Adversarial Attack and Defense Technologies
inferredcites →https://doi.org/10.3390/electronics11081283openalex-snapshot
Adversarial Attack and Defense: A Survey
inferredcites →https://doi.org/10.3390/jmse8010041openalex-snapshot
The Ocean-Going Autonomous Ship—Challenges and Threats
inferredcites →https://doi.org/10.3940/rina.hf.2014.12openalex-snapshot
Situation Awareness in Remote Control Centres for Unmanned Ships
inferredcites →https://doi.org/10.4028/www.scientific.net/amm.568-570.785openalex-snapshot
Global Path Planning Method for USV System Based on Improved Ant Colony Algorithm

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-57452-8_9openalex-snapshot
On the Cybersecurity of Logistics in the Age of Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/978-3-031-69437-0_9openalex-snapshot
MASS Cybersecurity
inferred← citeshttps://doi.org/10.1007/978-3-031-99342-8_1openalex-snapshot
Artificial Intelligence-Driven Cyberattacks: A General Approach to Understanding Adversarial and Offensive AI
inferred← citeshttps://doi.org/10.1007/978-3-032-02102-1_22openalex-snapshot
Operational Safety and Cybersecurity in Autonomous Vessel Mooring and Cargo Handling: A Cascading Effects Approach
inferred← citeshttps://doi.org/10.1007/978-3-032-18132-9_5openalex-snapshot
A Machine Learning Framework for Autonomous Bilge Water Management
inferred← citeshttps://doi.org/10.1007/s00773-026-01123-0openalex-snapshot
A HFACS-BN model-based investigation of human factors in MASS accidents
inferred← citeshttps://doi.org/10.1007/s13437-025-00362-zopenalex-snapshot
Visualisation of cyber vulnerabilities in maritime human-autonomy teaming technology
inferred← citeshttps://doi.org/10.1016/b978-0-443-13223-0.00104-1openalex-snapshot
Future Trends in Maritime Cybersecurity
inferred← citeshttps://doi.org/10.1080/08839514.2024.2395750openalex-snapshot
A Red Teaming Framework for Securing AI in Maritime Autonomous Systems
inferred← citeshttps://doi.org/10.1080/20464177.2023.2298521openalex-snapshot
Adversarial waypoint injection attacks on Maritime Autonomous Surface Ships (MASS) collision avoidance systems
inferred← citeshttps://doi.org/10.1080/20464177.2024.2428022openalex-snapshot
The survivability of autonomous vessels from cyber-attacks
inferred← citeshttps://doi.org/10.1109/access.2025.3589512openalex-snapshot
Investigating the Transferability of TOG Adversarial Attacks in YOLO Models in the Maritime Domain
inferred← citeshttps://doi.org/10.1109/csr64739.2025.11130142openalex-snapshot
PASTA Threat Modeling for Cyber Resilience and COLREG Compliance in Autonomous Ship Systems
inferred← citeshttps://doi.org/10.1109/icomet69771.2026.11592032openalex-snapshot
Adversarial Robustness Analysis of Object Detection Model under Black-Box Patch Attacks
inferred← citeshttps://doi.org/10.1109/icpads67057.2025.11323042openalex-snapshot
FCA-MARS: Full-Coverage Adversarial Camouflage for Few-Shot Ships with Multi-Angle Attack Robustness
inferred← citeshttps://doi.org/10.1109/lcn60385.2024.10639747openalex-snapshot
AIS Spoofing: A Tutorial for Researchers
inferred← citeshttps://doi.org/10.1109/milcom58377.2023.10356321openalex-snapshot
Autonomous Cyber Defense Agents for NATO: Threat Analysis, Design, and Experimentation
inferred← citeshttps://doi.org/10.1109/satc65530.2025.11137247openalex-snapshot
Artificial Intelligence’s Impact on the Banking Industry: Enhancing Security and Efficiency
inferred← citeshttps://doi.org/10.1177/15485129241283056openalex-snapshot
Unmanned surface vehicles for naval warfare and maritime security
inferred← citeshttps://doi.org/10.12716/1001.19.02.35openalex-snapshot
Developing Human-Autonomy Teaming Strategies for Maritime Cyber Security Resilience in Uncrewed Autonomous and Remote Surface Vessel Operations
inferred← citeshttps://doi.org/10.12716/1001.20.01.25openalex-snapshot
SAFE-MASS Sociotechnical Array Framework for Evolving Maritime Autonomous Surface Ships
inferred← citeshttps://doi.org/10.14569/ijacsa.2025.01604104openalex-snapshot
Adversarial Attack on Autonomous Ships Navigation Using K-Means Clustering and CAM
inferred← citeshttps://doi.org/10.14569/ijacsa.2025.01604106openalex-snapshot
A Robust Defense Mechanism Against Adversarial Attacks in Maritime Autonomous Ship Using GMVAE+RL
inferred← citeshttps://doi.org/10.2514/6.2026-0431openalex-snapshot
Sensor Data Fusion for Adversarial Patch Attack Mitigation
inferred← citeshttps://doi.org/10.3390/app15031666openalex-snapshot
Leveraging Large Language Models for Enhancing Safety in Maritime Operations
inferred← citeshttps://doi.org/10.3390/app15094986openalex-snapshot
Enhancing Safety in Autonomous Maritime Transportation Systems with Real-Time AI Agents
inferred← citeshttps://doi.org/10.3390/jmse11061179openalex-snapshot
Vulnerability of Clean-Label Poisoning Attack for Object Detection in Maritime Autonomous Surface Ships
inferred← citeshttps://doi.org/10.4018/979-8-3693-0774-8.ch010openalex-snapshot
Data Security and Privacy Concerns in Drone Operations
inferred← citeshttps://doi.org/10.59247/csol.v2i3.128openalex-snapshot
Potential Applications and Limitations of Artificial Intelligence in Remote Sensing Data Interpretation: A Case Study
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