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@article{jabary2024seeing,
title={Seeing Through the Mask: Rethinking Adversarial Examples for CAPTCHAs},
author={Jabary, Yahya and Plesner, Andreas and Kuzhagaliyev, Turlan and Wattenhofer, Roger},
journal={arXiv preprint arXiv:2409.05558},
year={2024}
}
@inproceedings{plesner2024breaking,
title={Breaking reCAPTCHAv2},
author={Plesner, Andreas and Vontobel, Tobias and Wattenhofer, Roger},
booktitle={48th IEEE International Conference on Computers, Software, and Applications (COMPSAC 2024)},
year={2024},
organization={IEEE}
}
@inproceedings {218395,
author = {James Mickens},
title = {Q: Why Do Keynote Speakers Keep Suggesting That Improving Security Is Possible? A: Because Keynote Speakers Make Bad Life Decisions and Are Poor Role Models},
booktitle = {27th USENIX Security Symposium (USENIX Security 18)},
year = {2018},
isbn = {978-1-939133-04-5},
address = {Baltimore, MD},
url = {https://www.usenix.org/conference/usenixsecurity18/presentation/mickens},
publisher = {USENIX Association},
month = aug
}
%
% computational geometry stuff
%
@article{hornik1989multilayer,
title={Multilayer feedforward networks are universal approximators},
author={Hornik, Kurt and Stinchcombe, Maxwell and White, Halbert},
journal={Neural networks},
volume={2},
number={5},
pages={359--366},
year={1989},
publisher={Elsevier}
}
@article{mentzer2020high,
title={High-Fidelity Generative Image Compression},
author={Mentzer, Fabian and Toderici, George D and Tschannen, Michael and Agustsson, Eirikur},
journal={Advances in Neural Information Processing Systems},
volume={33},
year={2020}
}
@article{seidel1998nature,
title={The nature and meaning of perturbations in geometric computing},
author={Seidel, Raimund},
journal={Discrete \& Computational Geometry},
volume={19},
pages={1--17},
year={1998},
publisher={Springer}
}
@book{de2000computational,
title={Computational geometry: algorithms and applications},
author={De Berg, Mark},
year={2000},
publisher={Springer Science \& Business Media}
}
@article{edelsbrunner2002topological,
title={Topological persistence and simplification},
author={Edelsbrunner and Letscher and Zomorodian},
journal={Discrete \& computational geometry},
volume={28},
pages={511--533},
year={2002},
publisher={Springer}
}
@inproceedings{edelsbrunner2001sink,
title={Sink-insertion for mesh improvement},
author={Edelsbrunner, Herbert and Guoy, Damrong},
booktitle={Proceedings of the seventeenth annual symposium on Computational geometry},
pages={115--123},
year={2001}
}
@article{edelsbrunner1990simulation,
title={Simulation of simplicity: a technique to cope with degenerate cases in geometric algorithms},
author={Edelsbrunner, Herbert and M{\"u}cke, Ernst Peter},
journal={ACM Transactions on Graphics (tog)},
volume={9},
number={1},
pages={66--104},
year={1990},
publisher={ACM New York, NY, USA}
}
@article{levy2016robustness,
title={Robustness and efficiency of geometric programs: The Predicate Construction Kit (PCK)},
author={L{\'e}vy, Bruno},
journal={Computer-Aided Design},
volume={72},
pages={3--12},
year={2016},
publisher={Elsevier}
}
@article{franklin2022implementing,
title={Implementing Simulation of Simplicity for geometric degeneracies},
author={Franklin, W Randolph and de Magalh{\~a}es, Salles Viana Gomes},
journal={arXiv preprint arXiv:2212.08226},
year={2022}
}
@article{schorn1993axiomatic,
title={An axiomatic approach to robust geometric programs},
author={Schorn, Peter},
journal={Journal of symbolic computation},
volume={16},
number={2},
pages={155--165},
year={1993},
publisher={Elsevier}
}
%
% motivation
%
@misc{vulnhuntr,
title = {vulnhuntr},
author = {ProtectAI},
year = {2024},
publisher = {GitHub},
howpublished = {\url{https://github.com/protectai/vulnhuntr}},
note = {GitHub repository},
commit = {}
}
@online{carlini2019adversarial,
author = {Carlini, Nicholas},
title = {A Complete List of All Adversarial Example Papers},
year = {2019},
month = {6},
day = {15},
url = {https://nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html}
}
@article{keysers2019measuring,
title={Measuring compositional generalization: A comprehensive method on realistic data},
author={Keysers, Daniel and Sch{\"a}rli, Nathanael and Scales, Nathan and Buisman, Hylke and Furrer, Daniel and Kashubin, Sergii and Momchev, Nikola and Sinopalnikov, Danila and Stafiniak, Lukasz and Tihon, Tibor and others},
journal={arXiv preprint arXiv:1912.09713},
year={2019}
}
@article{Miller2017ComputerVO,
title={Computer Vision on the Battlefield: Can Machines Distinguish Between Enemy and Civilian in Military Urban Operations?},
author={Ian Miller},
journal={Mechanical Engineering eJournal},
year={2017},
url={https://api.semanticscholar.org/CorpusID:237530499}
}
@online{bigsleep2024,
author = {{Big Sleep Team}},
title = {From Naptime to Big Sleep: Using Large Language Models To Catch Vulnerabilities In Real-World Code},
year = {2024},
month = {10},
organization = {Google Project Zero},
note = {A collaboration between Google Project Zero and Google DeepMind}
}
@article{Ananthaswamy2024,
title={New Theory Suggests Chatbots Can Understand Text},
author={Ananthaswamy, Anil},
journal={Quanta Magazine},
year={2024},
month={January},
day={22},
publisher={Simons Foundation}
}
@article{qiu2024can,
title={Can Large Language Models Understand Symbolic Graphics Programs?},
author={Qiu, Zeju and Liu, Weiyang and Feng, Haiwen and Liu, Zhen and Xiao, Tim Z and Collins, Katherine M and Tenenbaum, Joshua B and Weller, Adrian and Black, Michael J and Sch{\"o}lkopf, Bernhard},
journal={arXiv preprint arXiv:2408.08313},
year={2024}
}
@misc{FLI2023pause,
title = {Pause Giant {AI} Experiments: An Open Letter},
author = {{Future of Life Institute}},
year = {2023},
month = {March},
day = {22},
howpublished = {Future of Life Institute},
note = {Open letter calling for pause in AI development}
}
@article{hendrycks2021unsolved,
title={Unsolved problems in ml safety},
author={Hendrycks, Dan and Carlini, Nicholas and Schulman, John and Steinhardt, Jacob},
journal={arXiv preprint arXiv:2109.13916},
year={2021}
}
@online{80000hours_infosec,
title = {Information security in high-impact areas career review},
author = {80000 Hours},
organization = {80000 Hours},
year = {2024},
url = {https://80000hours.org/career-reviews/information-security/},
urldate = {2024-12-27}
}
@online{80000hours_ai_2024,
author = {80000 Hours},
title = {Preventing an AI-related catastrophe},
year = {2024},
url = {https://80000hours.org/problem-profiles/artificial-intelligence/},
organization = {80000 Hours},
urldate = {2024-12-27}
}
@online{boozallen2023adversarialother,
title = {Booz Allen Hamilton Expands Adversarial AI Capabilities},
author = {MSSPAlert},
year = {2023},
month = {September},
day = {26},
publisher = {MSSPAlert},
keywords = {artificial intelligence, cybersecurity, HiddenLayer, Booz Allen Hamilton}
}
@online{boozallen2023adversarial,
title = {Booz Allen Doubles Down on Adversarial AI Capabilities With New Investment},
organization = {Business Wire},
author = {{Booz Allen Hamilton}},
year = {2023},
month = {9},
day = {26},
location = {McLean, Virginia},
publisher = {Business Wire},
note = {Press Release}
}
@online{huggingface2024security,
title = {Hugging Face partners with Wiz Research to Improve AI Security},
author = {Hugging Face},
year = {2024},
organization = {Hugging Face},
url = {https://huggingface.co/blog/hugging-face-wiz-security-blog},
note = {Blog post discussing security improvements, pickle file security concerns, and partnership with Wiz Research}
}
@article{mitre2024ml,
title = {MITRE, Microsoft, and 11 Other Organizations Take on Machine-Learning Threats},
author = {Eidson, Bill},
journal = {MITRE News and Insights},
organization = {MITRE},
year = {2024},
url = {https://www.mitre.org/news-insights/impact-story/mitre-microsoft-and-11-other-organizations-take-machine-learning-threats},
note = {Impact Story on the Adversarial Machine Learning Threat Matrix initiative},
keywords = {artificial intelligence, machine learning, cybersecurity, threat matrix}
}
@misc{openphil2024adversarial,
title = {Carnegie Mellon University — Research on Adversarial Examples},
author = {{Open Philanthropy}},
year = {2024},
institution = {Open Philanthropy},
note = {Grant of \$343,235 to support research on adversarial examples led by Professor Aditi Raghunathan}
}
@online{roy2020darpa,
author = {Roy-Chowdhury, Amit and Krishnamurthy, Srikanth and Song, Chengyu and Asif, Salman},
title = {{ECE and CSE faculty receive new DARPA grant on adversarial machine learning}},
year = {2020},
month = {7},
day = {29},
organization = {University of California, Riverside},
type = {Web Article},
note = {DARPA Machine Vision Disruption program grant announcement}
}
@online{coursera_adversarial_2024,
author = {{Coursera Editorial Team}},
title = {What Is Adversarial Machine Learning?},
year = {2024},
publisher = {Coursera},
url = {https://www.coursera.org/articles/adversarial-machine-learning},
urldate = {2024-12-09}
}
@article{cai2020robust,
author = {Cai, Kenrick},
title = {Robust Intelligence Raises \$14 Million Series A Led By Sequoia To Build Platform For Testing Machine Learning Applications},
journal = {Forbes},
year = {2020},
month = {October},
day = {21},
publisher = {Forbes Media LLC}
}
@online{robustintelligence2024,
title = {AI Application Security},
author = {{Robust Intelligence}},
year = {2024},
organization = {Robust Intelligence},
url = {https://www.robustintelligence.com/ai-application-security},
urldate = {2024-12-09}
}
@ARTICLE{9154468,
author={Rahman, Abdur and Hossain, M. Shamim and Alrajeh, Nabil A. and Alsolami, Fawaz},
journal={IEEE Internet of Things Journal},
title={Adversarial Examples—Security Threats to COVID-19 Deep Learning Systems in Medical IoT Devices},
year={2021},
volume={8},
number={12},
pages={9603-9610},
keywords={Machine learning;Medical diagnostic imaging;Perturbation methods;Computed tomography;Biological system modeling;Image recognition;Adversarial examples (AEs);COVID-19;deep learning (DL);medical IoT},
doi={10.1109/JIOT.2020.3013710}
}
@article{najafi2024dft,
title={DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studies},
author={Najafi, Mohammad Hossein and Morsali, Mohammad and Vahediahmar, Mohammadmahdi and Shouraki, Saeed Bagheri},
journal={arXiv preprint arXiv:2408.08489},
year={2024}
}
@article{jogani2022analysis,
title={Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification},
author={Jogani, Vinay and Purohit, Joy and Shivhare, Ishaan and Shrawne, Seema C},
journal={arXiv preprint arXiv:2212.10565},
year={2022}
}
@inproceedings{Rudolph2008DevelopingPS,
title={Developing Protective Strategies forCriticalBuilding Infrastructures Potentially Subjected to M alevolentThreats* By},
author={Rudolph and Rudolph V. Matalucci and Jon T. Matalucci},
year={2008},
url={https://api.semanticscholar.org/CorpusID:111438592}
}
@article{Halak2022TowardsAP,
title={Towards Autonomous Physical Security Defenses using Machine Learning},
author={Basel Halak and Christian Hall and Syed Fathir and Nelson Kit and Ruwaydah Raymonde and Michael Gimson and Ahmad Kida and Hugo Vincent},
journal={IEEE Access},
year={2022},
volume={PP},
pages={1-1},
url={https://api.semanticscholar.org/CorpusID:248849785}
}
@article{Ulybyshev2021TrustworthyDA,
title={Trustworthy Data Analysis and Sensor Data Protection in Cyber-Physical Systems},
author={Denis A. Ulybyshev and Ibrahim Yilmaz and Bradley Northern and Vadim Kholodilo and Mike Rogers},
journal={Proceedings of the 2021 ACM Workshop on Secure and Trustworthy Cyber-Physical Systems},
year={2021},
url={https://api.semanticscholar.org/CorpusID:233384629}
}
@article{Chevardin2023AnalysisOA,
title={Analysis of adversarial attacks on the machine learning models of cyberprotection systems.},
author={V. Chevardin and O. Yurchenko and O. V. Zaluzhnyi and Ye. Peleshok},
journal={Communication, informatization and cybersecurity systems and technologies},
year={2023},
url={https://api.semanticscholar.org/CorpusID:266487123}
}
@article{Moradpoor2023TheTO,
title={The Threat of Adversarial Attacks Against Machine Learning-based Anomaly Detection Approach in a Clean Water Treatment System},
author={Naghmeh Moradpoor and Leandros A. Maglaras and Ezra Abah and Andres Robles-Durazno},
journal={2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)},
year={2023},
pages={453-460},
url={https://api.semanticscholar.org/CorpusID:262980912}
}
@article{Tsai2024EffectiveAE,
title={Effective Adversarial Examples Identification of Credit Card Transactions},
author={Min-Yan Tsai and Hsin-Hung Cho and Chia-Mu Yu and Yao-Chung Chang and Han-Chieh Chao},
journal={IEEE Intelligent Systems},
year={2024},
volume={39},
pages={50-59},
url={https://api.semanticscholar.org/CorpusID:268628851}
}
@inproceedings{Agarwal2021BlackBoxAE,
title={Black-Box Adversarial Entry in Finance through Credit Card Fraud Detection},
author={Akshay Agarwal and Nalini K. Ratha},
booktitle={CIKM Workshops},
year={2021},
url={https://api.semanticscholar.org/CorpusID:245540840}
}
@article{Gu2022DeepLT,
title={Deep Learning Techniques in Financial Fraud Detection},
author={Kuangyi Gu},
journal={Proceedings of the 7th International Conference on Cyber Security and Information Engineering},
year={2022},
url={https://api.semanticscholar.org/CorpusID:253120915}
}
@article{Patel2019AdaptiveAV,
title={Adaptive Adversarial Videos on Roadside Billboards: Dynamically Modifying Trajectories of Autonomous Vehicles},
author={Naman Patel and Prashanth Krishnamurthy and Siddharth Garg and Farshad Khorrami},
journal={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year={2019},
pages={5916-5921},
url={https://api.semanticscholar.org/CorpusID:210971572}
}
@article{Ji2021PoltergeistAA,
title={Poltergeist: Acoustic Adversarial Machine Learning against Cameras and Computer Vision},
author={Xiaoyu Ji and Yushi Cheng and Yuepeng Zhang and Kai Wang and Chen Yan and Wenyuan Xu and Kevin Fu},
journal={2021 IEEE Symposium on Security and Privacy (SP)},
year={2021},
pages={160-175},
url={https://api.semanticscholar.org/CorpusID:235601506}
}
@article{Axelrod2017CybersecurityCO,
title={Cybersecurity challenges of systems-of-systems for fully-autonomous road vehicles},
author={C. Warren Axelrod},
journal={2017 13th International Conference and Expo on Emerging Technologies for a Smarter World (CEWIT)},
year={2017},
pages={1-6},
url={https://api.semanticscholar.org/CorpusID:29935654}
}
@article{Chahar2024AdversarialTI,
title={Adversarial Threats in Machine Learning: A Critical Analysis},
author={Suman Chahar and Sonali Gupta and Isha Dhingra and Kuldeep Singh Kaswan},
journal={2024 International Conference on Computational Intelligence and Computing Applications (ICCICA)},
year={2024},
volume={1},
pages={253-258},
url={https://api.semanticscholar.org/CorpusID:271116821}
}
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author={Sadeghi, Koosha and Banerjee, Ayan and Gupta, Sandeep K. S.},
journal={IEEE Transactions on Emerging Topics in Computational Intelligence},
title={A System-Driven Taxonomy of Attacks and Defenses in Adversarial Machine Learning},
year={2020},
volume={4},
number={4},
pages={450-467},
keywords={Taxonomy;Machine learning;Robustness;Security;Observers;Machine learning algorithms;Computational intelligence;Computational intelligence (CI);adversarial machine learning;supervised learning;attack model;defense model},
doi={10.1109/TETCI.2020.2968933}
}
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title={Resilient Machine Learning in Space Systems: Pose Estimation as a Case Study},
author={Anita Khadka and Saurav Sthapit and Gregory Epiphaniou and Carsten Maple},
journal={2022 IEEE Aerospace Conference (AERO)},
year={2022},
pages={1-9},
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}
@inproceedings{yilmaz2021privacy,
title={Privacy protection of grid users data with blockchain and adversarial machine learning},
author={Yilmaz, Ibrahim and Kapoor, Kavish and Siraj, Ambareen and Abouyoussef, Mahmoud},
booktitle={proceedings of the 2021 ACM workshop on secure and trustworthy cyber-physical systems},
pages={33--38},
year={2021}
}
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title={“real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice},
author={Apruzzese, Giovanni and Anderson, Hyrum S and Dambra, Savino and Freeman, David and Pierazzi, Fabio and Roundy, Kevin},
booktitle={2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)},
pages={339--364},
year={2023},
organization={IEEE}
}
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title={Legal risks of adversarial machine learning research},
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year={2020}
}
@inproceedings{Cao2020HateGANAG,
title={HateGAN: Adversarial Generative-Based Data Augmentation for Hate Speech Detection},
author={Rui Cao and Roy Ka-Wei Lee},
booktitle={International Conference on Computational Linguistics},
year={2020},
url={https://api.semanticscholar.org/CorpusID:227230383}
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@article{Nurseitov2022ApplicationOM,
title={Application of machine learning methods to detect and classify Core images using GAN and texture recognition},
author={Daniyar B. Nurseitov and Kairat A. Bostanbekov and Galymzhan Abdimanap and Abdelrahman Abdallah and Anel N. Alimova and Darkhan Kurmangaliyev},
journal={ArXiv},
year={2022},
volume={abs/2204.14224},
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title={Attacks against Machine Learning Models in 5G Networks},
author={Mikhail Zolotukhin and Di Zhang and Parsa Miraghaie and Timo H{\"a}m{\"a}l{\"a}inen and Wang Ke and Marja Dunderfelt},
journal={2022 6th European Conference on Electrical Engineering \& Computer Science (ELECS)},
year={2022},
pages={106-114},
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}
@article{Yuan2023MultiSpacePhishET,
title={Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors Using Machine Learning},
author={Ying Yuan and Giovanni Apruzzese and Mauro Conti},
journal={Digital Threats: Research and Practice},
year={2023},
volume={5},
pages={1 - 51},
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}
@inproceedings{Radlak2021DefendingAS,
title={Defending against sparse adversarial attacks using impulsive noise reduction filters},
author={Krystian Radlak and Michal Szczepankiewicz and Bogdan Smolka},
booktitle={Defense + Commercial Sensing},
year={2021},
url={https://api.semanticscholar.org/CorpusID:234868177}
}
@article{to2023effectiveness,
title={On the Effectiveness of Adversarial Samples against Ensemble Learning-based Windows PE Malware Detectors},
author={To, Trong-Nghia and Kim, Danh Le and Hien, Do Thi Thu and Khoa, Nghi Hoang and Hoang, Hien Do and Duy, Phan The and Pham, Van-Hau},
journal={arXiv preprint arXiv:2309.13841},
year={2023}
}
@article{ifci2023AnalysisOT,
title={Analysis of Turkey's Cybersecurity Strategies: Historical Developments, Scope, Content and Objectives},
author={Hasan Çifci},
journal={Sakarya University Journal of Science},
year={2023},
url={https://api.semanticscholar.org/CorpusID:268035521}
}
@INPROCEEDINGS{10585001,
author={Chahar, Suman and Gupta, Sonali and Dhingra, Isha and Kaswan, Kuldeep Singh},
booktitle={2024 International Conference on Computational Intelligence and Computing Applications (ICCICA)},
title={Adversarial Threats in Machine Learning: A Critical Analysis},
year={2024},
volume={1},
number={},
pages={253-258},
keywords={Training;Surveys;Technological innovation;Ethics;Terminology;Collaboration;Machine learning;Automobiles;Transportation;Cybersecurity;Adversarial Attacks;Model Explain-ability},
doi={10.1109/ICCICA60014.2024.10585001}
}
@article{yuan2020fooling,
title={Fooling the primate brain with minimal, targeted image manipulation},
author={Yuan, Li and Xiao, Will and Dellaferrera, Giorgia and Kreiman, Gabriel and Tay, Francis EH and Feng, Jiashi and Livingstone, Margaret S},
journal={arXiv preprint arXiv:2011.05623},
year={2020}
}
%
% intro
%
@article{szegedy2013intriguing,
title={Intriguing properties of neural networks},
author={Szegedy, C},
journal={arXiv preprint arXiv:1312.6199},
year={2013}
}
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title={Adversarial examples: Opportunities and challenges},
author={Zhang, Jiliang and Li, Chen},
journal={IEEE transactions on neural networks and learning systems},
volume={31},
number={7},
pages={2578--2593},
year={2019},
publisher={IEEE}
}
@inproceedings{korkmaz2023detecting,
title={Detecting adversarial directions in deep reinforcement learning to make robust decisions},
author={Korkmaz, Ezgi and Brown-Cohen, Jonah},
booktitle={International Conference on Machine Learning},
pages={17534--17543},
year={2023},
organization={PMLR}
}
@article{Han2022TextAA,
title={Text Adversarial Attacks and Defenses: Issues, Taxonomy, and Perspectives},
author={Xuechun Han and Ying Zhang and Wei Wang and Bin Wang},
journal={Security and Communication Networks},
year={2022},
url={https://api.semanticscholar.org/CorpusID:248369346}
}
@inproceedings{rajaratnam2018noise,
title={Noise flooding for detecting audio adversarial examples against automatic speech recognition},
author={Rajaratnam, Krishan and Kalita, Jugal},
booktitle={2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)},
pages={197--201},
year={2018},
organization={IEEE}
}
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title={Adversarial Examples Construction Towards White-Box Q Table Variation in DQN Pathfinding Training},
author={XiaoXuan Bai and Wenjia Niu and Jiqiang Liu and Xu Gao and Yingxiao Xiang and Jingjing Liu},
journal={2018 IEEE Third International Conference on Data Science in Cyberspace (DSC)},
year={2018},
pages={781-787},
url={https://api.semanticscholar.org/CorpusID:49895854}
}
@inproceedings{eisenhofer2023no,
title={No more Reviewer\# 2: Subverting Automatic $\{$Paper-Reviewer$\}$ Assignment using Adversarial Learning},
author={Eisenhofer, Thorsten and Quiring, Erwin and M{\"o}ller, Jonas and Riepel, Doreen and Holz, Thorsten and Rieck, Konrad},
booktitle={32nd USENIX Security Symposium (USENIX Security 23)},
pages={5109--5126},
year={2023}
}
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title={Adversarial Attacks against Binary Similarity Systems},
author={Capozzi, Gianluca and D’Elia, Daniele Cono and Di Luna, Giuseppe Antonio and Querzoni, Leonardo},
journal={IEEE Access},
year={2024},
publisher={IEEE}
}
@article{Kashyap2024AdversarialAA,
title={Adversarial Attacks and Defenses in Deep Learning},
author={Swati Kashyap and Akshay Sharma and Savit Gautam and Rishabh Sharma and Sneha Chauhan and Simran},
journal={2024 International Conference on Emerging Innovations and Advanced Computing (INNOCOMP)},
year={2024},
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}
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year={2020}
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title={Adversarial Attacks in Machine Learning: Key Insights and Defense Approaches},
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year={2024},
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journal={arXiv preprint arXiv:2004.01970},
year={2020}
}
@article{Li2022ASO,
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author={Yishan Li and Yanming Guo and Yuxiang Xie and Qi Wang},
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year={2022},
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volume={76},
number={4},
pages={329--345},
year={2022},
publisher={Taylor \& Francis}
}
@inproceedings{li2019nattack,
title={Nattack: Learning the distributions of adversarial examples for an improved black-box attack on deep neural networks},
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booktitle={International Conference on Machine Learning},
pages={3866--3876},
year={2019},
organization={PMLR}
}
@article{zheng2023black,
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journal={arXiv preprint arXiv:2310.10010},
year={2023}
}
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year={2020}
}
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title={Assessing Adversarial Robustness of Large Language Models: An Empirical Study},
author={Yang, Zeyu and Meng, Zhao and Zheng, Xiaochen and Wattenhofer, Roger},
journal={arXiv preprint arXiv:2405.02764},
year={2024}
}
%
% imperceptibliity
%
@online{brown2018unrestricted,
author = {Brown, Tom B. and Olsson, Catherine},
title = {Introducing the Unrestricted Adversarial Examples Challenge},
year = {2018},
month = {9},
day = {13},
publisher = {Google Research Blog},
organization = {Google Brain Team}
}
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journal={arXiv preprint arXiv:2403.04493},
year={2024}
}
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year={2020}
}
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year={2019}
}
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title={Preserving semantics in textual adversarial attacks},
author={Herel, David and Cisneros, Hugo and Mikolov, Tomas},
booktitle={ECAI 2023},
pages={1036--1043},
year={2023},
publisher={IOS Press}
}
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}
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year={2017}
}
@inproceedings{ning2023hflic,
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pages={188--194},
year={2023},
organization={IEEE}
}
@inproceedings{careil2023towards,
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author={Careil, Marlene and Muckley, Matthew J and Verbeek, Jakob and Lathuili{\`e}re, St{\'e}phane},
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year={2023}
}
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title={Imperceptible adversarial attack via invertible neural networks},
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number={1},
pages={414--424},
year={2023}
}
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author={McGuire, Sarah and Jackson, Shane and Emerson, Tegan and Kvinge, Henry},
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year={2023},
organization={PMLR}
}
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year={2024}
}
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year={2021}
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year={2022},
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}
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journal={2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)},
year={2022},
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}
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year={2022}
}
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year={2024}
}
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year={2017}
}
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journal={Advances in Neural Information Processing Systems},
volume={34},
pages={23885--23899},
year={2021}
}
@ONLINE{teenybiscuittweet,
author = {Zack, Karen},
title = {Archive of deleted tweet by @teenybiscuit},
url = {https://imgur.com/a/deep-learning-training-set-K4RWn},
urldate = {2024-06-04}
}
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year={2021}
}
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pages={1802--1811},
year={2019},
organization={PMLR}
}
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year={2018}
}
@article{fazlija2024real,
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author={Fazlija, Dren and Orlov, Arkadij and Schrader, Johanna and Z{\"u}hlke, Monty-Maximilian and Rohs, Michael and Kudenko, Daniel},
journal={arXiv preprint arXiv:2404.12653},
year={2024}
}
%
% mental models
%
@inproceedings{sutskever2014sequence,
title={Sequence to Sequence Learning with Neural Networks},
author={Sutskever, Ilya and Vinyals, Oriol and Le, Quoc V.},
booktitle={Neural Information Processing Systems (NeurIPS) Test of Time Award},
year={2024},
address={West Exhibition Hall C, B3},
note={Presented at NeurIPS 2024 Test of Time Award Session}
}
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}
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year={2018},
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}
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year={2020},
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}
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year={2018}
}
@article{shamir2021dimpled,
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year={2021}
}
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year={2023},
url={https://api.semanticscholar.org/CorpusID:259099406}
}
@inproceedings{dyrmishi2023empirical,
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author={Dyrmishi, Salijona and Ghamizi, Salah and Simonetto, Thibault and Le Traon, Yves and Cordy, Maxime},
booktitle={2023 IEEE symposium on security and privacy (SP)},
pages={1384--1400},
year={2023},
organization={IEEE}
}
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journal={arXiv preprint arXiv:1811.00525},
year={2018}
}
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year = {2019},
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}
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year={2018}
}
@inproceedings{wong2018provable,
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year={2018},
organization={PMLR}
}
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year={2018}
}
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year={2019},
organization={PMLR}
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year={2018}
}
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}
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}
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@article{fawzi2016robustness,
title={Robustness of classifiers: from adversarial to random noise},
author={Fawzi, Alhussein and Moosavi-Dezfooli, Seyed-Mohsen and Frossard, Pascal},
journal={Advances in neural information processing systems},
volume={29},
year={2016}