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diff --git a/references.bib b/references.bib
@@ -80,6 +80,202 @@ @article{schorn1993axiomatic
 % motivation
 %
 
+@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}
+}
 @ARTICLE{9099439,
   author={Sadeghi, Koosha and Banerjee, Ayan and Gupta, Sandeep K. S.},
   journal={IEEE Transactions on Emerging Topics in Computational Intelligence}, 
@@ -143,6 +339,46 @@ @article{Zolotukhin2022AttacksAM
   pages={106-114},
   url={https://api.semanticscholar.org/CorpusID:259102662}
 }
+@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},
+  url={https://api.semanticscholar.org/CorpusID:266363431}
+}
+@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}
+}
 
 %
 % intro
@@ -457,6 +693,12 @@ @article{gilmer2018motivating
   journal={arXiv preprint arXiv:1807.06732},
   year={2018}
 }
+@article{fazlija2024real,
+  title={How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples},
+  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

diff --git a/thesis.pdf b/thesis.pdf