@misc{ristea2026direction,title={Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points},author={Ristea, Dan and McFadden, Shae and Shereen, Ezzeldin and Dwyer, Madeleine and Vyas, Sanyam and Hicks, Chris and Mavroudis, Vasilios},year={2026},eprint={2412.11194},archiveprefix={arXiv},primaryclass={cs.SE},}
AI4CNI
Building Better Environments for Autonomous Cyber Defence
Chris Hicks, Elizabeth Bates, Shae McFadden, Isaac Symes Thompson, Myles Foley, and 10 more authors
@misc{hicks2026building,title={Building Better Environments for Autonomous Cyber Defence},author={Hicks, Chris and Bates, Elizabeth and McFadden, Shae and Thompson, Isaac Symes and Foley, Myles and Chapman, Ed and Dice, Nickolas Espinosa and Samaddar, Ankita and Sylvester, Joshua and Neema, Himanshu and Butts, Nicholas and Foster, Nate and Ridley, Ahmad and M, Zoe and Jones, Paul},year={2026},eprint={2604.08805},archiveprefix={arXiv},primaryclass={cs.CR},}
arXiv
SoK: The Pitfalls of Deep Reinforcement Learning for Cybersecurity
Shae McFadden, Myles Foley, Elizabeth Bates, Ilias Tsingenopoulos, Sanyam Vyas, and 3 more authors
@misc{McFadden2026Pitfalls,title={SoK: The Pitfalls of Deep Reinforcement Learning for Cybersecurity},author={McFadden, Shae and Foley, Myles and Bates, Elizabeth and Tsingenopoulos, Ilias and Vyas, Sanyam and Mavroudis, Vasilios and Hicks, Chris and Pierazzi, Fabio},year={2026},eprint={2602.08690},archiveprefix={arXiv},primaryclass={cs.LG},}
AAAI
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
Shae McFadden, Myles Foley, Mario D’Onghia, Chris Hicks, Vasilios Mavroudis, and 2 more authors
In Proc. of the AAAI Conference on Artificial Intelligence , 2026
@inproceedings{McFadden2026DRMD,title={DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift},author={McFadden, Shae and Foley, Myles and D'Onghia, Mario and Hicks, Chris and Mavroudis, Vasilios and Paoletti, Nicola and Pierazzi, Fabio},booktitle={Proc. of the {AAAI} Conference on Artificial Intelligence},year={2026},}
TMLR
One Pic is All it Takes: Poisoning Visual Document Retrieval Augmented Generation with a Single Image
Ezzeldin Shereen, Dan Ristea, Shae McFadden, Burak Hasircioglu, Vasilios Mavroudis, and 1 more author
@article{shereen2026OnePic,title={One Pic is All it Takes: Poisoning Visual Document Retrieval Augmented Generation with a Single Image},author={Shereen, Ezzeldin and Ristea, Dan and McFadden, Shae and Hasircioglu, Burak and Mavroudis, Vasilios and Hicks, Chris},journal={Transactions on Machine Learning Research},year={2026},}
2024
ARTMAN
The Impact of Active Learning on Availability Data Poisoning for Android Malware Classifiers
Shae McFadden, Zeliang Kan, Lorenzo Cavallaro, and Fabio Pierazzi
In Proc. of the Annual Computer Security Applications Conference Workshops (ACSAC Workshops) , 2024
@inproceedings{mcfadden2024recovery,title={The Impact of Active Learning on Availability Data Poisoning for Android Malware Classifiers},author={McFadden, Shae and Kan, Zeliang and Cavallaro, Lorenzo and Pierazzi, Fabio},booktitle={Proc. of the Annual Computer Security Applications Conference Workshops ({ACSAC Workshops})},year={2024},}
Competition
Impact of "TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time"
Shae McFadden, Zeliang Kan, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, and 3 more authors
@misc{McFadden2024tesseract,title={Impact of "{TESSERACT}: Eliminating Experimental Bias in Malware Classification across Space and Time"},author={McFadden, Shae and Kan, Zeliang and Arp, Daniel and Pendlebury, Feargus and Jordaney, Roberto and Kinder, Johannes and Pierazzi, Fabio and Cavallaro, Lorenzo},booktitle={ACSAC Cybersecurity Artifact Competition},year={2024},}
DLSP
Wendigo: Deep Reinforcement Learning for Denial-of-Service Query Discovery in GraphQL
Shae McFadden, Marcello Maugeri, Chris Hicks, Vasilis Mavroudis, and Fabio Pierazzi
In Proc. of the IEEE Workshop on Deep Learning Security and Privacy (DLSP) , 2024
@inproceedings{mcfadden2024wendigo,title={Wendigo: Deep Reinforcement Learning for Denial-of-Service Query Discovery in GraphQL},author={McFadden, Shae and Maugeri, Marcello and Hicks, Chris and Mavroudis, Vasilis and Pierazzi, Fabio},booktitle={Proc. of the {IEEE} Workshop on Deep Learning Security and Privacy ({DLSP})},year={2024},}
arXiv
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, and 3 more authors
@misc{kan2024tesseract,title={TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)},author={Kan, Zeliang and McFadden, Shae and Arp, Daniel and Pendlebury, Feargus and Jordaney, Roberto and Kinder, Johannes and Pierazzi, Fabio and Cavallaro, Lorenzo},year={2024},eprint={2402.01359},archiveprefix={arXiv},primaryclass={cs.LG},}
2023
CCS Poster
Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning
Shae McFadden, Zeliang Kan, Lorenzo Cavallaro, and Fabio Pierazzi
In Proc. of ACM Conference on Computer and Communications Security (CCS) , 2023
@inproceedings{mcfadden2023rpal,title={Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning},author={McFadden, Shae and Kan, Zeliang and Cavallaro, Lorenzo and Pierazzi, Fabio},booktitle={Proc. of {ACM} Conference on Computer and Communications Security ({CCS})},year={2023},}