Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models
Authors: Zenghui Yuan, Yangming Xu, Jiawen Shi, Pan Zhou, Lichao Sun | Published: 2025-05-29
Model Protection Methods
THEMIS: Towards Practical Intellectual Property Protection for Post-Deployment On-Device Deep Learning Models
Authors: Yujin Huang, Zhi Zhang, Qingchuan Zhao, Xingliang Yuan, Chunyang Chen | Published: 2025-03-31
Encryption and Real Time Decryption for protecting Machine Learning models in Android Applications
Authors: Aryan Verma | Published: 2021-09-06
Automating Defense Against Adversarial Attacks: Discovery of Vulnerabilities and Application of Multi-INT Imagery to Protect Deployed Models
Authors: Josh Kalin, David Noever, Matthew Ciolino, Dominick Hambrick, Gerry Dozier | Published: 2021-03-29
Leaky Nets: Recovering Embedded Neural Network Models and Inputs through Simple Power and Timing Side-Channels — Attacks and Defenses
Authors: Saurav Maji, Utsav Banerjee, Anantha P. Chandrakasan | Published: 2021-03-26
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
Authors: Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein | Published: 2020-12-18 | Updated: 2021-03-31
CSI Neural Network: Using Side-channels to Recover Your Artificial Neural Network Information
Authors: Lejla Batina, Shivam Bhasin, Dirmanto Jap, Stjepan Picek | Published: 2018-10-22