Obfuscation Technique
Obfuscation techniques aim to transform data or code to conceal sensitive information while preserving functionality or utility. Current research focuses on developing and evaluating obfuscation methods for various data types (text, images, code, and even model parameters) using diverse approaches, including large language models, transformer networks, and differential privacy mechanisms. These techniques are crucial for protecting privacy in various applications, from securing sensitive data shared across platforms to mitigating risks associated with adversarial attacks on machine learning models. The ongoing development and rigorous evaluation of these methods are vital for advancing privacy-preserving technologies and ensuring responsible data handling.
Papers
Antelope: Potent and Concealed Jailbreak Attack Strategy
Xin Zhao, Xiaojun Chen, Haoyu Gao
Unseen Horizons: Unveiling the Real Capability of LLM Code Generation Beyond the Familiar
Yuanliang Zhang, Yifan Xie, Shanshan Li, Ke Liu, Chong Wang, Zhouyang Jia, Xiangbing Huang, Jie Song, Chaopeng Luo, Zhizheng Zheng, Rulin Xu, Yitong Liu, Si Zheng, Xiangke Liao