What You See Is The Tip Of The Iceberg: A Novel Technique For Data Leakage Prevention
Kai Chen, Qian Yang, Jiankai Wang, Duohe Ma, Liming Wang, Zhen Xu · 2024
Data leakage is one of the most severe security threats that can compromise sensitive data through breaches or unauthorized access. Existing techniques usually adopt encryption or access control protection methods, but inevitably affects the data usability and introduce significant overhead. In this paper, we propose a novel technique for data leakage prevention in collaborative systems by dynamically broadening the deceptive attack surface. Our proposed technique offers an adaptive deception strategy that leverages historical user behaviors and current operations to generate deceptive data, and we developed an amplifying-based calculation method to enhance the accuracy of user trust degree evaluation. Furthermore, we introduce three deceptive indicators to evaluate our technique. Experimental results show that our technique can effectively prevent data leakage while preserving data usability and imposing minimal overhead to the system.