Abstract

Ransomware attacks are often catastrophic, yet existing reactive and preventative measures could only partially mitigate ransomware damage, often not in a timely manner, and often cannot prevent the novel attack vectors. Many of them were program-centric or data-centric and did not take into consideration user intention or consent. In this paper, we advocate for a dynamic approach of detecting ransomware-like behaviors by proposing a user-centric access control framework, which collects security indicators from the Operating System (OS) to deduct security metrics, compute security indicators and estimate security positions, to dynamically make access control assessments on file access requests. To demonstrate its applicability, we effectuated the principles of User-Driven Access Control (UDAC) for user intention (the goal of a user operation) and Content-Based Isolation (CBI) for user consent (the acceptance of the consequence of a user operation), and developed a proof-of-concept prototype on Windows desktop platforms. It collected information that could reveal the application identity, behavior and the OS environmental factor, before assessing whether an access request to the file system violated the principles of UDAC or CBI. Our prototype was able to raise early warnings on both attacks by real and simulated ransomware of novel vectors.

Links

• https://www.sciencedirect.com/science/article/pii/S0167404821002856

Citation

McIntosh, T., Kayes, A.S.M., Phoebe Chen, Y.-P., Ng, A., Watters, P., 2021. Dynamic User-Centric Access Control for Detection of Ransomware Attacks. Computers & Security. https://doi.org/10.1016/j.cose.2021.102461