Qihang Zhou (Institute of Information Engineering, Chinese Academy of Sciences), Wenzhuo Cao (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Xiaoqi Jia (Institute of Information Engineering, Chinese Academy of Sciences), Peng Liu (The Pennsylvania State University, USA), Shengzhi Zhang (Department of Computer Science, Metropolitan College, Boston University, USA), Jiayun Chen (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Shaowen Xu (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyberspace Security, University of Chinese Academy of Sciences), Zhenyu Song (Institute of Information Engineering, Chinese Academy of Science)

Containers have become widely adopted in cloud platforms due to their efficient deployment and high resource utilization. However, their weak isolation has always posed a significant security concern. In this paper, we propose RContainer, a novel secure container architecture that protects containers from untrusted operating systems and enforces strong isolation among containers by extending ARM Confidential Computing Architecture (CCA) hardware primitives. RContainer introduces a small, trusted mini-OS that runs alongside the deprivileged OS, responsible for monitoring the control flow between the operating system and containers. Additionally, RContainer uses shim-style isolation, creating an isolated physical address space called con-shim for each container at the kernel layer through the Granule Protection Check mechanism. We have implemented RContainer on ARMv9-A Fixed Virtual Platform and ARMv8 hardware SoC for security analysis and performance evaluation. Experimental results demonstrate that RContainer can significantly enhance container security with a modest performance overhead and a minimal Trusted Computing Base (TCB).

View More Papers

Vision: Retiring Scenarios — Enabling Ecologically Valid Measurement in...

Oliver D. Reithmaier (Leibniz University Hannover), Thorsten Thiel (Atmina Solutions), Anne Vonderheide (Leibniz University Hannover), Markus Dürmuth (Leibniz University Hannover)

Read More

Passive Inference Attacks on Split Learning via Adversarial Regularization

Xiaochen Zhu (National University of Singapore & Massachusetts Institute of Technology), Xinjian Luo (National University of Singapore & Mohamed bin Zayed University of Artificial Intelligence), Yuncheng Wu (Renmin University of China), Yangfan Jiang (National University of Singapore), Xiaokui Xiao (National University of Singapore), Beng Chin Ooi (National University of Singapore)

Read More

Query Privacy in Data Spaces

Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

Read More

Securing BGP ASAP: ASPA and other Post-ROV Defenses

Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), Reynaldo Morillo (University of Connecticut), Arvind Kasiliya (University of Connecticut), Bing Wang (University of Connecticut), Amir Herzberg (University of Connecticut)

Read More