ZhanPeng Liu (Peking University), Chenyang Li (Peking University), Wende Tan (Imperial College London), Yuan Li (Zhongguancun Laboratory), Xinhui Han (Peking University), Xi Cao (Science City (Guangzhou) Digital Technology Group Co., Ltd.), Yong Xie (Qinghai University), Chao Zhang (Tsinghua University)

Modern software systems increasingly rely on compartmentalization to isolate untrusted or potentially vulnerable components, such as third-party drivers and JIT-compiled code.
However, existing hardware isolation techniques suffer from scalability constraints, high switching latency, and inadequate security guarantees. In particular, permission-changing instructions used by some compartmentalization technology, such as Intel MPK’s WRPKRU, can be exploited by untrusted code, which complicates the secure deployment process.

In this paper, we introduce LatticeBox, a hardware-software co-designed framework that addresses these limitations using a lattice-based access control model. LatticeBox encodes permissions and memory regions as compact, hierarchical N-bit vectors. This design enables a hardware architecture that reduces domain-switching latency to a single CPU cycle and inherently prevents misuse of permission-switching instructions. Additionally, LatticeBox employs a customized instruction (lp_land) to enforce strict cross-domain control-flow integrity, effectively preventing unauthorized indirect function calls. We implement LatticeBox on a RISC-V BOOM core and evaluate it using both microbenchmarks and real-world applications, including WebAssembly runtimes and Linux kernel modules. Our results show that LatticeBox achieves domain switching up to 180× faster than Intel MPK while supporting fine-grained, scalable isolation. Evaluation on real-world workloads demonstrates only a modest performance impact, with only 2% slowdown for enhanced WebAssembly runtimes and just 3% lower throughput for ApacheBench running isolated Linux kernel modules.

View More Papers

QNBAD: Quantum Noise-induced Backdoor Attacks against Zero Noise Extrapolation

Cheng Chu (Indiana University Bloomington), Qian Lou (University of Central Florida), Fan Chen (Indiana University Bloomington), Lei Jiang (Indiana University Bloomington)

Read More

A Comparative Study of Program Graph Effectiveness for Binary...

Michael Kadoshnikov, Clemente Izurieta, Matthew Revelle (Montana State University)

Read More

From Perception to Protection: A Developer-Centered Study of Security...

Kunlin Cai (University of California, Los Angeles), Jinghuai Zhang (University of California, Los Angeles), Ying Li (University of California, Los Angeles), Zhiyuan Wang (University of Virginia), Xun Chen (Independent Researcher), Tianshi Li (Northeastern University), Yuan Tian (University of California, Los Angeles)

Read More