Ganxiang Yang (Shanghai Jiao Tong University), Chenyang Liu (Shanghai Jiao Tong University), Zhen Huang (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Hongfei Fu (Shanghai Jiao Tong University), Yuanyuan Zhang (Shanghai Jiao Tong University), Haojin Zhu (Shanghai Jiao Tong University)

Trusted Execution Environments (TEE) have been widely adopted as a protection approach for security-critical applications. Although feature extensions have been previously proposed to improve the usability of enclaves, their provision patterns are still confronted with security challenges. This paper presents Palantir, a verifiable multi-layered inter-enclave privilege model for secure feature extensions to enclaves. Specifically, a parent-children inter-enclave relationship, with which a parent enclave is granted two privileged permissions, the Execution Control and Spatial Control, over its children enclaves to facilitate secure feature extensions, is introduced. Moreover, by enabling nesting parent-children relationships, Palantir achieves multi-layered privileges (MLP) that allow feature extensions to be placed in various privilege layers following the Principle of Least Privilege. To prove the security of Palantir, we verified that our privilege model does not break or weaken the security guarantees of enclaves by building and verifying a formal model named $text{TAP}^{infty}$. Furthermore, We implemented a prototype of Palantir on Penglai, an open-sourced RISC-V TEE platform. The evaluation demonstrates the promising performance of Palantir in runtime overhead $(<5%)$ and startup latencies.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 118 ) ) ) [post__not_in] => Array ( [0] => 20069 ) )

Power-Related Side-Channel Attacks using the Android Sensor Framework

Mathias Oberhuber (Graz University of Technology), Martin Unterguggenberger (Graz University of Technology), Lukas Maar (Graz University of Technology), Andreas Kogler (Graz University of Technology), Stefan Mangard (Graz University of Technology)

Read More

Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication...

Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

Read More

The Kids Are All Right: Investigating the Susceptibility of...

Elijah Bouma-Sims (Carnegie Mellon University), Lily Klucinec (Carnegie Mellon University), Mandy Lanyon (Carnegie Mellon University), Julie Downs (Carnegie Mellon University), Lorrie Faith Cranor (Carnegie Mellon University)

Read More

Truman: Constructing Device Behavior Models from OS Drivers to...

Zheyu Ma (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; EPFL; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Qiang Liu (EPFL), Zheming Li (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Tingting Yin (Zhongguancun…

Read More