Integrated Scheduling for a Reliable Dual-OS Monitor

Sangorrin, Daniel; Honda, Shinya; Takada, Hiroaki

doi:10.2197/ipsjtrans.5.47

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…Furthermore, the scheduler should take real-time constraints into consideration. Authors in [20] propose a secure scheduler that enhances the responsiveness of the main OS without compromising the real-time performance of the system.…”

Section: Building Blocks Of Teementioning

confidence: 99%

Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

Zobaed

Mokhtari

Champati

et al. 2022

2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)

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Confidential computing has gained prominence due to the escalating volume of datadriven applications (e.g., machine learning and big data) and the acute desire for secure processing of sensitive data, particularly, across distributed environments, such as edge-to-cloud continuum. Provided that the works accomplished in this emerging area are scattered across various research fields, this paper aims at surveying the fundamental concepts, and cutting-edge software and hardware solutions developed for confidential computing using trusted execution environments, homomorphic encryption, and secure enclaves. We underscore the significance of building trust in both hardware and software levels and delve into their applications particularly for machine learning (ML) applications. While substantial progress has been made, there are some barely-explored areas that need extra attention from the researchers and practitioners in the community to improve confidentiality aspects, develop more robust attestation mechanisms, and to address vulnerabilities of the existing trusted execution environments. Providing a comprehensive taxonomy of the confidential computing landscape, this survey enables researchers to advance this field to ultimately ensure the secure processing of users' sensitive data across a multitude of applications and computing tiers.

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Section: Building Blocks Of Teementioning

confidence: 99%

Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

Zobaed

Mokhtari

Champati

et al. 2022

2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)

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“…DRAM is divided into two parts, one for the secure world to store trusted applications and the other for normal world to run Linux. SafeG [43] is used as the monitor for world switching and runs on the on-chip memory. Since FMP, SafeG, and Linux storage space cannot be overlapped, we will store them separately in the memory area, where 0x00900000-0x0091FFFF is used by FMP, and 0x00920000-0x0092FFFF is used by SafeG.…”

Section: Memory Isolationmentioning

confidence: 99%

SoftME: A Software-Based Memory Protection Approach for TEE System to Resist Physical Attacks

Zhang

Zhao

et al. 2019

Security and Communication Networks

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The development of the Internet of Things has made embedded devices widely used. Embedded devices are often used to process sensitive data, making them the target of attackers. ARM TrustZone technology is used to protect embedded device data from compromised operating systems and applications. But as the value of the data stored in embedded devices increases, more and more effective physical attacks have emerged. However, TrustZone cannot resist physical attacks. We propose SoftME, an approach that utilizes the on-chip memory space to provide a trusted execution environment for sensitive applications. We protect the confidentiality and integrity of the data stored on the off-chip memory. In addition, we design task scheduling in the encryption process. We implement a prototype system of our approach on the development board supporting TrustZone and evaluate the overhead of our approach. The experimental results show that our approach improves the security of the system, and there is no significant increase in system overhead.

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“…Furthermore, the scheduler should take real-time constraints into consideration. Authors in [23] propose a secure scheduler that enhances the responsiveness of the main OS without compromising the realtime performance of the system. • Inter-Environment Communication defines an interface allowing TEE to communicate with the rest of the system.…”

Section: Tee Building Blocksmentioning

confidence: 99%

Trusted Execution Environment: What It is, and What It is Not

Sabt

Achemlal

Bouabdallah

2015

2015 IEEE Trustcom/BigDataSE/Ispa

429

186

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Nowadays, there is a trend to design complex, yet secure systems. In this context, the Trusted Execution Environment (TEE) was designed to enrich the previously defined trusted platforms. TEE is commonly known as an isolated processing environment in which applications can be securely executed irrespective of the rest of the system. However, TEE still lacks a precise definition as well as representative building blocks that systematize its design. Existing definitions of TEE are largely inconsistent and unspecific, which leads to confusion in the use of the term and its differentiation from related concepts, such as secure execution environment (SEE). In this paper, we propose a precise definition of TEE and analyze its core properties. Furthermore, we discuss important concepts related to TEE, such as trust and formal verification. We give a short survey on the existing academic and industrial ARM TrustZone-based TEE, and compare them using our proposed definition. Finally, we discuss some known attacks on deployed TEE as well as its wide use to guarantee security in diverse applications.

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Integrated Scheduling for a Reliable Dual-OS Monitor

Cited by 3 publications

References 13 publications

Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

SoftME: A Software-Based Memory Protection Approach for TEE System to Resist Physical Attacks

Trusted Execution Environment: What It is, and What It is Not

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