Toward a Global Data Infrastructure

Mor, Nitesh; Zhang, Ben; Kolb, Jack; Chan, Douglas S.; Goyal, Nikhil; Sun, Nicholas; Lutz, Ken; Allman, Eric; Wawrzynek, John; Lee, Edward A.; Kubiatowicz, John

doi:10.1109/mic.2016.51

Cited by 21 publications

(14 citation statements)

References 11 publications

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“…Global Data Plane (GDP) [5] is a log-based distributed cloud platform, which focuses on the characteristics of the IoT, such as small gateway devices, moderate or low end computing power nodes, etc. GDP is similar to Cisco Fog Computing [14] and Edge computing, but focuses on a fully distributed storage, not computing.…”

Section: ) Global Data Planementioning

confidence: 99%

“…A growing number of IoT devices will require efficient and scalable solutions for data dissemination. Global Data Plane (GDP) [5], which is a data-centric networking approach, satisfies the requirements by adopting appendonly logs. IoT devices generate data, which will update the append-only logs that are written on a potentially untrusted distributed infrastructure.…”

Section: Introductionmentioning

confidence: 99%

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An SGX-Based Key Management Framework for Data Centric Networking

Park

Kim

et al. 2020

IEEE Access

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As the Internet has evolved from host-to-host communications to content distribution, datacentric networking is poised to improve networking efficiency. Especially, as the cloud computing, the Internet of Things (IoT), the fifth-generation (5G) networking become popular, there is a consensus that data is to be distributed over some potentially untrusted middleboxes (e.g., CDN servers, web caches) that mediates between data writers and data readers. While data-centric networking designs such as Edge Caching, Global Data Plane (GDP), Named Data Networking (NDN) have been active explored, there have been few studies on how to distribute and manage keys for data access control in such designs with untrusted servers (i.e., middleboxes). We present a key management framework in which symmetric and asymmetric keys are securely managed. A writer publishes his (encrypted) data along with the decryption key for the data. Likewise, an authorized reader retrieves the decryption key as well as the data of interest. To make the key distribution securely between a writer and a reader via an untrusted server, we introduce a key server running on top of the Intel SGX technology. In this way, we can manage and distribute keys for data access control in an efficient and flexible manner. We evaluate the proposed framework by prototyping, which shows some delays in key publishing and retrieval. However, the delays in real operations will be marginal as the period will become longer.INDEX TERMS Data-centric networking, key management, Intel software guard extension, transport layer security.

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Section: ) Global Data Planementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An SGX-Based Key Management Framework for Data Centric Networking

Park

Kim

et al. 2020

IEEE Access

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“…Data-centric infrastuctures such as Global Data Plane (GDP) [52] can provide a scalable alternative to control the placement and scope of data while providing verifiable security guarantees. GDP uses cryptographically secured data containers called DataCapsules.…”

Section: B Security Privacy and Control Over Datamentioning

confidence: 99%

A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering

Tanwani

Mor

Kubiatowicz

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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The growing demand of industrial, automotive and service robots presents a challenge to the centralized Cloud Robotics model in terms of privacy, security, latency, bandwidth, and reliability. In this paper, we present a 'Fog Robotics' approach to deep robot learning that distributes compute, storage and networking resources between the Cloud and the Edge in a federated manner. Deep models are trained on non-private (public) synthetic images in the Cloud; the models are adapted to the private real images of the environment at the Edge within a trusted network and subsequently, deployed as a service for lowlatency and secure inference/prediction for other robots in the network. We apply this approach to surface decluttering, where a mobile robot picks and sorts objects from a cluttered floor by learning a deep object recognition and a grasp planning model. Experiments suggest that Fog Robotics can improve performance by sim-to-real domain adaptation in comparison to exclusively using Cloud or Edge resources, while reducing the inference cycle time by 4× to successfully declutter 86% of objects over 213 attempts.

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“…The IOT paradigm promises to revolutionize the way in which we can perceive, transform, and unite the physical-cyber world into a united Internet of Things (IOT) world. IOT architecture [3][4] has received highlight in IOT related fields, where several solutions have been proposed from different perspectives such as IOT Computing [5][7] , IOT Storage [6] , etc.. So many researches focus on the IOT architecture, which are trying to focus on how to make the IOT as a whole integrating the current physical world and the extend future world, from the aspect of computation, storage, communication, security, practical, service, and others focus on the IOT applications.…”

Section: Introductionmentioning

confidence: 99%

FLIOTA: A Novel Four-Layer IOT Architecture

Zhang¹

2019

dteees

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The IOT paradigm promises to revolutionize the way we perceive the world which unites the physical world into Internet of Things (IOT) world. This paper discussed the IOT Architecture on the dynamic condition and information isolated island. Thus a novel Four-layer IOT architecture(FLIOTA) was proposed, which consists of Core Layer (CL), Security and Application Layer (SIL), Application Layer (AL) and Sensor and Actuator Layer (SAL), and is better to settle down the problem of the ignorance of dynamics of adaptability and the information isolated island.

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Toward a Global Data Infrastructure

Cited by 21 publications

References 11 publications

An SGX-Based Key Management Framework for Data Centric Networking

An SGX-Based Key Management Framework for Data Centric Networking

A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering

FLIOTA: A Novel Four-Layer IOT Architecture

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