Authenticating query results in edge computing

Pang, HweeHwa; Tan, Kian-Lee

doi:10.1109/icde.2004.1320027

Cited by 166 publications

(147 citation statements)

References 12 publications

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“…We compare three different range query verification methods, Authentic Publication proposed by Devanbu, et al in [6], Pang and Tan's verifiable B-tree (VB tree) in [17] and the proposals in this paper. We focus on Client proof overhead and verification cost and then consider the effect of bandwidth.…”

Section: Performance Comparisonmentioning

confidence: 99%

“…In the original Authentic Publication method, proof size depends on the number of data points in the answer and the tree height, O(log N ) additional hash values for a tree over N data points. Pang and Tan [17] proposed to eliminate this dependence on tree height with the verifiable B-tree (VB tree). This requires some degree of trust in the Publisher, relies heavily on Owner signatures and a proposed one-way digest function based on modular exponentiation.…”

Section: Introductionmentioning

confidence: 99%

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Verified Query Results from Hybrid Authentication Trees

Nuckolls

2005

Data and Applications Security XIX

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Abstract. We address the problem of verifying the accuracy of query results provided by an untrusted third party Publisher on behalf of a trusted data Owner. We propose a flexible database verification structure, the Hybrid Authentication Tree (HAT), based on fast cryptographic hashing and careful use of a more expensive one-way accumulator. This eliminates the dependence on tree height of earlier Merkle tree based proposals and improves on the VB tree, a recent proposal to reduce proof sizes, by eliminating a trust assumption and reliance on signatures. An evaluation of the Hybrid Authentication Tree against the VB tree and Authentic Publication showing that a HAT provides the smallest proofs and faster verification than the VB tree. With moderate bandwidth limitations, the HATs low proof overhead reduces transfer time to significantly outweigh the faster verification time of Authentic Publication. A HAT supports two verification modes that can vary per query and per Client to match Client resources and applications. This flexibility allows the HAT to match the best performance of both hash based and accumulator based methods.

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Section: Performance Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Verified Query Results from Hybrid Authentication Trees

Nuckolls

2005

Data and Applications Security XIX

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“…-removes the single point of failure in the infrastructure by lowering the dependency to the corporate data center, hence reducing its http://journals.uob.edu.bh susceptibility to denial of service attacks and improving service availability [34].…”

Section: ) Goalsmentioning

confidence: 99%

“…Edge computing is a natural extension of the Content Delivery Network (CDN) architecture [34] [35]. It pushes application logic and the underlying data processing from corporate data centers out to proxy servers at the "edge" of the network in order to achieve scalable and highly available Web services [34] and for better efficiency and performance [36].…”

Section: Edge Computingmentioning

confidence: 99%

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Evolution of the Distributed Computing Paradigms: a Brief Road Map

Barkallah¹

2017

IJCDS

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Today's computing development is being characterized by the rapid development of high speed networks and the increase in computing power. Computing is not any more limited to the supercomputers, PCs and laptops but also smart phones and tablets which are available for billions of users offering high computing performances at low cost and interconnected via Internet. This continuing technological development is leading the increase importance of the distributed computing paradigms and the apparition of new ones. This paper aims to review the most important distributed computing paradigms and the principal similarities and differences between them. This survey is a kind of a brief road map that would be useful for researchers, students, and commercial users.

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Internet of Things (IoT) and New Computing Paradigms

Chang

Srirama²,

Buyya

2019

Fog and Edge Computing

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The Internet of Things (IoT) [1] represents a comprehensive environment that interconnects a large number of heterogeneous physical objects or things such as appliances, facilities, animals, vehicles, farms, factories etc. to the Internet, in order to enhance the efficiency of the applications such as logistics, manufacturing, agriculture, urban computing, home automation, ambient assisted living and various real-time ubiquitous computing applications.Commonly, an IoT system follows the architecture of the Cloud-centric Internet of Things (CIoT) in which the physical objects are represented in the form of Web resources that are managed by the servers in the global Internet [2] . Fundamentally, in order to interconnect the physical entities to the Internet, the system will utilize various front-end devices such as wired or wireless sensors, actuators, readers to interact with them. Further, the front-end devices have the Internet connectivity via the mediate gateway nodes such as Internet modems, routers, switches, cellular base stations and so on. In general, the common IoT system involves three major technologies: embedded systems, middleware and cloud services, where the embedded systems provide intelligence to the front-end devices, middleware interconnects the heterogeneous embedded systems of front-end devices to the cloud and finally, the cloud provides comprehensive storage, processing, and management mechanisms. Although the CIoT model is a common approach to implement IoT systems, it is facing the growing challenges in IoT. Specifically, CIoT faces challenges in BLURS-Bandwidth, Latency, Uninterrupted, Resource-constraint and Security [3] . Bandwidth. The increasingly large and high-frequent rate data produced by objects in IoT will exceed the bandwidth availability. For example, a connected car can generate Wiley STM / Editor Buyya, Srirama: Fog and Edge Computing: Principles and Paradigms, Chapter 1 / Internet of Things (IoT) and New Computing Paradigms 2 tens of megabytes' data per second for the information of its route, speeds, car operating condition, driver's condition, surrounding environment, weather etc. Further, a selfdriving vehicle can generate gigabytes of data per second due to the need for real-time video streaming. Therefore, fully relying on the distant cloud to manage the things becomes impractical.  Latency. Cloud faces the challenges to achieve the requirement of controlling the endto-end latency within tens of milliseconds. Specifically, industrial smart grids systems, self-driving vehicular networks, virtual and augmented reality applications, real-time financial trading applications, healthcare and eldercare applications cannot afford the causes derived from the latency of CIoT.  Uninterrupted. The long distance between cloud and the front-end IoT devices can face issues derived from the unstable and intermittent network connectivity. For example, a CIoT-based connected vehicle will be unable to function properly due to the disconnection occurred at the intermediate node betwee...

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Authenticating query results in edge computing

Abstract: Abstract

Cited by 166 publications

References 12 publications

Verified Query Results from Hybrid Authentication Trees

Verified Query Results from Hybrid Authentication Trees

Evolution of the Distributed Computing Paradigms: a Brief Road Map

Internet of Things (IoT) and New Computing Paradigms

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