Date of Award
2016
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Committee Chair
Sun-il Kim
Committee Member
Letha Etzkorn
Committee Member
David Coe
Subject(s)
Information storage and retrieval systems, Parallel processing (Electronic computers), Computer algorithms, Storage area networks (Computer networks)
Abstract
In this paper, we describe a secure distributed storage model to be used especially with untrusted devices, most notably cloud storage devices. The model does so through a peer-to-peer overlay and storage protocol designed to run on existing networked systems. We utilize a structured overlay that is organized in a layered, hierarchical manner based on the underlying network structure. These layers are used as storage sites for pieces of data near the layer at which that data is needed. This data is generated and distributed via a technique called an information dispersal algorithm (IDA) which utilizes an erasure code such as Cauchy Reed-Solomon (RS). Through the use of this IDA, the data pieces are organized across neighboring layers to maximize locality and prevent a compromise within one layer from compromising the data of that layer. Specifically, for a single datum to become compromised, a minimum of two layers would have to become compromised. As a result, security, survivability, and availability of the data is improved compared to other distributed storage systems. We present significant background in this area followed by an analysis of similar distributed storage systems. Then, an overview of our proposed model is given along with an in-depth analysis, including both experimental results and theoretical analysis. The recorded overhead (encoding/decoding times and associated data sizes) shows that such a scheme can be utilized with little increase in overall latency. Making the proposed model an ideal choice for any distributed storage needs.
Recommended Citation
Johnston, Reece G., "Secure storage via information dispersal across network overlays" (2016). Theses. 172.
https://louis.uah.edu/uah-theses/172
