Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Improving Security and Reliability in Merkle Tree-Based Online Data Authentication with Leakage Resilience

Authors
Koo, DongyoungShin, YoungjooYun, JoobeomHur, Junbeom
Issue Date
Dec-2018
Publisher
MDPI
Keywords
data outsourcing; integrity; online authentication; Merkle (hash) tree; data loss; information leakage; reliability
Citation
APPLIED SCIENCES-BASEL, v.8, no.12
Indexed
SCIE
SCOPUS
Journal Title
APPLIED SCIENCES-BASEL
Volume
8
Number
12
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/71346
DOI
10.3390/app8122532
ISSN
2076-3417
Abstract
With the successful proliferation of data outsourcing services, security and privacy issues have drawn significant attention. Data authentication in particular plays an essential role in the storage of outsourced digital content and keeping it safe from modifications by inside or outside adversaries. In this paper, we focus on online data authentication using a Merkle (hash) tree to guarantee data integrity. By conducting in-depth diagnostics of the side channels of the Merkle tree-based approach, we explore novel solutions to improve the security and reliability of the maintenance of outsourced data. Based on a thorough review of previous solutions, we present a new method of inserting auxiliary random sources into the integrity verification proof on the prover side. This prevents the exposure of partial information within the tree structure and consequently releases restrictions on the number of verification execution, while maintaining desirable security and reliability of authentication for the long run. Based on a rigorous proof, we show that the proposed scheme maintains consistent reliability without being affected by continuous information leakage caused by repetitions of the authentication process. In addition, experimental results comparing with the proposed scheme with other state-of-the-art studies demonstrate its efficiency and practicality.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE