Detailed Information

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

Secure Data Retrieval for Decentralized Disruption-Tolerant Military Networks

Authors
Hur, JunbeomKang, Kyungtae
Issue Date
Feb-2014
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Access control; attribute-based encryption (ABE); disruption-tolerant network (DTN); multiauthority; secure data retrieval
Citation
IEEE-ACM TRANSACTIONS ON NETWORKING, v.22, no.1, pp 16 - 26
Pages
11
Indexed
SCI
SCIE
SCOPUS
Journal Title
IEEE-ACM TRANSACTIONS ON NETWORKING
Volume
22
Number
1
Start Page
16
End Page
26
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/23765
DOI
10.1109/TNET.2012.2210729
ISSN
1063-6692
1558-2566
Abstract
Mobile nodes in military environments such as a battlefield or a hostile region are likely to suffer from intermittent network connectivity and frequent partitions. Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow wireless devices carried by soldiers to communicate with each other and access the confidential information or command reliably by exploiting external storage nodes. Some of the most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues. However, the problem of applying CP-ABE in decentralized DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. In this paper, we propose a secure data retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to securely and efficiently manage the confidential data distributed in the disruption-tolerant military network.
Files in This Item
Go to Link
Appears in
Collections
COLLEGE OF COMPUTING > DEPARTMENT OF ARTIFICIAL INTELLIGENCE > 1. Journal Articles

qrcode

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

Related Researcher

Researcher Kang, Kyung tae photo

Kang, Kyung tae
ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)
Read more

Altmetrics

Total Views & Downloads

BROWSE