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Balancing Compression and Encryption of Satellite Imagery

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 5 (2018)

DOI
10.11591/ijece.v8i5.pp3568-3586
ISSN
2088-8708, 2088-8708
Published
2018-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources.

Collaboration network of the authors

3 authors · 3 co-authorship links · 2 across different organisations

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  • University of Diyala
  • University of Baghdad
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Balancing Compression and Encryption of Satellite Imagery</dc:title><dc:creator>Abboud, Ali J.</dc:creator><dc:creator>Albu-Rghaif, Ali N.</dc:creator><dc:creator>Jassim, Abbood Kirebut</dc:creator><dc:description>&lt;jats:p&gt;With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v8i5.pp3568-3586</dc:identifier><dc:identifier>10.11591/ijece.v8i5.pp3568-3586</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 5 (2018); 3568</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/9577/9547</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>