Cited by 140Blockchain Technology Applications and SecurityAdvanced Steganography and Watermarking TechniquesBlockchain Technology in Education and Learning

A secured distributed detection system based on IPFS and blockchain for industrial image and video data security

Kumar, Randhir, Tripathi, Rakesh, Marchang, Ningrinla, Srivastava, Gautam, Gadekallu, Thippa Reddy, Xiong, Neal N.·2021·Journal of Parallel and Distributed Computing

Integrity signals

Registry

Crossref · 10.1016/j.jpdc.2021.02.022

Cites

59 of 59 references verified0 citation errors · 0 not checkable

Statistics

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Cites

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2 of the 61 references couldn’t be matched to a known paper.

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Authors
Kumar, R., Tripathi, R., Marchang, N., Srivastava, G., Gadekallu, T. R., & Xiong, N. N.
Affiliations
  • National Institute of Technology Raipur (IN)
  • North Eastern Regional Institute of Science and Technology (IN)
  • China Medical University (TW)
  • Vellore Institute of Technology University (IN)
Corresponding author
Srivastava, Gautam
Venue
Journal of Parallel and Distributed Computing
Publisher
Elsevier BV
Published
2021-06
Volume
152
Pages
128-143
ISSN
0743-7315 (ISSN-L)
OpenAlex
W3135191333
Cited by
140
References
61
Citations by year
2026: 8 · 2025: 24 · 2024: 28 · 2023: 36 · 2022: 30 · 2021: 14
FWCI
22.45
Type
journal article
Language
en
Open access
closed
Locations
Journal of Parallel and Distributed Computing (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
copyright infringement detection, image forgery detection, video tampering detection, IPFS, blockchain, perceptual hashing, multimedia security, distributed detection

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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