About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
ew 23(1):

Research Article

Geo-Tagged Spoofing Detection using Jaccard Similarity

Download385 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/ew.4239,
        author={Shweta Koparde and Vanita Mane},
        title={Geo-Tagged Spoofing Detection using Jaccard Similarity},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={EW},
        year={2023},
        month={10},
        keywords={Spoofing detection, Dicerete Cosine Transform, Tanimoto similarity, Fuzzy filter},
        doi={10.4108/ew.4239}
    }
    
  • Shweta Koparde
    Vanita Mane
    Year: 2023
    Geo-Tagged Spoofing Detection using Jaccard Similarity
    EW
    EAI
    DOI: 10.4108/ew.4239
Shweta Koparde1,*, Vanita Mane1
  • 1: D.Y. Patil University
*Contact email: kopardeshweta21@gmail.com

Abstract

In recent years, position evaluation of mobile devices has developed as an essential part of social movement. Meantime, the criminals may interfere with the information of geographical position (geo-position), and they can adjust the geo-position for their convenience. Therefore, it is important to identify the authenticity of geo-position. In this paper, an instant messaging platform-based geo-tagged spoof image detection system is created using Jaccard similarity. With the help of a Fuzzy filter, the input, as well as spoofing images, are subjected to camera footprint extraction, and their corresponding outputs are fused by Dice Coefficient. Moreover, the input as well as spoofed images is subjected to geotagged process, and their corresponding geotagged input, and geotagged spoofed images are fused by Tanimoto similarity. At last, the fused images from Dice Coefficient, and Tanimoto similarity are employed for the spoof detection process, where the Jaccard similarity compares the two images using Dicerete Cosine Transform (DCT). Consequently, the spoofed images are detected, and their effectiveness is measured in terms of accuracy, False Positive Rate (FPR), and True Positive Rate (TPR), as well as the corresponding values are attained like 0.099, 0.892, and 0.896 respectively.

Keywords
Spoofing detection, Dicerete Cosine Transform, Tanimoto similarity, Fuzzy filter
Received
2023-07-17
Accepted
2023-10-12
Published
2023-10-26
Publisher
EAI
http://dx.doi.org/10.4108/ew.4239

Copyright © 2023 S. Kparde et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL