Artificial intelligent drone-based encrypted machine learning of image extraction using pretrained Convolutional Neural Network (CNN)

Murad Al Shibli, Pascual Marques, Elena Spiridon

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

1 Citation (Scopus)

Abstract

Recently Pretrained Convolutional Neural Networks (CNNs) have proven its effectiveness in image extraction and classification. This powerful feature of CNNs in image processing is facilitated by machine learning to train and classify big data. Image capturing and security transformation are considered as a central necessity of remote sensing imagery of unmanned aerial vehicles (UAVs) and drones. This paper presents a novel artificial intelligent drone-based encrypted machine learning of image classification using a pertained CNN and image encryption-decryption by utilizing singular value decomposition (SVD) and XOR-Secret-Key block cipher cryptology. Initially, pretrained convolutional neural networks (CNN) are extensively used to extract and classify image features making advantage of machine learning training tools features. Training of partial set of image data can be performed to test, classify and label the untrained image data. Pretrained CNN can classify images into object categories. Afterward, the CNN the classified image output is transformed into a digital matrix using SVD and identifies its associated eigenvalues. These eigenvalues are then converted into a binary code. The image data encryption is implemented according to suggested keys. The first part applies the exclusive OR (XOR) operation of the eigenvalues with a selected cipher key. Meanwhile, the second part implements the XOR operation of the output of part one with a randomly generated key using Poisson distribution. The last step in the encryption will be obtained by generating a non-real SVD decomposition matrix; according to which a non-readable image will be resulted. The original image-matrix can be constructed by reversing the process using the security key-cipher block (Poisson Distribution Key and Stand-alone Cipher Code). Finally, SVD image processing results are demonstrated to verify the effectiveness and security of the applied approach that can be implemented for different images.

Original languageEnglish
Title of host publicationAIVR 2018 - 2018 International Conference on Artificial Intelligence and Virtual Reality
PublisherAssociation for Computing Machinery
Pages72-82
Number of pages11
ISBN (Electronic)9781450366410
DOIs
Publication statusPublished - 23 Nov 2018
Event2018 International Conference on Artificial Intelligence and Virtual Reality, AIVR 2018 - Nagoya, Japan
Duration: 23 Nov 201825 Nov 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2018 International Conference on Artificial Intelligence and Virtual Reality, AIVR 2018
Country/TerritoryJapan
CityNagoya
Period23/11/1825/11/18

Keywords

  • Artificial intelligent
  • CNN
  • Cryptology
  • Drone
  • Image extraction
  • Machine learning
  • Poisson Distribution
  • Pretrained convolutional neural networks
  • SVD
  • UAV
  • XOR

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