Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Information Security and Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Information Security and Applications, 59, 2021 DOI: 10.1016/j.jisa.2021.102810
Accepted author manuscript, 1.53 MB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Secure facial recognition in the encrypted domain using a local ternary pattern approach
AU - Khan, F.A.
AU - Bouridane, A.
AU - Boussakta, S.
AU - Jiang, R.
AU - Almaadeed, S.
N1 - This is the author’s version of a work that was accepted for publication in Journal of Information Security and Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Information Security and Applications, 59, 2021 DOI: 10.1016/j.jisa.2021.102810
PY - 2021/6/30
Y1 - 2021/6/30
N2 - Automatic facial recognition is fast becoming a reliable method for identifying individuals. Due to its reliability and unobtrusive nature facial recognition has been widely deployed in law enforcement and civilian application. Recent implementations of facial recognition systems on public cloud computing infrastructures have raised strong concerns regarding an individual's privacy. In this paper, we propose and implement a novel approach for facial recognition in the encrypted domain. This allows for facial recognition to be performed without revealing the actual image unnecessarily as the features stay encrypted at all times. Our proposed system exploits the homomorphic properties of the Paillier cryptosystem and performs Euclidean distance calculations using encrypted data. We propose to represent the images using a radial Local Ternary Pattern approach where a higher than proposed radius is used to extract the image features. Our proposed system has been evaluated using two publicly available datasets and has also been compared against the previously used eigenface approach in the encrypted domain and the obtained results justify the feasibility of the proposed system. © 2021 Elsevier Ltd
AB - Automatic facial recognition is fast becoming a reliable method for identifying individuals. Due to its reliability and unobtrusive nature facial recognition has been widely deployed in law enforcement and civilian application. Recent implementations of facial recognition systems on public cloud computing infrastructures have raised strong concerns regarding an individual's privacy. In this paper, we propose and implement a novel approach for facial recognition in the encrypted domain. This allows for facial recognition to be performed without revealing the actual image unnecessarily as the features stay encrypted at all times. Our proposed system exploits the homomorphic properties of the Paillier cryptosystem and performs Euclidean distance calculations using encrypted data. We propose to represent the images using a radial Local Ternary Pattern approach where a higher than proposed radius is used to extract the image features. Our proposed system has been evaluated using two publicly available datasets and has also been compared against the previously used eigenface approach in the encrypted domain and the obtained results justify the feasibility of the proposed system. © 2021 Elsevier Ltd
KW - Biometric identification
KW - Cloud computing
KW - Homomorphic encryption
KW - Paillier cryptosystem
KW - Public key distance calculation
KW - Cryptography
KW - Eigenface approach
KW - Euclidean distance
KW - Facial recognition
KW - Facial recognition systems
KW - Homomorphic property
KW - Local ternary patterns
KW - Reliable methods
KW - Face recognition
U2 - 10.1016/j.jisa.2021.102810
DO - 10.1016/j.jisa.2021.102810
M3 - Journal article
VL - 59
JO - Journal of Information Security and Applications
JF - Journal of Information Security and Applications
SN - 2214-2126
ER -