Abstract
Facial recognition is a wide area of a computer vision which is mostly used for security purpose. The main motive of the face recognition system is to authentic a person from a given training database. The face-based biometric system and surveillance cameras are deployed everywhere, for that need a strong face recognition system. The recognition system needs a large number of training samples that need to store in any storage center but when the face data is collected and stored, that time hackers can access and manipulate that data. So, a platform is presented that is secure and tamper-proof from these data breaches as well as hacks and is not compromising with data availability, by using blockchain to store face images. The absolute infeasibility of editing a historical record in a blockchain makes it tamper-proof (immutable) ensuring security. The storage of data on multiple computers provides accessibility. For face recognition, VGGFace deep neural network is used for automatic extraction of features and logistic regression for classification. \(\ldots \)
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Acknowledgements
The work was supported by Visvesvaraya PhD scheme, Govt of India.
Funding
This study was funded by the Ministry of Electronics and Information Technology (India) (Grant No.: MLA/MUM/GA/10(37)B).
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Shankar, S., Madarkar, J., Sharma, P. (2020). Securing Face Recognition System Using Blockchain Technology. In: Bhattacharjee, A., Borgohain, S., Soni, B., Verma, G., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1241. Springer, Singapore. https://doi.org/10.1007/978-981-15-6318-8_37
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