Design on Novel Door Lock Using Minimizing Physical Exposure and Fingerprint Recognition Technology

Seungdo Jeong - Department of Smart Information and Telecommunication Engineering, Sangmyung University, Cheonan, Chungnam, 31066, Republic of Korea

Citation Format:



Digital door locks are widely used not only in general homes such as houses and apartments, but also in spaces where external intrusion must be prevented based on high security and convenience. Recently, smart door locks with additional technologies such as fingerprint recognition and Bluetooth communication have also been developed, and the door lock market is on the rise. Digital door locks are more convenient to use compared to the existing key-type door locks. However, there are often cases of exploiting security vulnerabilities such as exploiting and invading the user's trace remaining on the door lock. This paper proposes a door lock with a structure that can complement the shape of the current door lock exposed to the outside and minimize the user's fingerprint trace. In addition, a method of reinforcing security is applied using fingerprint recognition through image processing and a random pattern number arrangement. An experiment was conducted to confirm whether the door lock of this type was actually usable, and the recognition of partially damaged fingerprints was also confirmed. It was shown that the door lock structure proposed in this paper can maximize security by combining fingerprint recognition technology and random pattern numbering while minimizing external exposure.


Door lock; fingerprints recognition; random number placement; image processing; convolutional neural network.

Full Text:



S. H. Lim, “The market trend of door lock in US,” Kotra, Accessed on August 14, 2020. [Online]. Available:

M. S. Kim, “The market trend of digital door lock in Thailand,” Kotra, c2020. Accessed on June 11, 2020. [Online]. Available:

J. S. Seok, “Smartphone becomes the key! The popularity of smart door lock in Japan,” Kotra, 2019. Accessed on August 1, 2019. [Online]. Available:

M. Pavelić, Z. Lončarić, M. Vuković and M. Kušek, "Internet of Things Cyber Security: Smart Door Lock System," International Conference on Smart Systems and Technologies (SST), 2018, pp. 227-232, doi: 10.1109/SST.2018.8564647.

Y. J. Bae, “Thief stealing money by finding a password with a 'fire detector hidden camera'”, CHANNEL A, Accessed on July 17, 2019. [Online]. Available:

C. H. Jeon, A man in his 30s who invade an empty house eight times after seeing the fingerprints on the door lock was arrested., Yonhap News Agency, viewed at January 21, 2019. [Online]. Available:

R. L. Jorda et al., "Comparative Evaluation of NFC Tags for the NFC-Controlled Door Lock with Automated Circuit Breaker," IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), 2018, pp. 1-6, doi: 10.1109/HNICEM.2018.8666375.

V. J. Govindraj, P. V. Yashwanth, S. V. Bhat and T. K. Ramesh, "Smart Door Using Biometric NFC Band and OTP Based Methods," 2020 International Conference for Emerging Technology (INCET), 2020, pp. 1-4, doi: 10.1109/INCET49848.2020.9153970.

M. S. Hadis, E. Palantei, A. A. Ilham and A. Hendra, "Design of smart lock system for doors with special features using bluetooth technology," International Conference on Information and Communications Technology (ICOIACT), 2018, pp. 396-400, doi: 10.1109/ICOIACT.2018.8350767.

Paul, Piash, et al. "Smart Door Lock Using Fingerprint Sensor." BRAC University, pp. 1-13, 2019.

J. Baidya, T. Saha, R. Moyashir and R. Palit, "Design and implementation of a fingerprint based lock system for shared access," IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2017, pp. 1-6, doi: 10.1109/CCWC.2017.7868448.

M. Waseem, S. A. Khowaja, R. K. Ayyasamy and F. Bashir, "Face Recognition for Smart Door Lock System using Hierarchical Network," International Conference on Computational Intelligence (ICCI), 2020, pp. 51-56, doi: 10.1109/ICCI51257.2020.9247836.

Zhu, Zhiguo, and Yao Cheng. "Application of attitude tracking algorithm for face recognition based on OpenCV in the intelligent door lock." Computer Communications, vol. 154, pp. 390-397, 2020.

Aiswarya, I. P. "Real Time Smart Door Lock System Using Image Detection and Voice Recognition," International Research Journal of Modernization in Engineering Technology and Science, vol.2, pp. 393-407, 2020.

Patil, Karthik A., et al. "Smart door locking system using IoT." International Research Journal on EngTechnol (IRJET), pp. 3090-3094, 2020.

Stojkoska, Biljana L. Risteska, and Kire V. Trivodaliev. "A review of Internet of Things for smart home: Challenges and solutions." Journal of cleaner production, vol.140, pp. 1454-1464, 2017.

Sovacool, Benjamin K., and Dylan D. Furszyfer Del Rio. "Smart home technologies in Europe: A critical review of concepts, benefits, risks and policies." Renewable and sustainable energy reviews, vol.120, 2020.

Hassan, Wan Haslina. "Current research on Internet of Things (IoT) security: A survey." Computer networks, vol.148, 2019, pp. 283-294.

Khan, Minhaj Ahmad, and Khaled Salah. "IoT security: Review, blockchain solutions, and open challenges." Future generation computer systems, vol.82, pp. 395-411, 2018.

Amanullah, Mohamed Ahzam, et al. "Deep learning and big data technologies for IoT security." Computer Communications, vol.151, pp. 495-517, 2020.

Belhadjamor, M., et al. "Anti-fingerprint properties of engineering surfaces: a review." Surface Engineering, vol.34, no.2, pp. 85-120, 2018.

Forchelet, Sandra, and Andy Bécue. "Impact of anti-fingerprint coatings on the detection of fingermarks." Journal of Forensic Identification, vol.68, no.3, pp. 348-368, 2018.

Schulz, Marc-André, et al. "A cognitive fingerprint in human random number generation." Scientific reports, vol.11, no.1, pp. 1-7, 2021.

Alsmirat, Mohammad A., et al. "Impact of digital fingerprint image quality on the fingerprint recognition accuracy." Multimedia Tools and Applications, vol.78, no.3, pp. 3649-3688, 2019.

Hindi, Amjad, Majed Omar Dwairi, and Ziad Alqadi. "Analysis of procedures used to build an optimal fingerprint recognition system." International Journal of Computer Science and Mobile Computing, vol.9, no.2, pp.21-37, 2020.

Liu, Feng, et al. "Robust and high-security fingerprint recognition system using optical coherence tomography." Neurocomputing, vol.402, pp. 14-28, 2020.

Minaee, Shervin, Elham Azimi, and Amirali Abdolrashidi. "Fingernet: Pushing the limits of fingerprint recognition using convolutional neural network." arXiv preprint arXiv:1907.12956, 2019.

Tereikovskyi, I. A., et al. "The procedure for the determination of structural parameters of a convolutional neural network to fingerprint recognition." Journal of Theoretical and Applied Information Technology, vol.97, no.8, pp. 2381-2392, 2019.

I. S. Yahaya, R.-G. Ariel, P. Vasile, J. Anne, Sokoto Coventry Fingerprint Dataset, TarXiv preprint arXiv:1807.10609, July. 2018.

Papi, S., Ferrara, M., Maltoni, D., & Anthonioz, A, On the generation of synthetic fingerprint alterations, 2016 International Conference of the Biometrics Special Interest Group (BIOSIG), IEEE, pp.1-6, September 2016.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

JOIV : International Journal on Informatics Visualization
ISSN 2549-9610  (print) | 2549-9904 (online)
Organized by Department of Information Technology - Politeknik Negeri Padang, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
W :
E :,,

View JOIV Stats

Creative Commons License is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.