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Modern advancement of different technologies led to the increasing computational power of each individual component of digital computers that threatens to crack many secure classical algorithms as they are based on mathematical assumption. Thus like authenticated users, hackers or intruders are also able to crack security system. So, researchers and scientists are moving to new directions as well as merging different types of algorithms. Different GPS-enabled devices like smartphone, PDA, etc. are easily accessible which also supports many different applications that extract patterns like iris, fingerprint, etc. Biometric features can be used along with location of intended receiver to develop a cryptographic algorithm. Different smartphone apps provide both locations and can extract the biometric features by which people can form new key. The focus of this paper is to examine that merging of two approaches is advantageous as it provides more security to data.
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Raper, J., Gartner, G., Karimi, H., & Rizos, C. (2007). Applications of location based services: A selected review. Journal of Location Based Services. https://doi.org/10.1080/17489720701862184.
Kealy, A., Winter, S., & Retscher, G. (2007). Intelligent location models for next generation location-based services. Journal of Location Based Services, 1(4). https://doi.org/10.1080/17489720801905313.
Barni, M., Droandi, G., & Lazzeretti, R. (2015, September). Privacy protection in biometric-based recognition systems. IEEE Signal Processing Magazine, 6676. https://doi.org/10.1109/MSP.2015.2438131.
Chiou, S. Y. (2013). Secure method for biometric-based recognition with integrated cryptographic functions. BioMed Research International. https://doi.org/10.1155/2013/623815.
Chang, Y., Zhang, W., & Chen, T. (2004). Biometrics-based cryptographic key generation. In International Conference on Multimedia and Expo (ICME), 22032206. https://doi.org/10.1109/ICME.2004.1394707.
Jagadeesan, A., Duraiswamy, K. (2010). Secured cryptographic key generation from multimodal biometrics: Feature level fusion of fingerprint and Iris. (IJCSIS) International Journal of Computer Science and Information Security, 7(2), 028037. http://arxiv.org/abs/1003.1458.
Goh, A., & Ngo, D. C. L. (2003). Computation of cryptographic keys from face bio-metrics. Communications and Multimedia Security, 2828, 113. https://doi.org/10.1007/978-3-540-45184-61.
Raghavendra, R., & Busch, C. (2014). Presentation attack detection algorithm for face and iris biometrics. In European Signal Processing Conference, EUSIPCO, pp. 1387–1391.
Ellul, C., Gupta, S., Haklay, M. M., & Bryson, K. (2013). A platform for location based app development for citizen science and community mapping. In Progress in Location-Based Services. Springer, Heidelberg, pp. 71–90. https://doi.org/10.1007/978-3-642-34203-55.
Pradeep, J., Srinivasan, E., & Himavathi, S. (2011). Diagonal based feature extraction for handwritten alphabets recognition system using neural network. International Journal of Computer Science and Information Technology (IJCSIT), 3(1), 2738. https://doi.org/10.5121/ijcsit.2011.3103. CrossRef
Shrivastava, A., & Srivastava, D. K. (2014). Fingerprint identification using feature extraction: A survey. In Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014. https://doi.org/10.1109/IC3I.2014.7019653.
- A Cryptographic Algorithm Using Location-Based Service and Biometrics
- Springer Singapore