Abstract
Digital Twin is the mirror image of any living or non-living objects. Digital Twin and Cyber-physical system (CPS) provides a new era for industries especially in the healthcare sector that keeps track of health data of individuals to provide on-demand, fast and efficient services to the users. In the suggested system, various health parameters of the patients are collected through different health instruments, wearable devices that communicate data to the primary database; used for analysis purposes for better diagnosis and training for automated systems. The primary database in a physical object and parallelly maintain virtual object/digital twin of the same in order of analyzing, summarize and mine data for diagnosis, monitoring the patient in real-time. The e-health cloud data need to be protected from unauthorized access by biometric authentication using iris biometric trait. The proposed paper suggested two phases EfficientNet Convolution Neural Network-based framework for identifying the real or spoofed user sample. The proposed system is trained using EfficientNet Convolution Neural Network on different datasets of spoofed and actual iris biometric samples to discriminate the original and spoofed one.
Similar content being viewed by others
References
Abhishek K, Yogi A (2015) A minutiae count based method for fake fingerprint detection. Procedia Comput Sci 58:447–452
Agarwal R, Jalal AS, Arya KV (2020) Enhanced binary hexagonal extrema pattern (EBH X EP) descriptor for iris liveness detection. Wireless Pers Commun 115(3):2627–2643
Agrawal R, Jalal AS, Arya KV (2019) Fake fingerprint liveness detection based on micro and macro features. Int J Biom 11(2):177–206
Anjos A, Chakka MM, Marcel S (2013) Motion-based counter-measures to photo attacks in face recognition. IET Biom 3(3):147–158
Bahga A, Madisetti VK (2013) A cloud-based approach for interoperable electronic health records (EHRs). IEEE J Biomed Health Inform 17(5):894–906
Brettel M, Friederichsen N, Keller M, Rosenberg M (2014) How virtualization, decentralization and network building change the manufacturing landscape: an industry 40 perspective. Int J Mech Sci 8(1):37–44
Chen J, Shan S, He C, Zhao G, Pietikainen M, Chen X, Gao W (2009) WLD: a robust local image descriptor. IEEE Trans Pattern Anal Mach Intell 32(9):1705–1720
Chen R, Lin X, Ding T (2012) Liveness detection for iris recognition using multispectral images. Pattern Recogn Lett 33(12):1513–1519
Dubey RK, Goh J, Thing VL (2016) Fingerprint liveness detection from single image using low-level features and shape analysis. IEEE Trans Inf Forensics Secur 11(7):1461–1475
Framling K, Holmström J, Ala-Risku T, Karkkainen M (2003) Product agents for handling information about physical objects. Helsinki University Technology, Department Computer Science Engineering Series B TKO-B, Espoo
Galbally J, Alonso-Fernandez F, Fierrez J, Ortega-Garcia J (2012) A high performance fingerprint liveness detection method based on quality related features. Futur Gener Comput Syst 28(1):311–321
Galbally J, Ortiz-Lopez J, Fierrez J, Ortega-Garcia J (2012). Iris liveness detection based on quality related features. In: 2012 5th IAPR International Conference on Biometrics (ICB) (pp. 271–276). IEEE
Galbally J, Marcel S, Fierrez J (2013) Image quality assessment for fake biometric detection: application to iris, fingerprint, and face recognition. IEEE Trans Image Process 23(2):710–724
Glaessgen E, Stargel D (2012) The digital twin paradigm for future NASA and U.S. Air Force vehicles. In: Proceeding of the 53rd Structural Dynamics, and Materials Conference, Special Session Digit. Twin, 2012, p. 818.
Glaessgen E, Stargel D (2012) The digital twin paradigm for future NASA and U.S. air force vehicles. In: Proceeding of the 53rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference 20th AIAA/ASME/AHS adapting structure conference, 14th AIAA, Honolulu pp 1–14
Gockel B, Tudor A, Brandyberry M, Penmetsa R, Tuegel E (2012) Challenges with structural life forecasting using realistic mission profiles. In Structural Dynamics and Materials Conference. p 1812
Gragnaniello D, Poggi G, Sansone C, Verdoliva L (2015) Local contrast phase descriptor for fingerprint liveness detection. Pattern Recogn 48(4):1050–1058
Gragnaniello D, Poggi G, Sansone C, Verdoliva L (2015) An investigation of local descriptors for biometric spoofing detection. IEEE Trans Inf Forensics Secur 10(4):849–863
Grieves M (2015).Digital twin: manufacturing excellence through virtual factory replication. digital twin white paper. Available: https://research.fit.edu/media/sitespecific/researchfitedu/camid/documents/1411.0_Digital_Twin_White_Paper_Dr_Grieves.pdf. Accessed 16 Oct 2019
Grieves M, Vickers J (2017) Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. Springer, Berlin, pp 85–113
Grieves M, Vickers J (2017) Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary perspectives on complex systems. Springer, Berlin, pp 85–113
Guo L, Chen F, Chen L, Tang X (2010) The building of cloud computing environment for e-health. In: Proceeding of the IEEE International Conference E-Health Network Digital Ecosystem Technology, pp 89–92
He C, Fan X, Li Y (2013) Toward ubiquitous healthcare services with a novel effcient cloud platform. IEEE Trans Biomed Eng 60(1):230–234
Hochhalter JD et al. (2014) Coupling damage-sensing particles to the digital twin concept. NASA Langley Res. Center, Hampton, VA, USA, Technical report NASA/TM-2014-218257, L-20401, and NF1676L-18764
Kannala J, Rahtu E (2012). Bsif: binarized statistical image features. In: Proceedings of the 21st international conference on pattern recognition (ICPR2012) (pp. 1363–1366). IEEE
Latif G, Alghazo J (2021) IoT Cloud Based Rx healthcare expert system. In: Fog computing for healthcare 4.0 environments (pp. 251–265). Springer, Cham
Liu X, Jiang Y (2017) Fingerprint spoof detection using gradient cooccurrence matrix. Eng Lett 25(4):44
Määttä J, Hadid A, Pietikäinen M (2012) Face spoofing detection from single images using texture and local shape analysis. IET Biom 1(1):3–10
Matsumoto T (2002) Gummy and conductive silicone rubber fingers importance of vulnerability analysis. In International conference on the theory and application of cryptology and information security (pp. 574–575). Springer, Berlin
Nasiri S, Sadoughi F, Tadayon MH, Dehnad A (2019) Security requirements of internet of things-based healthcare system: a survey study. Acta Inform Medica 27(4):253
Nogueira RF, de Alencar Lotufo R, Machado RC (2016) Fingerprint liveness detection using convolutional neural networks. IEEE Trans Inf Forensics Secur 11(6):1206–1213
Nosaka R, Ohkawa Y, Fukui, K (2011) Feature extraction based on co-occurrence of adjacent local binary patterns. In: Pacific-rim symposium on image and video technology (pp. 82–91). Springer, Berlin
Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell 24(7):971–987
Ojansivu V, Rahtu E, Heikkila J (2008) Rotation invariant local phase quantization for blur insensitive texture analysis. In: 2008 19th International conference on pattern recognition (pp. 1–4). IEEE
Raja KB, Raghavendra R, Busch C (2015) Video presentation attack detection in visible spectrum iris recognition using magnified phase information. IEEE Trans Inf Forensics Secur 10(10):2048–2056
Reifsnider K, Majumdar P (2013) Multiphysics stimulated simulation digital twin methods for fleet management. In Proceeding of the 54thAIAA/ASME/ASCE/AHS/ASC structural dynamics, and materials conference, Boston 2013, pp 1–11
Ruiz-Albacete V, Tome-Gonzalez P, Alonso-Fernandez F, Galbally J, Fierrez J, Ortega-Garcia J (2008) Direct attacks using fake images in iris verification. In: European workshop on biometrics and identity management (pp. 181–190). Springer, Berlin
Russakovsky O, Deng J Su H, Krause J, Satheesh S, Ma S, ... & Berg A.(2015) Imagenet large scale visual recognition challenge. Int J Comput Vis, 115(3), 211-252
Selvaraj S, Sundaravaradhan S (2020) Challenges and opportunities in IoT healthcare systems: a systematic review. SN Appl Sci 2(1):139
Shafto M, Conroy M, Doyle R, Glaessgen E, Kemp C, LeMoigne J, Wang L (2010) Modeling, simulation, information technology & processing roadmap. National Aeronautics and Space Administration. Available https://www.nasa.gov/pdf/501321main_TA11-MSITP-DRAFT-Nov2010-A1.pdf. Accessed 16 Oct 2019
Stén A, Kaseva A, Virtanen T (2003) Fooling fingerprint scanners-biometric vulnerabilities of the precise biometrics 100 SC scanner. In: Proceedings of 4th Australian Information Warfare and IT Security Conference, vol. 2003, pp. 333–340
Tan M, Le QV (2019) Efficientnet: rethinking model scaling for convolutional neural networks. ar**v preprint ar**v:1905.11946
Tola E, Lepetit V, Fua P (2009) Daisy: an efficient dense descriptor applied to wide-baseline stereo. IEEE Trans Pattern Anal Mach Intell 32(5):815–830
Tuegel E (2012) The airframe digital twin: some challenges to realization. In: Proceeding of the 53rd structures, structural dynamics, and materials conference, p. 1812.
Tuegel EJ, Ingraffea AR, Eason EG, Spottswood SM (2011) Reengineering aircraft structural life prediction using a digital twin. Int J Aerosp Eng. https://doi.org/10.1155/2011/154798
Van Gorp P, Comuzzi M (2014) Lifelong personal health data and application software via virtual machines in the cloud. IEEE J Biomed Health Inform 18(1):36–45
Yadav D, Kohli N, Doyle JS, Singh R, Vatsa M, Bowyer KW (2014) Unraveling the effect of textured contact lenses on iris recognition. IEEE Trans Inf Forensics Secur 9(5):851–862
Yao Q, Han X, Ma X-K, Xue Y-F, Chen Y-J, Li J-S (2014) Cloud-based hospital information system as a service for grassroots healthcare institutions. J Healthcare Syst 38(9):104
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Garg, H., Sharma, B., Shekhar, S. et al. Spoofing detection system for e-health digital twin using EfficientNet Convolution Neural Network. Multimed Tools Appl 81, 26873–26888 (2022). https://doi.org/10.1007/s11042-021-11578-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-021-11578-5