Research article Special Issues

Biometrics-based Internet of Things and Big data design framework

  • Received: 13 January 2021 Accepted: 22 April 2021 Published: 24 May 2021
  • Application Specific Internet of Things (ASIoTs) has recently been proposed to address specific requirements for IoT. The objective of this paper is to serve as a framework for the design of ASIoTs using biometrics as the application. This paper provides comprehensive discussions for an ASIoT architecture considering the requirements for biometrics-based security, multimedia content and Big data applications. A comprehensive architecture for Biometrics-based IoT (BiometricIoT) and Big data applications needs to address three challenges: 1) IoT devices are hardware-constrained and cannot afford resource-demanding cryptographic protocols; 2) Biometrics devices introduce multimedia data content due to different biometric traits; and 3) The rapid growth of biometrics-based IoT devices and content creates large amounts of data for computational processing. The proposed BiometricIoT architecture consists of seven layers which have been designed to handle the challenges for biometrics applications and decision making. The latter part of the paper gives discussions for design factors for the BiometricIoT from four perspectives: 1) parallel divide-and-conquer (D&C) computation; 2) computational complexity; 3) device security; and 4) algorithm efficacies. Experimental results are given to validate the effectiveness of the D&C approach. The paper motivates the further research towards the research and development of ASIoTs for biometrics applications.

    Citation: Kenneth Li-minn Ang, Kah Phooi Seng. Biometrics-based Internet of Things and Big data design framework[J]. Mathematical Biosciences and Engineering, 2021, 18(4): 4461-4476. doi: 10.3934/mbe.2021226

    Related Papers:

  • Application Specific Internet of Things (ASIoTs) has recently been proposed to address specific requirements for IoT. The objective of this paper is to serve as a framework for the design of ASIoTs using biometrics as the application. This paper provides comprehensive discussions for an ASIoT architecture considering the requirements for biometrics-based security, multimedia content and Big data applications. A comprehensive architecture for Biometrics-based IoT (BiometricIoT) and Big data applications needs to address three challenges: 1) IoT devices are hardware-constrained and cannot afford resource-demanding cryptographic protocols; 2) Biometrics devices introduce multimedia data content due to different biometric traits; and 3) The rapid growth of biometrics-based IoT devices and content creates large amounts of data for computational processing. The proposed BiometricIoT architecture consists of seven layers which have been designed to handle the challenges for biometrics applications and decision making. The latter part of the paper gives discussions for design factors for the BiometricIoT from four perspectives: 1) parallel divide-and-conquer (D&C) computation; 2) computational complexity; 3) device security; and 4) algorithm efficacies. Experimental results are given to validate the effectiveness of the D&C approach. The paper motivates the further research towards the research and development of ASIoTs for biometrics applications.



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    [1] Planet Biometrics, Gartner: Internet of Things will redefine identity management. Available from: http://www.planetbiometrics.com/article-details/i/2534/.
    [2] Business insider, Facebook Making Big Push Into Smart Home, IoT Device Market. Available from: https://mobileidworld.com/facebook-smart-home-iot-device-market-008252/.
    [3] Find biometrics, Arrow Electronics Signs On for IoT-Focused Distribution Agreement with NEXT. Available from: https://findbiometrics.com/arrow-electronic-next-408221.
    [4] Find biometrics, Baidu's Apollo Smart Car Program Depends on Face Biometrics. Available from: https://findbiometrics.com/baidus-apollo-smart-car-program-depends-face-biometrics/.
    [5] O. G. Morchon, R. Rietman, S. Sharma, L. Tolhuizen, J. T. Arce, A comprehensive and lightweight security architecture to secure the IoT throughout the lifecycle of a device based on HIMMO, in International Symposium on Algorithms and Experiments for Wireless Sensor Networks, (2015), 112-128.
    [6] T. Guneysu, T. Oder, Towards lightweight identity-based encryption for the post-quantum-secure Internet of Things, in 2017 18th International Symposium on Quality Electronic Design (ISQED), (2017), 319-324.
    [7] S. Dargan, M. Kumar, A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities, Exp. Syst. Appl., 143 (2020), 113114.
    [8] N. Yusuf, K. A. Marafa, K. L. Shehu, H. Mamman, M. Maidawa, A survey of biometric approaches of authentication, Int. J. Adv. Comput. Res., 10 (2020), 96-104. doi: 10.19101/IJACR.2019.940152
    [9] J. K. P. Seng, K. L. M. Ang, Multimodal emotion and sentiment modeling from unstructured Big data: Challenges, architecture, & techniques, IEEE Access, 7 (2019), 90982-90998.
    [10] S. A. Alvi, B. Afzal, G. A. Shah, L. Atzori, W. Mahmood, Internet of multimedia things: Vision and challenges, Ad Hoc Networks, 33 (2015), 87-111. doi: 10.1016/j.adhoc.2015.04.006
    [11] K. P. Seng, L. M. Ang, A big data layered architecture and functional units for the multimedia Internet of Things, IEEE Trans. Multi-Scale Comput. Syst., 4 (2018), 500-512. doi: 10.1109/TMSCS.2018.2886843
    [12] A. Nauman, Y. A. Qadri, M. Amjad, Y. B. Zikria, M. K. Afzal, S. W. Kim, Multimedia Internet of Things: A comprehensive survey, IEEE Access, 8 (2020), 8202-8250. doi: 10.1109/ACCESS.2020.2964280
    [13] L. M. Ang, K. P. Seng, L. W. Chew, L. S. Yeong, W. C. Chia, Wireless multimedia sensor networks on reconfigurable hardware, Springer, Heidelberg, 2013.
    [14] J. Qiu, Z. Tian, C. Du, Q. Zuo, S. Su, B. Fang, A survey on access control in the age of Internet of Things, IEEE Int. Things J., 7 (2020), 4682V4696.
    [15] G. K. Ijemaru, K. L. M. Ang, J. K. P. Seng, Mobile collectors for opportunistic Internet of Things in smart city environment with wireless power transfer, Electronics, 10 (2021), 697.
    [16] M. Stoyanova, Y. Nikoloudakis, S. Panagiotakis, E. Pallis, E. K. Markakis, A survey on the Internet of Things (IoT) forensics: challenges, approaches, and open issues, IEEE Commun. Surv. Tutorials, 22 (2020), 1191-1221.
    [17] D. Miorandi, S. Sicari, F. de Pellegrini, I. Chlamtac, Internet of Things: vision, applications and research challenges, Ad Hoc Networks, 10 (2012), 1497-1516.
    [18] M. S. Hossain, G. Muhammad, S. M. M. Rahman, W. Abdul, A. Alelaiwi, A. Alamri, Toward end-to-end biometrics-based security for IoT infrastructure, IEEE Wireless Commun., 23 (2016), 44-51. doi: 10.1109/MWC.2016.7721741
    [19] O. Said, M. Masud, Towards Internet of Things: survey and future vision, Int. J. Comput. Networks, 5 (2013), 1-17.
    [20] K. L. M. Ang, J. K. P. Seng, Application specific Internet of Things (ASIoTs): Taxonomy, applications, use case and future directions, IEEE Access, 7 (2019), 56577-56590.
    [21] A. Mosenia, N. K. Jha, A comprehensive study of security of Internet-of-Things, IEEE Trans. Emerging Top. Comput., 5 (2017), 586-602. doi: 10.1109/TETC.2016.2606384
    [22] L. Atzori, A. Iera, G. Morabito, The Internet-of-Things: a survey, Comput. Networks, 54 (2010), 2787-2805.
    [23] J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami, Internet of Things (IoT): a vision, architectural elements, and future directions, Future Gener. Comput. Syst., 29 (2013), 1645-1660.
    [24] A. Zankl, H. Seuschek, G. Irazoqui, B. Gulmezoglu, Side-channel attacks in the Internet of Things: threats and challenges, in Research Anthology on Artificial Intelligence Applications in Security, (2021), 325-357.
    [25] L. A. Tawalbeh, T. F. Somani, More secure Internet of Things using robust encryption algorithms against side channel attacks, in 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), IEEE, (2016), 978-983.
    [26] A. Mukherjee, Physical-layer security in the Internet of Things: sensing and communication confidentiality under resource constraints, Proc. IEEE, 103 (2015), 1747-1761. doi: 10.1109/JPROC.2015.2466548
    [27] N. Namvar, W. Saad, N. Bahadori, B. Kelley, Jamming in the Internet of Things: a game-theoretic perspective, in 2016 IEEE Global Communications Conference (GLOBECOM), (2016), 1-6.
    [28] W. Xu, K. Ma, W. Trappe, Y. Zhang, Jamming sensor networks: attack and defense strategies, IEEE Network, 20 (2006), 41-47. doi: 10.1109/MNET.2006.1637931
    [29] I. E. Bagci, U. Roedig, I. Martinovic, M. Schulz, M. Hollick, IoT: using channel state information for tamper detection in the Internet of Things, in Proceedings of Annual Computer Security Applications Conference, (2015), 131-140.
    [30] C. Hota, R. K. Shrivastava, S. shipra, Tamper-resistant code using optimal ROP gadgets for IoT devices, in 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), IEEE, (2017), 570-575.
    [31] IEEE Computer Society LAN MAN Standards Committee, Wireless medium access control (MAC) and physical layer (PHY) specifications for low-rate wireless personal area networks (LR-WPANs), ANSI/IEEE Std., 802 (1999).
    [32] J. Granjal, E. Monteiro, J. S. Silva, Security for the Internet of Things: a survey of existing protocols and open research issues, IEEE Commun. Surv. Tutorials, 17 (2015), 1294-1312. doi: 10.1109/COMST.2015.2388550
    [33] Y. Xiao, H. Chen, B. Sun, R. Wang, S. Sethi, MAC security and security overhead analysis in the IEEE 802.15.4 wireless sensor networks, EURASIP J. Wireless Commun. Networking, 2006 (2006), 1-12.
    [34] S. Radosavac, A. A. Cardenas, J. S. Baras, G. V. Moustakides, Detecting IEEE 802.11 MAC layer misbehavior in ad hoc networks: robust strategies against individual and colluding attackers, J. Comput. Secur., 15 (2007), 103-128. doi: 10.3233/JCS-2007-15105
    [35] S. Saleem, S. Ullah, K. S. Kwak, A study of IEEE 802.15.4 security framework for wireless body area networks, Sensors, 11 (2011), 1383-1395. doi: 10.3390/s110201383
    [36] A. Le., J. Loo, A. Lasebae, A. Vinel, Y. Chen, M. Chai, The impact of rank attack on network topology of routing protocol for low-power and lossy networks, IEEE Sensors J., 13 (2013), 3685-3692. doi: 10.1109/JSEN.2013.2266399
    [37] P. Sethi, S. R. Sarangi, Internet of Things: architectures, protocols, and applications, J. Electr. Comput. Eng., 2017 (2017), 9324035.
    [38] C. Karlof, D. Wagner, Secure routing in wireless sensor networks: attacks and countermeasures, Ad Hoc Networks, 1 (2003), 293-315. doi: 10.1016/S1570-8705(03)00008-8
    [39] J. Zhou, Z. Cao, X. Dong, A. V. Vasilakos, Security and privacy for cloud-based IoT: challenges, countermeasures, and future directions, IEEE Comms. Mag., 55 (2017), 26-33.
    [40] C. Bormann, Z. Shelby, K. Hartke, B. Frank, Constrained application protocol (CoAP), Int. Eng. Task Force, 2014.
    [41] T. Kothmayr, C. Schmitt, W. Hu, M. Brunig, G. Carle, DTLS based security and two-way authentication for the Internet of Things, Ad Hoc Networks, 11 (2013), 2710-2723. doi: 10.1016/j.adhoc.2013.05.003
    [42] A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, M. Ayyash, Internet of Things: a survey on enabling technologies, protocols, and applications, IEEE Commun. Surv. Tutorials, 17 (2015), 2347-2376.
    [43] I. Jolliffe, Principal component analysis, Princ. Compon. Anal., (2002), 167-198.
    [44] A. J. Izenman, Linear discriminant analysis, in Modern Multivariate Statistical Techniques. Springer, (2013), 237-280.
    [45] J. K.P. Seng, K. L. M. Ang, Big feature data analytics: split and combine linear discriminant analysis (SC-LDA) for integration towards decision making analytics, IEEE Access, 5 (2017), 14056-14065. doi: 10.1109/ACCESS.2017.2726543
    [46] A. Sharma, K. K. Paliwal, S. Imoto, S. Miyano, Principal component analysis using QR decomposition, Int. J. Mach. Learn. Cybern., 4 (2013), 679-683. doi: 10.1007/s13042-012-0131-7
    [47] D. Chu, L. Z. Liao, M. K. P. Ng, X. Wang, Incremental linear discriminant analysis: A fast algorithm and comparisons, IEEE Trans. Neural Network Learn. Syst., 26 (2015), 2716-2735. doi: 10.1109/TNNLS.2015.2391201
    [48] G. W. Stewart, Matrix Algorithms: Volume 1: Basic Decompositions, in Society for Industrial and Applied mathematics, 1998.
    [49] B. S. Adiga, M. A. Fajan, R. Shastry, V. L. Shivraj, P. Balamuralidhar, Lightweight IBE scheme for wireless sensor nodes, in 2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), IEEE, (2013), 1-6.
    [50] S. Sankaran, Lightweight security framework for IoTs using identity-based cryptography, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, (2016), 880-886.
    [51] X. Xiong, D. S. Wong, X. Deng, Tinypairing: A fast and lightweight pairing-based cryptographic library for wireless sensor networks, in 2010 IEEE Wireless Communication and Networking Conference, IEEE, (2010), 1-6.
    [52] D. Boneh, M. Franklin, Identity-based encryption from the Weil pairing, in Annual International Cryptology Conference, (2001), 213-229.
    [53] K. Hoeper, G. Gong, Key revocation for identity-based schemes in mobile ad hoc networks, in International Conference on Ad-Hoc Networks and Wireless, (2006), 224-237.
    [54] R. J. Hwang, Y. Z. Huang, Secure data collection schemes for wireless sensor networks, in 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA), IEEE, (2017), 553-558.
    [55] P. N. Belhumeour, J. P. Hespanha, D. J. Kriegman, Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection, in European Conference on Computer Vision, (1996), 43-58.
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