Skip to main content

Advance Security and Challenges with Intelligent IoT Devices

  • Conference paper
  • First Online:
Proceedings of Second International Conference on Smart Energy and Communication

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

By 2025, more than 25 billion devices are connected over Internet with high cognitive intelligence. Internet of things has major issues and threats regarding security challenges over billions of intelligent devices connecting over Internet. Internet connectivity reaches to 7G in the future. In Japan, it is already on the way and so as complexity regarding connectivity as well as security increases. Internet of things opens the doors for various sectors in advancements but cognitive devices security is become major threat with advancements in IoT. Now, devices are connected with advance and high connectivity Internet and stored over different types of clouds. So, this paper aims purely security to these smart cognitive devices with assistance of deep learning, artificial intelligence with IoT with big data assistance, and discuss the security issues with intelligent devices with different useful applications on day by day basis as well as provide proposed secured methodology for “Smart ATM” with advance applications of deep learning and natural language processing (NLP) with artificial intelligence. In this paper, apply the “Weapon Detection,” “Crime Intention Detection” and using “Edge Computing” with convolutional neural networks irrespective of the use of cloud computing with machine learning for the cognitive intelligence and fast access with high security in smart devices with IoT. This paper also proposes “Smart Laser Fencing” for the Hi-Tech security of smart devices with “Deep-fi Geo-Fencing,” and this eliminates the major security threats in various smart devices and decreases the rate of cyber-crimes majorly in e-money transactions as well as in other various domains.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. J. Holler et aI., From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence, 1st edn. (Academic Press Ltd., London, UK, 10 Apr 2014)

    Google Scholar 

  2. M.A. Feki, F. Kawsar, M. Boussard, L. Trappeniers, The Internet of Things: the next technological revolution. Computer 46(2), 24–25, February 2013 (Online)

    Google Scholar 

  3. A. Kiourt I, C. Lee, J. Volakis, Fabrication of textile antennas and circuits with 0.1 mm precision. IEEE Antennas Wirel. Propag. Lett. 99, 1–1 (2015)

    Google Scholar 

  4. A. Caragliu, C. Del Bo, P. Nijkamp, Smart cities in Europe. J. Urban Technol. 18(2), 65–82 (2011)

    Article  Google Scholar 

  5. S. Li, L. Da Xu, S. Zhao, The Internet of Things: a survey. Inf. Syst. Front. 17(2), 243–259 (2015)

    Article  Google Scholar 

  6. Z. Pang, Q. Chen, W. Han, L. Zheng, Value-centric design of the Internet-of-Things solution for food supply chain: value creation, sensor portfolio and information fusion. Inf. Syst. Front. 17(2), 289–319 (2015)

    Article  Google Scholar 

  7. L. Da Xu, W. He, S. Li, Internet of Things in industries: a survey. IEEE Trans. Ind. Informatics 10(4), 2233–2243 (2014)

    Article  Google Scholar 

  8. A. Kiourt I, C. Lee, J. Volakis, Fabrication of textile antennas and circuits with 0.1 mm precision. IEEE Antennas Wirel. Propag. Lett. 99, 1–1 (2015)

    Google Scholar 

  9. A. Weissberger, TiECon 2014 Summary-Part I: Qualcomm Keynote & loT Track Overview, IEEE Com Soc, May 2014 (Online)

    Google Scholar 

  10. D. Evans, The Internet of Everything: How More Relevant and Valuable Connections Will Change the World, Cisco Internet Business Solutions Group (TBSG) (Cisco Systems Inc, San Jose, CA, USA, 2012). (White Paper)

    Google Scholar 

  11. J. Bradley, C. Reberger, A. Dixit, V. Gupta, J. Macaulay, Internet of Everything (IoE): Top 10 Insights from Cisco’s IoE Value at Stake Analysis for the Public Sector, Cisco Internet Business Solutions Group (1BSG) (Cisco Systems Inc, San Jose, CA, USA, 2013). (Economic Analysis)

    Google Scholar 

  12. S. Balasubramaniam, J. Kangasharju, Realizing the internet of nano things: challenges, solutions, and applications. Computer 46(2), 62–68, February 2013 (Online)

    Google Scholar 

  13. I.F. Akyildiz, J.M. Jornet, The Internet of Nano-Things. IEEE Wireless Commun. 17(6), 58–63, December 2010 (Online)

    Google Scholar 

  14. LucMaret, Member, IEEE, C´edricDehos, “6GThenextfrontier” Member, IEEEtamp/stamp.jsp?tp = &arnumber = S67S779 arXiv:1901.03239v2 [cs.NI] 16 May 2019

  15. G. Gan, Z. Lu, J. Jiang, Internet of Things Security Analysis. Published in: 2011 International Conference on Internet Technology and Applications

    Google Scholar 

  16. K. Zhao, L. Ge, A Survey on the Internet of Things Security. Published in: IEEE 2013 Ninth International Conference on Computational Intelligence and Security, China

    Google Scholar 

  17. M. Wu, T.-L. Lu, F.-Y. Ling, L. Sun, H.-Y. Du, Research on the architecture of Internet of things. In: 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE) (2010)

    Google Scholar 

  18. N. Lin, W. Shi, The research on Internet of Things application architecture based on web. In: IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA) (2014)

    Google Scholar 

  19. C.-W. Tsai, C.-F. Lai, A.V. Vasilakos, Future Internet of Things: Open Issues and Challenge (Springer Science, New York, 2014)

    Google Scholar 

  20. P. Bhuyan, Smart ATM Machines. Published in Research Gate

    Google Scholar 

  21. R.S. Divya, M. Mathew, Survey on Various Door Lock Access Control Mechanisms. Published by IEEE in 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT), Kollam

    Google Scholar 

  22. J. Johnson, C. Dow, Intelligent Door Lock System with Encryption. US Patent Application Publication Johnson et al., June 2016, pp. 1–92

    Google Scholar 

  23. Jacintha, J. Nagarajan, K. Thanga Yogesh, S. Tamilarasu et al., An IOT based ATM surveillance system. Published in: 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore

    Google Scholar 

  24. R. Vijaysanthi, N. Radha, M. Jaya Shree, V. Sindhujaa, Fingerprint authentication using Raspberry Pi based on IoT. Published by IEEE in 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies, Chennai (2017)

    Google Scholar 

  25. N. Patil, S. Ambatkar, S. Kakde, IoT based smart surveillance security system using Raspberry Pi. Published by IEEE in 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai (2017)

    Google Scholar 

  26. S. Feng, P. Setoodeh, S. Haykin, Smart Home: Cognitive Interactive People-Centric Internet of Things. Published by IEEE in 2017

    Google Scholar 

  27. D.-G. Shin, M.-S. Jun, Home IoT Device Certification Through Speaker Recognition. Published by IEEE in 2015, South Korea

    Google Scholar 

  28. H. Jung, S. Lee, S. Park, Development of deep learning-based facial expression recognition system. Published by IEEE in 2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV), South Korea

    Google Scholar 

  29. P. Anne, B. McClard Aaren, E. Wendy, Facilitating Smart Geo-fencing-based Payment Transactions, Google patent US20170178117A1, March

    Google Scholar 

  30. J.-M. Bohli, A. Skarmeta, M. Victoria Moreno, Dan García, P. Langendörfer, SMARTIE project: secure IoT data management for smart cities. Published in: 2015 International Conference on Recent Advances in Internet of Things (RIoT) by IEEE, Singapore

    Google Scholar 

  31. B. Rosemary, A. Martin Felix, Mon “Smart Safe for Multiple Users” Google patents 2010

    Google Scholar 

  32. Z. Fadlullah et al., State-of-the-art deep learning: evolving machine intelligence toward tomorrow’s intelligent network traffic control systems. IEEE Commun. Surv. Tutorials. https://doi.org/10.1109/comst.2017.2707140

  33. N. Kato et al., The deep learning vision for heterogeneous network traffic control: proposal, challenges, and future perspective. IEEE Wireless Commun. 24(3), 146–153 (2017). https://doi.org/10.1109/MWC.2016.1600317WC

    Article  Google Scholar 

  34. S. Verma et al., A survey on network methodologies for real-time analytics of massive IoT data and open research issues. IEEE Commun. Surv. Tutorials. https://doi.org/10.1109/comst.2017.2694469

  35. L. Li, K. Ota, M. Dong, When weather matters: IoT based electrical load forecasting for smart grid. IEEE Commun. Mag. 55(10), 46–51 (2017)

    Article  Google Scholar 

  36. Ren et al., Serving at the edge: a scalable IoT architecture based on transparent computing. IEEE Netw. (2017)

    Google Scholar 

  37. Y. Bengio et al., Deep learning of representations for unsupervised and transfer learning. ICML Unsupervised Transf. Learn. 27, 17–36 (2012)

    Google Scholar 

  38. H. Valpola, From neural PCA to deep unsupervised learning, in Advances in Independent Component Analysis and Learning Machines (2015), pp. 143–171

    Google Scholar 

  39. H. Larry, Voice Control Everywhere: Low-power Special Purpose Chip Could Make Speech Recognition Ubiquitous in Electronics (2017)

    Google Scholar 

  40. O.M. Parkhi, A. Vedaldi, A. Zisserman et al., Deep face recognition, in British Machine Vision Conference, vol. 1, no. 3 (2015), p. 6

    Google Scholar 

  41. W. Zhang, K. Liu, W. Zhang, Y. Zhang, J. Gu, Deep neural networks for wireless localization in indoor and outdoor environments. Neuro Comput. 194, 279–287 (2016)

    Google Scholar 

  42. X. Wang, L. Gao, S. Mao, S. Pandey, Deepfi: Deep learning for indoor fingerprinting using channel state information, in 2015 IEEE Wireless Communications and Networking Conference (WCNC), (IEEE 2015), pp. 1666–1671

    Google Scholar 

  43. J. Liu, Y. Gu, S. Kamijo, Joint customer pose and orientation estimation using deep neural network from surveillance camera,” in 2016 IEEE International Symposium on Multimedia (ISM) (IEEE, 2016), pp. 216–221

    Google Scholar 

  44. Z. Yuan, Y. Lu, Z. Wang, Y. Xue, Droid-sec: deep learning in android malware detection, in ACM SIGCOMM Computer Communication Review, vol. 44, no. 4 (ACM, 2014), pp. 371–372

    Google Scholar 

  45. R. Shokri, V. Shmatikov, Privacy-preserving deep learning, in Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (ACM, 2015), pp. 1310–1321

    Google Scholar 

  46. M. Abadi, A. Chu, I. Goodfellow, H.B. McMahan, I. Mironov, K. Talwar, L. Zhang, Deep learning with differential privacy, in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (ACM, 2016), pp. 308–318

    Google Scholar 

  47. M. Mohammadi, A. Al-Fuqaha, S. Sorour, M. Guizani et al., Deep learning for IoT big data and streaming analytics: a survey. Published in: IEEE Communications Surveys & Tutorials Fourth Quarter (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Neha Sharma .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sharma, N., Panwar, D. (2021). Advance Security and Challenges with Intelligent IoT Devices. In: Goyal, D., Chaturvedi, P., Nagar, A.K., Purohit, S. (eds) Proceedings of Second International Conference on Smart Energy and Communication. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-6707-0_17

Download citation

Publish with us

Policies and ethics