Skip to main content
SpringerLink
Log in

Securing Data from Active Attacks in IoT: An Extensive Study

  • Conference paper
  • First Online:
Proceedings of International Conference on Deep Learning, Computing and Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1396))

Abstract

The Internet of Things (IoT) is one of the most important technologies aimed at improving the quality of human lives. IoT plays a promising role in many business applications including healthcare, automotive, agriculture, and education. But the crucial task is to address and analyze the IoT security issues because the IoT environment has a heterogeneous nature of data. In order to achieve end-to-end secure environment, it is necessary to change the design of IoT application’s architecture. Therefore, a detailed study of security issues of IoT devices, its limitations, requirements of security, and possible solutions are presented in this research study. In addition, various sources of security threats at different layers of IoT environment are presented. The main contribution of this study is to classify threats and potential IoT security challenges from an architectural perspective. After discussing various security issues, a number of emerging and existing technologies are presented that are focused on achieving higher user confidence in IoT applications.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight 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. H. Zakaria, N.A.A. Bakar, N.H. Hassan, S. Yaacob, IoT security risk management model for secured practice in healthcare environment. Procedia Comput. Sci. 161, 1241–1248 (2019)

    Article  Google Scholar 

  2. S. Rathore, J.H. Park, Semi-supervised learning based distributed attack detection framework for IoT. Appl. Soft Comput. 72, 79–89 (2018)

    Article  Google Scholar 

  3. K. Mabodi, M. Yusefi, S. Zandiyan, L. Irankhah, R. Fotohi, Multi-level trust based intelligence schema for securing of Internet of Things (IoT) against security threats using cryptographic authentication. J. Supercomput. 1–25 (2020)

    Google Scholar 

  4. X. Li, Q. Wang, X. Lan, X. Chen, N. Zhang, D. Chen, Enhancing cloudbased IoT security through trustworthy cloud service: an integration of security and reputation approach. IEEE Access 7, 9368–9383 (2019)

    Article  Google Scholar 

  5. D. Wang, B. Bai, K. Lei, W. Zhao, Y. Yang, Z. Han, Enhancing information security via physical layer approaches in heterogeneous IoT with multiple access mobile edge computing in smart city. IEEE Access 7, 54508–54521 (2019)

    Article  Google Scholar 

  6. B. Mukherjee, S. Wang, W. Lu, R.L. Neupane, D. Dunn, Y. Ren, Q. Su, P. Calyam, Flexible IoT security middleware for end-to-end cloud–fog communication. Futur. Gener. Comput. Syst. 87, 688–703 (2018)

    Article  Google Scholar 

  7. M.D. Alshehri, F.K. Hussain, A fuzzy security protocol for trust management in the Internet of Things (Fuzzy-IoT). Computing 101(7), 791–818 (2019)

    Article  MathSciNet  Google Scholar 

  8. S.K. Sood, Mobile fog based secure cloud-IoT framework for enterprise multimedia security. Multimedia Tools Appl. 1–16 (2019)

    Google Scholar 

  9. Y. Meidan, M. Bohadana, Y. Mathov, Y. Mirsky, A. Shabtai, D. Breitenbacher, Y. Elovici, N-baiot—network-based detection of IoT botnet attacks using deep autoencoders. IEEE Pervasive Comput. 17(3), 12–22 (2018)

    Article  Google Scholar 

  10. Y. Zong, G. Huang, A feature dimension reduction technology for predicting DDoS intrusion behavior in multimedia Internet of Things. Multimedia Tools Appl. 1–14 (2019)

    Google Scholar 

  11. Y. Liu, C. Yang, L. Jiang, S. Xie, Y. Zhang, Intelligent edge computing for IoT-based energy management in smart cities. IEEE Netw. 33(2), 111–117 (2019)

    Article  Google Scholar 

  12. B. Maram, J.M. Gnanasekar, G. Manogaran, M. Balaanand, Intelligent security algorithm for UNICODE data privacy and security in IoT. SOCA 13(1), 3–15 (2018). https://doi.org/10.1007/s11761-018-0249-x

    Article  Google Scholar 

  13. P.N. Hiremath, J. Armentrout, S. Vu, T.N. Nguyen, Q.T. Minh, P.H. Phung, MyWebGuard: toward a user-oriented tool for security and privacy protection on the web, in Future Data and Security Engineering, FDSE 2019. Lecture Notes in Computer Science, edited by T. Dang, J. KĂĽng, M. Takizawa, S. Bui, vol. 11814. (Springer, Cham, 2019). https://doi.org/10.1007/978-3-030-35653-8_33

  14. R. Arridha, S. Sukaridhoto, S. Pramadihanto, N. Funabiki, Classification extension based on IoT-big data analytic for smart environment monitoring and analytic in real-time system. Int. J. Space-Based Situated Comput. 7(2), 82–93 (2017)

    Google Scholar 

  15. O. Elijah, T.A. Rahman, I. Orikumhi, C.Y. Leow, M.N. Hindia, An overview of Internet of Things (IoT) and data analytics in agriculture: benefits and challenges. IEEE Internet Things J. 5(5), 3758–3773 (2018)

    Article  Google Scholar 

  16. S. Pirbhulal, H. Zhang, E. Alahi, M. Eshrat, H. Ghayvat, S.C. Mukhopadhyay, Y.T. Zhang, W. Wu, A novel secure IoT-based smart home automation system using a wireless sensor network. Sensors 17(1), 69 (2017)

    Google Scholar 

  17. S. Challa, M. Wazid, A.K. Das, N. Kumar, A.G. Reddy, E.J. Yoon, K.Y. Yoo, Secure signature-based authenticated key establishment scheme for future IoT applications. IEEE Access 5, 3028–3043 (2017)

    Article  Google Scholar 

  18. D. Yin, L. Zhang, K. Yang, A DDoS attack detection and mitigation with software-defined Internet of Things framework. IEEE Access 6, 24694–24705 (2018)

    Article  Google Scholar 

  19. A. Mehmood, M. Mukherjee, S.H. Ahmed, H. Song, K.M. Malik, NBCMAIDS: Näıve Bayesian classification technique in multi-agent system-enriched IDS for securing IoT against DDoS attacks. J. Supercomput. 74(10), 5156–5170 (2018)

    Article  Google Scholar 

  20. S. Rathore, B.W. Kwon, J.H. Park, BlockSecIoTNet: blockchain-based decentralized security architecture for IoT network. J. Netw. Comput. Appl. 143, 167–177 (2019)

    Article  Google Scholar 

  21. A. Dorri, S.S. Kanhere, R. Jurdak, P. Gauravaram, LSB: a lightweight scalable blockchain for IoT security and anonymity. J. Parallel Distrib. Comput. 134, 180–197 (2019)

    Article  Google Scholar 

  22. H. Si, C. Sun, Y. Li, H. Qiao, L. Shi, IoT information sharing security mechanism based on blockchain technology. Futur. Gener. Comput. Syst. 101, 1028–1040 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of CSE, SRMIST, Chennai, India

    C. Silpa & G. Niranjana

  2. Department of IT, SVEC, Tirupati, India

    K. Ramani

Authors
  1. C. Silpa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. G. Niranjana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Ramani
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of California, Davis, CA, USA

    Gunasekaran Manogaran

  2. Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, India

    A. Shanthini

  3. Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur, India

    G. Vadivu

Rights and permissions

Reprints and permissions

Copyright information

© 2022 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

Silpa, C., Niranjana, G., Ramani, K. (2022). Securing Data from Active Attacks in IoT: An Extensive Study. In: Manogaran, G., Shanthini, A., Vadivu, G. (eds) Proceedings of International Conference on Deep Learning, Computing and Intelligence. Advances in Intelligent Systems and Computing, vol 1396. Springer, Singapore. https://doi.org/10.1007/978-981-16-5652-1_5

Download citation

Publish with us

Policies and ethics

Search

Navigation