Skip to main content
SpringerLink
Log in

Big Data Analytics for Cybersecurity in IoE Networks

  • Chapter
  • First Online:
Cybersecurity Vigilance and Security Engineering of Internet of Everything

Part of the book series: Internet of Things ((ITTCC))

  • 138 Accesses

Abstract

The term Internet of Everything (IoE) refers to the intelligent network that links together people, data, objects, and processes. These devices generate a massive amount of data which leads to Big Data and its analysis issues. The primary function of Big Data analytics is data storage, management, and processing. The main purpose of this chapter is to investigate the existing frameworks for implementing Big Data analytics into the development of safe IoE network operations and services. The data is gathered from different sources like sensors, smart wireless, and wireless devices and is further utilized for predictive analysis and planning. This information is further used for decision-making to control the surrounding processes. However, due to the massive amount of data and open systems scenario, the network is vulnerable to security attacks and threats. This chapter presents a comprehensive look at how Big Data analytics can be applied to create a trustworthy network.

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 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
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. Dias I, Sousa MJ Business Intelligence applied to Human resources management. In: New Contributions in Information Systems and Technologies: Volume 2, 2015. Springer, pp. 105–113

    Chapter  Google Scholar 

  2. Rathore MM, Ahmad A, Paul A, Rho S (2016) Urban planning and building smart cities based on the internet of things using big data analytics. Computer networks 101:63–80. doi:https://doi.org/10.1016/j.comnet.2015.12.023

    Article  Google Scholar 

  3. Kashif Naseer Qureshi AA, Raja Waseem Anwar, Shahid Nazir Bhati, and Gwanggil Jeon (2021) Fully Integrated Data Communication Framework by Using Visualization Augmented Reality for Internet of Things Networks. Big Data 9 (4):253–264. doi:https://doi.org/10.1089/big.2020.0282

    Article  Google Scholar 

  4. Zhan K (2021) Sports and health big data system based on 5G network and Internet of Things system. Microprocessors and Microsystems 80:103363

    Article  Google Scholar 

  5. Pramanik M, Lau R, Youe W, Ye Y, Li C (2017) Big data analytics for security and criminal investigation. WIREs Data Min Knowl Discov 7: e1208. doi:https://doi.org/10.1002/widm.1208

    Article  Google Scholar 

  6. Qureshi MA, Qureshi KN, Jeon G, Piccialli F (2021) Deep learning-based ambient assisted living for self-management of cardiovascular conditions. Neural Computing and Applications. doi:https://doi.org/10.1007/s00521-020-05678-w

  7. Shojafar M, Sookhak M (2020) Internet of everything, networks, applications, and computing systems (IoENACS). vol 42. Taylor & Francis. doi:https://doi.org/10.1080/1206212X.2019.1575621

    Book  Google Scholar 

  8. Bandre SR, Nandimath JN Design consideration of Network Intrusion detection system using Hadoop and GPGPU. In: 2015 international conference on pervasive computing (ICPC), 2015. IEEE, pp 1–6. doi:https://doi.org/10.1109/PERVASIVE.2015.7087201

  9. Qureshi KN, Qayyum S, Ul Islam MN, Jeon G (2021) A secure data parallel processing based embedded system for internet of things computer vision using field programmable gate array devices. International Journal of Circuit Theory and Applications n/a (n/a). doi:https://doi.org/10.1002/cta.2964

  10. Ahmed E, Yaqoob I, Hashem IAT, Khan I, Ahmed AIA, Imran M, Vasilakos AV (2017) The role of big data analytics in Internet of Things. Computer Networks 129:459–471. doi:https://doi.org/10.1016/j.comnet.2017.06.013

    Article  Google Scholar 

  11. Lee I (2017) Big data: Dimensions, evolution, impacts, and challenges. Business horizons 60 (3):293–303. doi:https://doi.org/10.1016/j.bushor.2017.01.004

    Article  Google Scholar 

  12. Sheriff CI, Naqishbandi T, Geetha A Healthcare informatics and analytics framework. In: 2015 International Conference on Computer Communication and Informatics (ICCCI), 2015. IEEE, pp 1–6. doi:https://doi.org/10.1109/ICCCI.2015.7218108

  13. Marchal S, Jiang X, State R, Engel T A big data architecture for large scale security monitoring. In: 2014 IEEE International Congress on Big Data, 2014. IEEE, pp 56–63. doi:https://doi.org/10.1109/BigData.Congress.2014.18

  14. Chen Z, Zhang H, Hatcher WG, Nguyen J, Yu W A streaming-based network monitoring and threat detection system. In: 2016 IEEE 14th International Conference on Software Engineering Research, Management and Applications (SERA), 2016. IEEE, pp 31–37. doi:https://doi.org/10.1109/SERA.2016.7516125

  15. Lighari SN Testing of algorithms for anomaly detection in Big data using Apache spark. In: 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN), 2017. IEEE, pp 97–100. doi:https://doi.org/10.1109/CICN.2017.8319364

  16. Jia Z, Shen C, Yi X, Chen Y, Yu T, Guan X Big-data analysis of multi-source logs for anomaly detection on network-based system. In: 2017 13th IEEE conference on automation science and engineering (CASE), 2017. IEEE, pp 1136–1141. doi:https://doi.org/10.1109/COASE.2017.8256257

  17. Gupta GP, Kulariya M (2016) A framework for fast and efficient cyber security network intrusion detection using Apache spark. Procedia Computer Science 93:824–831. doi:https://doi.org/10.1016/j.procs.2016.07.238.

    Article  Google Scholar 

  18. Fontugne R, Mazel J, Fukuda K Hashdoop: A MapReduce framework for network anomaly detection. In: 2014 IEEE conference on computer communications workshops (INFOCOM WKSHPS), 2014. IEEE, pp 494–499. doi:https://doi.org/10.1109/INFCOMW.2014.6849281

  19. Dahiya P, Srivastava DK (2018) Network intrusion detection in big dataset using spark. Procedia computer science 132:253–262. doi:https://doi.org/10.1016/j.procs.2018.05.169

    Article  Google Scholar 

  20. Vangara RVB, Vangara SP, Thirupathur V (2020) A survey on natural language processing in context with machine learning. Int J Anal Exp Modal Anal: 1390–1395

    Google Scholar 

  21. Fayyad U Data mining and knowledge discovery in databases: implications for scientific databases. In: Proceedings. Ninth International Conference on Scientific and Statistical Database Management (Cat. No. 97TB100150), 1997. IEEE, pp. 2–11. doi:https://doi.org/10.1109/ssdm.1997.621141

    Chapter  Google Scholar 

  22. Srivastava J, Cooley R, Deshpande M, Tan P-N (2000) Web usage mining: Discovery and applications of usage patterns from web data. Acm Sigkdd Explorations Newsletter 1 (2):12–23. doi:https://doi.org/10.1145/846183.846188.

    Article  Google Scholar 

  23. Rabhi L, Falih N, Afraites A, Bouikhalene B (2019) Big data approach and its applications in various fields. Procedia Computer Science 155:599–605. doi:https://doi.org/10.1016/j.procs.2019.08.084

    Article  Google Scholar 

  24. Tien C-W, Chen S-W, Ban T, Kuo S-Y (2020) Machine learning framework to analyze IOT malware using ELF and opcode features. Digital Threats: Research and Practice 1 (1):1–19. doi:https://doi.org/10.1145/3378448

    Article  Google Scholar 

  25. Ming J, Xin Z (2017) Impeding behavior-based malware analysis via replacement attacks to malware specifications. Journal of Computer Virology and Hacking Techniques 13 (3):193–207. doi:https://doi.org/10.1007/s11416-016-0281-3

    Article  Google Scholar 

  26. Manogaran G, Thota C, Kumar MV (2016) MetaCloudDataStorage architecture for big data security in cloud computing. Procedia Computer Science 87:128–133. doi:https://doi.org/10.1016/j.procs.2016.05.138

    Article  Google Scholar 

  27. Cheng J, Xu R, Tang X, Sheng VS, Cai C (2018) An abnormal network flow feature sequence prediction approach for DDoS attacks detection in big data environment. Comput Mater Continua 55 (1):95–119. doi:https://doi.org/10.3970/cmc.2018.055.095

    Article  Google Scholar 

  28. Valle RR, Manzanares FV (2013) Concentration of goods traffic in Spanish ports during the period 2000–2009. Regional and Sectoral Economic Studies 13 (2):59–72

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Technology, Lahore Leads University, Lahore, Pakistan

    Faisal Rehman & Hanan Sharif

  2. Department of Statistics and Data Science, University of Mianwali, Mianwali, Pakistan

    Faisal Rehman

  3. Department of Information Sciences, Division of Science and Technology, University of Education, Lahore, Pakistan

    Muhammad Anwar

  4. National University of Sciences & Technology, Islamabad, Pakistan

    Naveed Riaz

Authors
  1. Faisal Rehman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hanan Sharif
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Muhammad Anwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Naveed Riaz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muhammad Anwar .

Editor information

Editors and Affiliations

  1. Department of Electronic and Computer Engineering, University of Limerick (UL), Limerick, Ireland

    Kashif Naseer Qureshi

  2. Department of Electronic and Computer Engineering, University of Limerick (UL), Limerick, Ireland

    Thomas Newe

  3. Department of Embedded Systems Engineering, Incheon National University, Incheon, Korea (Republic of)

    Gwanggil Jeon

  4. Department of Mathematics and Computer Science, Royal Military College of Canada, Kingston, ON, Canada

    Abdellah Chehri

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rehman, F., Sharif, H., Anwar, M., Riaz, N. (2024). Big Data Analytics for Cybersecurity in IoE Networks. In: Naseer Qureshi, K., Newe, T., Jeon, G., Chehri, A. (eds) Cybersecurity Vigilance and Security Engineering of Internet of Everything. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-031-45162-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-45162-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45161-4

  • Online ISBN: 978-3-031-45162-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation