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Big Data and Its Role in Cybersecurity

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Innovations in Data Analytics ( ICIDA 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1442))

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Abstract

Big Data Analytics (BDA) is defined as the process of processing, storing, and acquiring enormous volumes of data for future analysis. Data is being generated at an alarmingly rapid rate. The Internet’s fast expansion, the Internet of Things (IoT), social networking sites, and other technical breakthroughs are the primary sources of big data. It is a critical characteristic in cybersecurity, where the purpose is to safeguard assets. Furthermore, the increasing value of data has elevated big data to the status of a high-value target. In this study, we look at recent cybersecurity research in connection to big data. We discussed how big data is safeguarded and how it could be utilized as a cybersecurity tool. We also discussed cybersecurity in the age of big data as well as trends and challenges in its research.

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References

  1. D. Laney, 3d data management: controlling data volume, velocity and variety. META Group Res. Note 6(70), 1 (2001)

    Google Scholar 

  2. N. Miloslavskaya, A. Tolstoy, Application of big data, fast data, and data lake concepts to information security issues, in 2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) (IEEE, 2016), pp. 148–153

    Google Scholar 

  3. D. Rawat, K.Z. Ghafoor, Smart Cities Cybersecurity and Privacy (Elsevier, Amsterdam, The Netherlands, 2018)

    Google Scholar 

  4. E. Bertino, Big data-security and privacy, in 2015 Proceedings on IEEE International Congress on Big Data (IEEE, 2015), pp. 757–761

    Google Scholar 

  5. S. Abidin, V.R. Vadi, V. Tiwari, Big data analysis using R and hadoop, in Springer 2nd International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020), Kolkata, 2–4 July 2020 (Publication in Advances in Intelligent System and Computing, Springer AISC, ISSN: 2194-5357), pp. 50–53

    Google Scholar 

  6. S. Abidin, V.R. Vadi, A. Rana, On confidentiality, integrity, authenticity and freshness (CIAF) in WSN, in 4th Springer International Conference on Computer, Communication and Computational Sciences (IC4S 2019), Bangkok, Thailand, 11–12 October 2019 (Publication in Advances in Intelligent Systems and Computing, ISSN: 2194-5357), pp. 952–957

    Google Scholar 

  7. T. Mahmood, U. Afzal, Security analytics: big data analytics for cybersecurity: a review of trends, techniques and tools, in 2013 2nd National Conference on Information Assurance (NCIA) (IEEE, 2013), pp. 129–134

    Google Scholar 

  8. S. Rao, S. Suma, M. Sunitha, Security solutions for big data analytics in healthcare, in 2015 2nd International Conference on Advances in Computing and Communication Engineering (IEEE, 2015), pp. 510–514

    Google Scholar 

  9. I. Olaronke, O. Oluwaseun, Big data in healthcare: prospects, challenges and resolutions, in 2016 Future Technologies Conference (FTC) (IEEE, 2016), pp. 1152–1157

    Google Scholar 

  10. H.-T. Cui, Research on the model of big data serve security in cloud environment, in 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI) (IEEE, 2016), pp. 514–517

    Google Scholar 

  11. E. Damiani, Toward big data risk analysis, in 2015 IEEE International Conference on Big Data (Big Data) (IEEE, 2015), pp. 1905–1909

    Google Scholar 

  12. Sinclair, L. Pierce, S. Matzner, An application of machine learning to network intrusion detection, in Proceedings 15th Annual Computer Security Applications Conference (ACSAC’99) (IEEE, 1999), pp. 371–377

    Google Scholar 

  13. E. Chickowski, A Case Study in Security Big Data Analysis, vol. 9. (Dark Reading, 2012). https://www.darkreading.com/analytics/security-monitoring/a-case-study-in-security-big-data-analysis/d/d-id/1137299

  14. M.C. Raja, M.A. Rabbani, Big data analytics security issues in data driven information system. IJIRCCE 2(10), 6132–6134 (2014)

    Google Scholar 

  15. V.S. Carvalho, M.J. Polidoro, J.P. Magalhaes, Owlsight: platform for real-time detection and visualization of cyber threats, in 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS) (IEEE, 2016), pp. 61–66

    Google Scholar 

  16. Y. Yao, L. Zhang, J. Yi, Y. Peng, W. Hu, L. Shi, A framework for big data security analysis and the semantic technology, in 2016 6th International Conference on IT Convergence and Security (ICITCS) (IEEE, 2016), pp. 1–4

    Google Scholar 

  17. S. Abidin, Encryption and database security. Int. J. Comput. Eng. Appl. 11(8), 116–121 (2017). ISSN: 2321-3469

    Google Scholar 

  18. T. Zaki, M.S. Uddin, M.M. Hasan, M.N. Islam, Security threats for big data: a study on enron e-mail dataset, in 2017 International Conference on Research and Innovation in Information Systems (ICRIIS) (IEEE, 2017), pp. 1–6

    Google Scholar 

  19. P.H. Las-Casas, V.S. Dias, W. Meira, D. Guedes, A big data architecture for security data and its application to phishing characterization, in 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data And Security (IDS) (IEEE, 2016), pp. 36–41

    Google Scholar 

  20. A.A. Cardenas, P.K. Manadhata, S. Rajan, Big data analytics for security intelligence. Technical Report by (Big Data Working Group of CloudSecurity Alliance, 2013), pp. 1–22. https://downloads.cloudsecurityalliance.org/initiatives/bdwg/Big_Data_Analytics_for_Security_Intelligence.pdf

  21. B.G.-N. Crespo, A. Garwood, Fighting botnets with cyber- security analytics: dealing with heterogeneous cyber-security information in new generation siems, in 2014 9th International Conference on Availability, Reliability and Security (IEEE, 2014), pp. 192–198

    Google Scholar 

  22. D.C. Le, A.N. Zincir-Heywood, M.I. Heywood, Data analytics on network traffic flows for botnet behaviour detection, in 2016 IEEE symposium series on computational intelligence (SSCI) (IEEE, 2016), pp. 1–7

    Google Scholar 

  23. G. Gardikis, K. Tzoulas, K. Tripolitis, A. Bartzas, S. Costicoglou, A. Lioy, B. Gaston, C. Fernandez, C. Davila, A. Litke, et al., SHIELD: a novel NFV-based cybersecurity framework, in 2017 IEEE Conference on Network Softwarization (NetSoft) (IEEE, 2017), pp. 1–6

    Google Scholar 

  24. F. Gottwalt, A.P. Karduck, SIM in light of big data, in 2015 11th International Conference on Innovations in Information Technology (IIT) (IEEE, 2015), pp. 326–331

    Google Scholar 

  25. T.Y. Win, H. Tianfield, Q. Mair, Big data-based security analytics for protecting virtualized infrastructures in cloud computing. IEEE Trans. Big Data 4(1), 11–25 (2017). (March 2018)

    Google Scholar 

  26. C. Puri, C. Dukatz, Analyzing and predicting security event anomalies: Lessons learned from a large enterprise big data streaming analytics deployment, in 2015 26th International Workshop on Database and Expert Systems Applications (DEXA) (IEEE, 2015), pp. 152–158

    Google Scholar 

  27. S. Mukkamala, A. Sung, A. Abraham, Cyber security challenges: designing efficient intrusion detection systems and antivirus tools, in Enhancing Computer Security with Smart Technology, ed. by V. Rao (CRC Press, USA, 2005, ISBN 0849330459), pp.125–161

    Google Scholar 

  28. T. Yang, P. Shen, X. Tian, C. Chen, A fine-grained access control scheme for big data based on classification attributes, in 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW) (IEEE, 2017), pp. 238–245

    Google Scholar 

  29. S. Pérez, J.L. Hernández-Ramos, D. Pedone, D. Rotondi, L. Straniero, A.F. Skarmeta, A digital envelope approach using attribute-based encryption for secure data exchange in IoT scenarios, in 2017 Global Internet of Things Summit (GIoTS) (IEEE, 2017), pp. 1–6

    Google Scholar 

  30. A. Al Mamun, K. Salah, S. Al-Maadeed, T.R. Sheltami, BigCrypt for big data encryption, in 2017 4th International Conference on Software Defined Systems (SDS) (IEEE, 2017), pp. 93–99.

    Google Scholar 

  31. A. Sharma, D. Sharma, Big data protection via neural and quantum cryptography, in 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom) (IEEE, 2016), pp. 3701–3704

    Google Scholar 

  32. S. Almuhammadi, A. Amro, Double-hashing operation mode for encryption, in 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC) (IEEE, 2017), pp. 1–7

    Google Scholar 

  33. M.G. Schultz, E. Eskin, F. Zadok, S.J. Stolfo, Data mining methods for detection of new malicious executables, in Proceedings 2001 IEEE Symposium on Security and Privacy (IEEE, 2001), pp. 38–49

    Google Scholar 

  34. V. Patel, A practical solution to improve cyber security on a global scale, in 2012 3rd Worldwide Cybersecurity Summit (WCS) (IEEE, 2012), pp. 1–5

    Google Scholar 

  35. W. Jia, Study on network information security based on big data, in 2017 9th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (IEEE, 2017), pp. 408–409

    Google Scholar 

  36. H.H. Huang, H. Liu, Big data machine learning and graph analytics: current state and future challenges, in 2014 IEEE International Conference on Big Data (Big Data) (IEEE, 2014), pp. 16–17

    Google Scholar 

  37. S. Kumar, A. Viinikainen, T. Hamalainen, Machine learning classification model for network-based intrusion detection system, in 2016 11th International Conference for Internet Technology and Secured Transactions (ICITST) (IEEE, 2016), pp. 242–249

    Google Scholar 

  38. N. Naik, P. Jenkins, N. Savage, V. Katos, Big data security analysis approach using computational intelligence techniques in R for desktop users, in 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (IEEE, 2016), pp. 1–8

    Google Scholar 

  39. J. Kepner, V. Gadepally, P. Michaleas, N. Schear, M. Varia, A. Yerukhimovich, R.K. Cunningham, Computing on masked data: a high-performance method for improving big data veracity, in 2014 IEEE High Performance Extreme Computing Conference (HPEC) (IEEE, 2014), pp. 1–6

    Google Scholar 

  40. D. Wang, B. Guo, Y. Shen, S.-J. Cheng, Y.-H. Lin, A faster fully homomorphic encryption scheme in big data, in 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA) (IEEE, 2017), pp. 345–349

    Google Scholar 

  41. S. Perez, J.L. Hernandez-Ramos, D. Pedone, D. Rotondi, L. Straniero, A.F. Skarmeta, A digital envelope approach using attribute-based encryption for secure data exchange in IoT scenarios, in 2017 Global Internet of Things Summit (GIoTS) (IEEE, 2017), pp. 1–6

    Google Scholar 

  42. G. Xu, Y. Ren, H. Li, D. Liu, Y. Dai, K. Yang, Cryptmdb: a practical encrypted mongodb over big data, in 2017 IEEE International Conference on Communications (ICC) (IEEE, 2017), pp. 1–6

    Google Scholar 

  43. C. Zhao, J. Liu, Novel group key transfer protocol for big data security, in 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (IEEE, 2015), pp. 161–165

    Google Scholar 

  44. A. Al-Shomrani, F. Fathy, K. Jambi, Policy enforcement for big data security, in 2017 2nd International Conference on Anti-Cyber Crimes (ICACC) (IEEE, 2017), pp. 70–74

    Google Scholar 

  45. A. Samuel, M.I. Sarfraz, H. Haseeb, S. Basalamah, A. Ghafoor, A framework for composition and enforcement of privacy-aware and context-driven authorization mechanism for multimedia big data. IEEE Trans. Multimed. 17(9), 1484–1494 (2015)

    Article  Google Scholar 

  46. F. Gao, Research on cloud security control mechanism based on big data, in 2017 International Conference on Smart Grid and Electrical Automation (ICSGEA) (IEEE, 2017), pp. 366–370

    Google Scholar 

  47. A. Gupta, A. Verma, P. Kalra, L. Kumar, Big data: a security compliance model, in 2014 Conference on IT in Business, Industry and Government (CSIBIG) (IEEE, 2014), pp. 1–5

    Google Scholar 

  48. E. Damiani, C. Ardagna, F. Zavatarelli, E. Rekleitis, L. Marinos, Big Data Threat Landscape, (European Union Agency For Network And Information Security, 2017). https://www.enisa.europa.eu/publications/bigdata-threat-landscape. (Online)

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Authors and Affiliations

  1. Department of Information Technology, University of Technology and Applied Science Al Musanna, Muladdah, Sultanate of Oman

    Faheem Ahmad & Imran Qureshi

  2. Department of Computer Science, Aligarh Muslim University Aligarh, Aligarh, UP, India

    Shafiqul Abidin

  3. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India

    Mohammad Ishrat

Authors
  1. Faheem Ahmad
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  2. Shafiqul Abidin
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  3. Imran Qureshi
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  4. Mohammad Ishrat
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Corresponding author

Correspondence to Mohammad Ishrat .

Editor information

Editors and Affiliations

  1. Institute of Engineering & Management, kolkata, India

    Abhishek Bhattacharya

  2. Institute of Engineering & Management, Kolkata, West Bengal, India

    Soumi Dutta

  3. Visva-Bharati University, Shantiniketan, West Bengal, India

    Paramartha Dutta

  4. Universita' Degli Studi di Milano, Milano, Italy

    Vincenzo Piuri

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Ahmad, F., Abidin, S., Qureshi, I., Ishrat, M. (2023). Big Data and Its Role in Cybersecurity. In: Bhattacharya, A., Dutta, S., Dutta, P., Piuri, V. (eds) Innovations in Data Analytics. ICIDA 2022. Advances in Intelligent Systems and Computing, vol 1442. Springer, Singapore. https://doi.org/10.1007/978-981-99-0550-8_10

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