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2021 | OriginalPaper | Buchkapitel

8. Big Data Analytics and Cybersecurity: Emerging Trends

verfasst von : Sakshi Aggarwal, Stavros Sindakis

Erschienen in: Big Data Analytics in Cognitive Social Media and Literary Texts

Verlag: Springer Singapore

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Abstract

At the current digital age, cybercrimes are increasing vastly. The strategies and tools preventing sophisticated cyberattacks and crimes cause organizations to stay intelligent with developing dangers. Big Data Analytics plays a crucial role when it comes to operational intelligence and security. This chapter aims to present a comprehensive cutting edge of Security Analytics, i.e., its trends, tools, technology, and description. Similarly, the work is engaged in three sorts: supervised, unsupervised, and hybrid approaches. The theoretical model developed in the chapter is based on the three types of machine learning, allowing the P.C. to learn and get to sample information without being customized to predict each conceivable circumstance. A structured work was applied to synthesize the theoretical model. A search of the existing literature is done on different websites, Scopus and Google Scholar, applying a mix of keywords such as Big Data Analytics, cybersecurity, and security analytics. This chapter will put forth the ideas and emerging strategies available to work with Big Data to lay out a future vision. Hence, it aims to persuade the imminent reader about emerging applications/trends of analytics as a cybersecurity solution later.

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Apurva, A., Ranakoti, P., Yadav, S., Tomer, S., & Roy, N. R. (2017). Redefining cyber security with big data analytics. In 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN), pp. 199–203. IEEE.

Bachupally, Y. R., Yuan, X., & Roy, K. (2016) March network security analysis using big data technology. In SoutheastCon 2016, pp. 1–4. IEEE.

Balan, S., Otto, J., Minasian, E., & Aryal, A. (2017). Data analysis of cybercrimes in businesses. Information Technology and Management Science, 20(1), 64–68.CrossRef

Bendre, M. R., & Thool, V. R. (2016). Analytics, challenges and applications in big data environment: A survey. Journal of Management Analytics, 3(3), 206–239.CrossRef

Brewster, B., Kemp, B., Galehbakhtiari, S., & Akhgar, B. (2015). Cybercrime: attack motivations and implications for big data and national security. In Application of Big Data for National Security, pp. 108–127. Butterworth-Heinemann.

Broeders, D., Schrijvers, E., van der Sloot, B., van Brakel, R., de Hoog, J., & Ballin, E. H. (2017). Big Data and security policies: Towards a framework for regulating the phases of analytics and use of Big Data. Computer Law & Security Review, 33(3), 309–323.CrossRef

Boukri, K., & Chaoui, H. (2015). Security analytics in big data infrastructures. International Journal of Computer Science and Information Security, 13(5), 91.

Chan, J., & Bennett Moses, L. (2016). Is big data challenging criminology? Theoretical Criminology, 20(1), 21–39.CrossRef

Chhabra, G. S., Singh, V. P., & Singh, M. (2018). Cyber forensics framework for big data analytics in IoT environment using machine learning. Multimedia Tools and Applications, 1–20.

Devin, S. (2018). Supervised vs. Unsupervised Learning, Understanding the differences between the two main types of machine learning methods. Towards data science. Available at: https://towardsdatascience.com/supervised-vs-unsupervised-learning-14f68e32ea8d. Accessed on: June 11, 2020.

Dhaka, P., & Johari, R. (2016). April CRIB: Cyber crime investigation, data archival and analysis using big data tool. In 2016 International Conference on Computing, Communication and Automation (ICCCA), pp. 117–121. IEEE.

Iovan, S., & Iovan, A. A. (2016). From cyber threats to cyber-crime. Journal of Information Systems & Operations Management, 10(2).

Jadon, P., & Mishra, D. K. (2019). Security and privacy issues in big data: A review. In Emerging Trends in Expert Applications and Security, pp. 659–665. Springer, Singapore.

Jayasingh, B. B., Patra, M. R., & Mahesh, D. B. (2016). December Security issues and challenges of big data analytics and visualization. In 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), pp. 204–208. IEEE.

Joglekar, P., & Pise, N. (2016). Solving cyber security challenges using big data. International Journal of Computer Applications, 154(4), 9–12.CrossRef

Lehto, M., & Neittaanmäki, P. (eds.) (2015) Cyber security: Analytics, technology and automation (Vol. 78). Springer.

Lambert, I. I., & Glenn, M. (2017). Security analytics: Using deep learning to detect Cyber Attacks.

Lord, N. (2018). What is security analytics? Learn about the use cases and benefits of security analytics tools. DATAINSIDER. Available via https://digitalguardian.com/blog/what-security-analytics-learn-about-use-cases-and-benefits-security-analytics-tools. Accessed June 09, 2020.

Michelle, T. (2019). Top 6 emerging trends in cyber security for 2019. Stu News. Available at: https://www.stu.edu/news/emerging-trends-in-cyber-security-2019/. Accessed on: May 02, 2020.

Mishra, A. D., & Singh, Y. B.: (2016). April. Big data analytics for security and privacy challenges. In 2016 International Conference on Computing, Communication and Automation (ICCCA), pp. 50–53. IEEE.

Mondek, D., Blažek, R. B., & Zahradnický, T. (2017). Security analytics in the big data Era. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C, pp. 605–606. IEEE.

Petrenko, S. A., & Makoveichuk, K. A. (2017). Big data technologies for cybersecurity. In CEUR Workshop, pp. 107–111.

Pramanik, M. I., Lau, R. Y., Yue, W. T., Ye, Y., & Li, C. (2017) Big data analytics for security and criminal investigations. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(4), e1208.

Priya, D. (2019). Top 10 cyber security trends to watch in 2020. Analytics Insight. Available at: https://www.analyticsinsight.net/top-10-cyber-security-trends-to-watch-in-2020/. Accessed on: June 14, 2020.

Rassam, M. A., Maarof, M., & Zainal, A. (2017). Big data analytics adoption for cybersecurity: A Review of current solutions, requirements, challenges and trends. Journal of Information Assurance & Security, 12(4).

Samantha Ann Schwartz. (2020). 5 cybersecurity trends for 2020. CIODIVE. Available via https://www.ciodive.com/news/5-cybersecurity-trends-for-2020/569169/. Accessed June 22, 2020.

Sethi, A.. (2020). Supervised learning vs. unsupervised learning—a quick guide for beginners. Analytics Vidhya. Available via https://www.analyticsvidhya.com/blog/2020/04/supervised-learning-unsupervised-learning/. Accessed June 01, 2020.

Shalaginov, A., Johnsen, J. W., & Franke, K. (2017). December Cyber crime investigations in the era of big data. In 2017 IEEE International Conference on Big Data (Big Data), pp. 3672–3676. IEEE.

Tang, M., Alazab, M., & Luo, Y. (2017). Big data for cybersecurity: Vulnerability disclosure trends and dependencies. IEEE Transactions on Big Data.

Terzi, D. S., Terzi, R., & Sagiroglu, S. (2017) October Big data analytics for network anomaly detection from netflow data. In 2017 International Conference on Computer Science and Engineering (UBMK), pp. 592–597. IEEE.

Thomas, T. P. V., Vijayaraghavan, A. P. & Emmanuel, S. (2020) Machine learning approaches in cyber security analytics. Springer, Singapore.

Ullah, F., & Babar, M. A. (2019). An architecture-driven adaptation approach for big data cyber security analytics. In 2019 IEEE International Conference on Software Architecture (ICSA), pp. 41–50. IEEE.

Wall, D. S. (2018), How big data feeds big crime. Global History: A Journal of Contemporary World Affairs.

Wang, L., & Alexander, C. A. (2015). Big data in distributed analytics, cybersecurity, cyber warfare and digital forensics. Digital Technologies, 1(1), 22–27.

Yetis, Y., Sara, R. G., Erol, B. A., Kaplan, H., Akuzum, A., & Jamshidi, M. (2016). Application of big data analytics via cloud computing. In 2016 World Automation Congress (WAC), pp. 1–5. IEEE.

Zhang, C., Shen, X., Pei, X., & Yao, Y. (2016). Applying big data analytics into network security: Challenges, techniques and outlooks. In 2016 IEEE International Conference on Smart Cloud (SmartCloud), pp. 325–329. IEEE.

Titel: Big Data Analytics and Cybersecurity: Emerging Trends
verfasst von: Sakshi Aggarwal
Stavros Sindakis
Verlag: Springer Singapore
Buch: Big Data Analytics in Cognitive Social Media and Literary Texts
Print ISBN: 978-981-16-4728-4

Electronic ISBN: 978-981-16-4729-1

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-981-16-4729-1_8

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