Big Data Analytics in Cyber Security: Network Traffic and Attacks

References

• Ponemon I. Big data analytics in cyber defense. Ponemon Institute; Feb 2013. Report No: EB-7499 02.13.
   Google Scholar
• Gjelten T. Cyberattacks, terrorism top U.S. security threat report. Washington (DC): National Public Radio; (http://www.npr.org); 2013 Mar 12. http://www.npr.org/2013/03/12/174135800/cyber-attacks-terrorism-top-u-s-security-threat-report.
   Google Scholar
• Flowers A, Zeadally S. US policy on active cyber defense. J Homel Secur Emerg Manag. 2014;11(2):289–308. doi:https://doi.org/10.1515/jhsem-2014-0021.
   Web of Science ®Google Scholar
• Pătrascu A, Simion E. Critical infrastructures cyber protection using kernel based supervised learning techniques. MTA Rev Mil Tech Acad Publishing House. 2014;24:59–66.
   Google Scholar
• Crawford S, Piesse D. Cyber insurance, security and data integrity, Part 1: insights into cyber security and risk-2014. Ernst & Young LLP; 2014. Technical Report, p. 1–17.
   Google Scholar
• Youssef A, Emam A. Network intrusion detection using data mining and network behaviour analysis. Int J Comput Sci Inf Technol. 2011;3(6):87–98. doi:https://doi.org/10.5121/ijcsit.
   Google Scholar
• Patel A, Taghavi M, Bakhtiyari K, JúNior JC. An intrusion detection and prevention system in cloud computing: a systematic review. J Netw Comput Appl. 2013;36(1):25–41. doi:https://doi.org/10.1016/j.jnca.2012.08.007.
   Web of Science ®Google Scholar
• Rajesh KV. Big Data analytics: applications and benefits. J Inf Technol. 2013;9:41–51.
   Google Scholar
• Wang L, Randy J. Big Data analytics for disparate data. Am J Intell Syst. 2017;7:39–46.
   Google Scholar
• Han J, Pei J, Kamber M. Data mining: concepts and techniques. New York, USA: Elsevier; 2011.
   Google Scholar
• Rahm E, Do HH. Data cleaning: problems and current approaches. IEEE Data Eng Bull. 2000;23:3–13.
   Google Scholar
• Kewo A, Manembu P, Nielsen PS. Data pre-processing techniques in the regional emission’s load profiles case. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT); 2019 Apr 23; Paris, France: IEEE; p. 2016–21.
   Google Scholar
• Cong Y, Liu J, Fan B, Zeng P, Yu H, Luo J. Online similarity learning for big data with overfitting. IEEE Trans Big Data. 2017 Mar 28;4(1):78–89. doi:https://doi.org/10.1109/TBDATA.2017.2688360.
   Web of Science ®Google Scholar
• Kancharla GR. Feature selection in big data using filter based techniques. 2019 4th MEC International Conference on Big Data and Smart City (ICBDSC); 2019 Jan 15; Muscat, Oman: IEEE; p. 1–7.
   Google Scholar
• Balasubramanian R, Joseph SJ. Intrusion detection on highly imbalance big data using tree based real time intrusion detection system: effects and solutions. Int J Adv Res Comput Commun Eng. 2016;5:27–32.
   Google Scholar
• Talent M. Smarter cities: cleaning electricity, gas and water metered consumption data for social and urban research. J Sustainable Dev Energy Water Environ Syst. 2019 Sep 30;7(3):466–81.
   Google Scholar
• Ezzine I, Benhlima LA. Study of handling missing data methods for big data. 2018 IEEE 5th International Congress on Information Science and Technology (CiSt); 2018 Oct 21, Marrakech, Morocco: IEEE; p. 498–501.
   Google Scholar
• Balzano L, Chi Y, Lu YM. Streaming pca and subspace tracking: the missing data case. Proc IEEE. 2018 Jul 23;106(8):1293–310. doi:https://doi.org/10.1109/JPROC.2018.2847041.
   PubMed Web of Science ®Google Scholar
• Agbehadji IE, Millham RC, Fong SJ, Yang H. Bioinspired computational approach to missing value estimation. Math Probl Eng. 2018;2018:1–16. Article ID 9457821. doi:https://doi.org/10.1155/2018/9457821.
   Web of Science ®Google Scholar
• Chen Y, Li S, Yao J Missing information management for massive sparse data. 2018 IEEE 4th 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); 2018 May 3; IEEE; p. 238–43. doi:https://doi.org/10.1142/S2424835518500273.
   Google Scholar
• Jea KF, Hsu CW, Tang LY A missing data imputation method with distance function. 2018 International Conference on Machine Learning and Cybernetics (ICMLC); 2018 Jul 15; Vol. 2, Chengdu, China: IEEE; p. 450–55.
   Google Scholar
• Petrozziello A, Jordanov I, Sommeregger C. Distributed neural networks for missing big data imputation. 2018 International Joint Conference on Neural Networks (IJCNN); 2018 Jul 8; Rio de Janeiro, Brazil: IEEE; p. 1–8.
   Google Scholar
• Freund JE, Perles BM. Statistics: A first course. 8th ed. New Jersey (USA): Pearson Prentice Hall; 2004.
   Google Scholar
• Wu X, Kumar V. Top 10 algorithms in data mining. New York (USA): CRC Press, Taylor & Francis Group, LLC; 2009.
   Google Scholar
• Wang K, Stolfo S. One-class training for masquerade detection. Workshop on Data Mining for Computer Security; 2003 November; Melbourne (FL). p. 10–19.
   Google Scholar
• Garchery M, Granitzer M Identifying and clustering users for unsupervised intrusion detection in corporate audit sessions. 2019 IEEE International Conference on Cognitive Computing (ICCC) 2019 Jul 8, IEEE. p. 19–27.
   Google Scholar
• Kholidy HA, Abdulrahman AZ, Baiardi F. Data-driven semi-global alignment technique for masquerade detection in stand-alone and cloud computing systems. United States patent US10,193,904. 2019 Jan 29.
   Google Scholar
• Xu S, Lai S, Li Y. A deep learning based framework for cloud masquerade attack detection. 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC); 2018 Nov 17, Orlando, Florida, USA: IEEE; p. 1–2.
   Google Scholar
• Camiña JB, Medina-Pérez MA, Monroy R, Loyola-González O, Villanueva LA, Gurrola LC. Bagging-RandomMiner: a one-class classifier for file access-based masquerade detection. Mach Vis Appl. 2019;30(5):959–74. doi:https://doi.org/10.1007/s00138-018-0957-4.
   Web of Science ®Google Scholar
• Wang J, Cai L, Yu A, Zhu M, Meng D. TempatMDS: a masquerade detection system based on temporal and spatial analysis of file access records. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE); 2018 Aug 1; New York, USA: IEEE; p. 360–71.
   Google Scholar