Implentation of Critical Information Infrastructure Protection Techniques against Cyber Attacks
Autor: | Torty Vincent |
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EAN: | 9783346654489 |
eBook Format: | PDF/ePUB |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 02.06.2022 |
Kategorie: | |
Schlagworte: | Big Data Analytics Cybercrime Cybersecurity |
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Master's Thesis in the subject Computer Science - IT-Security, , language: English, abstract: Big Data analytics is the act of analysing data to discover hidden patterns, trends, preferences, and other important information in order to detect infiltration, prevent fraud, and possibly make the right judgements. This study was carried out to investigate the implementation of big data analytics as a technique for information protection against cyber attacks. This study specifically examined the extent of big data analytics implementation and the challenges militating the adoption and full implementation. The survey research design was employed and a total of one hundred and twenty-one staff members of the Joint Admission and Matriculation Board (JAMB) and the Independent National Electoral Commission (INEC) were enrolled in the study. The instrumentation of questionnaire was used to elicit information from the study participants. The data collected were analysed using the binary logistic regression. Findings from the study revealed that big data analytics provides better advantage to information protection against cyber attacks. Also, the findings showed that to a significant extent, big data analytics has not been full adopted and implemented by institution and organizations in Nigeria. This gap was detected in this study to be a result of high cost of hiring expert personnel, time and large quantity of silos. These factors indirectly affects the decision of top management regarding the adoption and implementation of big data analytics. This study recommends the adoption and implementation of big data analytics by organizations and institutions in Nigeria. Adequate training should be provided for staff members whose job description involves interacting with big data.