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.
Contents
1.0 Introduction
1.1 Background of the study
1.2 Problem Statement
1.3 Aims and Objectives of the study
1.4 Research Questions
1.5 Research hypotheses
1.6 Significance of the study
1.7 Scope of the study
1.8 Limitation of the study
2.1 INTRODUCTION
2.2 REVIEW/EXPLANATION OF IMPORTANT/RELEVANT TERMS AND TECHNOLOGIES
2.2.1 Concept of Critical Information Structure
2.2.2 Concept of Big Data
2.2.3 Concept of Big Data Analytics
2.2.4 Overview of Cyber-Crime and Cybersecurity
2.2.5 Goals of Cyber Security
2.2.6 E-crimes that are Peculiar to Nigeria
2.2.7 Concept of Cyber-Attack
2.2.8 Big Data Technologies
2.2.9 Threat detection with Big Data Analytics
2.2.10 Security Analytics With Big Data Analytics
2.2.11 Big Data Mechanism In Analytics Cybercrime
2.2.12 Challenges To Security From The Production, Storage, And Use Of Big Data
2.2.13 Best Practices For Managing Big Data In An Organization, From a Security Perspective
2.2.14 Technological Solutions Available To Secure Big Data And Ensure It’s Gathered And Used Properly
2.2.15 Strategic And Tactical Policy Approaches Exist To Do The Same
2.2.16 How The Use Of Big Data Different To The Use Of Large Datasets In The Past
2.2.17 How Companies Can Ensure And Prove Compliance While Using Big Data
2.2.18 How Traditional Notions Of Information Lifecycle Management Relate To Big Data
2.2.19 How Governance Frameworks Can Be Adapted To Handle Big Data Security Issues And Risk
2.3 REVIEW OF SIMILAR EXISTING SYSTEMS/PREVIOUS RELATED WORKS
2.3.1 SUMMARY OF RELATED WORK
2.4 IDENTIFICATION OF GAP FROM REVIEWED LITERATURE
3.1 Introduction
3.2 Research Design
3.3 Population of the Study
3.4 Sample and Sampling Techniques
3.4.1 Sample Size
3.4.2 Sample Technique
3.5 Method of Data Collection Result
3.5.1 Primary
3.5.2 Instrument of Data Collection
3.5.3 Administration of Instrument
3.5.4 Description Questionnaire
3.5.5 Secondary Data
3.6 Variables and Measurement
3.7 Method of Data Analysis
3.7.1 Non-inferential Techniques
3.7.2 Inferential Techniques
3.8 Ethical Consideration
3.9 Summary
4.1 Introduction
5.1 Summary of findings
5.2 Conclusion and Recommendation
Research Objectives and Themes
The primary research objective is to investigate the efficacy and implementation of big data analytics as a technique for protecting critical information infrastructure against cyber-attacks within Nigerian government agencies. It analyzes the current extent of adoption and identifies key institutional challenges hindering the full integration of these technologies.
- Efficacy of big data analytics in cybersecurity threat detection.
- Implementation status of data analytics within government institutions (JAMB and INEC).
- Barriers such as high costs, data silos, and personnel expertise.
- Statistical validation of security benefits through binary logistic regression analysis.
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1.0 Introduction
In 2016, BT, the telecoms company that owns and maintains the physical infrastructure that makes up the UK's broadband network, experienced an outage of a portion of its broadband services, causing hundreds of thousands of customers (including businesses) to lose Internet and phone connections for approximately two hours (Williams, 2016). This was the largest and most extensive network breakdown in years, according to the news item. Despite the fact that the corporation denies it and blames the network outage on a malfunctioning router, it has been speculated that the outage was caused by a cyber-attack. Whether BT's explanation for the outage (a malfunctioning router) is correct, the point is that it is definitely feasible to conduct a cyber-attack that may bring an organization's infrastructure down. What if this was a cyber-attack that affected more routers and lasted days rather than hours? For instance, the devastating effects on the country's economy, not to mention the lives lost when emergency services lost communication? On October 19, 2020, IBM researchers discovered vizom, a new type of stealthy malware that targets Brazilian account holders using remote overlay assaults according to Guillermo (2014) as cited in Brewer (2021). It is currently being used in a campaign in Brazil that aims to compromise bank accounts through online financial services. Due to the coronavirus pandemic, Vizom poses as a popular video conferencing software, which is now critical to businesses and social life (Brewer, 2021). The problem with such attacks is that they can eventually lead to a cascading failure of inter-bank funding, triggering a tipping point for a broader systemic liquidity crisis. In both of these scenarios, the organizations' operations are so intertwined with other organizations in their respective countries that their failure will inevitably trigger a domino effect, causing these other or related organizations to fail. As a result, the safeguarding of such infrastructures, also known as critical information infrastructures, is seen as a national security issue.
Summary of Chapters
CHAPTER ONE: Provides an introduction and context to the study by discussing the impact of cyber-attacks on critical infrastructure and establishing the research objectives.
CHAPTER TWO: Reviews literature regarding big data concepts, cyber-attack typologies, and existing systems to provide a theoretical foundation for the research.
CHAPTER THREE: Details the research methodology, including the survey design, population sampling (JAMB/INEC), and analytical tools used for the study.
CHAPTER FOUR: Presents the analysis of survey data and discusses the findings regarding the effectiveness and implementation levels of big data analytics.
CHAPTER FIVE: Summarizes the study’s findings, draws conclusions, and provides recommendations for the adoption of big data analytics in Nigerian institutions.
Keywords
Big Data Analytics, Cybersecurity, Critical Information Infrastructure, Cyber-attacks, Threat Detection, Data Silos, Network Security, Information Protection, Nigeria, Regression Analysis, Malware, Prevention Techniques, Data Mining, Digital Forensics, Institutional Implementation.
Frequently Asked Questions
What is the core focus of this research?
The research focuses on the implementation and effectiveness of using big data analytics as a specialized cybersecurity technique to protect critical information systems against modern cyber threats.
What are the primary themes discussed in the work?
The work covers cybercrime evolution, the specific technicalities of big data analytics in threat detection, security governance, and the practical challenges of implementation in large organizations.
What is the ultimate research objective?
The study aims to determine if big data analytics can serve as an effective protection mechanism and to evaluate the current adoption levels in Nigerian government agencies.
Which scientific methodology is applied?
The researcher utilizes a survey-based methodology, collecting primary data from government staff and applying binary logistic regression models to test research hypotheses.
What topics does the main corpus cover?
The main part of the book addresses the definitions of critical infrastructure, various types of cyber-attacks (such as botnets and ransomware), technical solutions like Hadoop, and best practices for organizational security.
What defines the core set of keywords for this work?
The core keywords center around big data analytics, critical infrastructure protection, threat detection, and organizational change management within the sphere of cybersecurity.
How does the work explain the impact of persistent threats?
It highlights that modern threats like stealthy malware often go undetected by traditional signature-based systems, necessitating faster, data-driven detection methods.
What conclusion does the author reach regarding Nigerian organizations?
The author concludes that while big data analytics offers significant security advantages, there is a low level of implementation in the studied Nigerian agencies, primarily due to financial, time, and structural factors.
- Arbeit zitieren
- Torty Vincent (Autor:in), Implentation of Critical Information Infrastructure Protection Techniques against Cyber Attacks, München, GRIN Verlag, https://www.grin.com/document/1224910
