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Cybersecurity Governance: Methodology and Analysis

1. Admassa, W. S., Munaye, Y. Y., & Diro, A. A. (2024).

Identified Problem: Problems of adopting advanced cybersecurity and its intersection with other frameworks and systems.

Research Questions: How can present cybersecurity problems be addressed through appropriate frameworks?

Methodology: Literature review and qualitative analysis only.

Outcomes: Explored existing studies on cybersecurity frameworks and generated knowledge for future work.

Alignment: A qualitative approach was appropriate for discussing general problems, but the approach presented rather vague solutions.

Alternative Approach: A mixed-methods study could have provided empirical support for the proposed solutions.

Ethical Issues: The possible factors related to bias when evaluating the current strategies and maintaining an objective stance in the recommendation.

2. Dillon, R., & Tan, K. L. (2024)

Identified Problem: Cybersecurity Skills Gap: Southeast Asia’s Unseen Crisis.

Research Questions: Indeed, workforce training and education in cybersecurity open the following questions: What strategies can enhance these objectives?

Methodology: Conducted from surveys and from case studies.

Outcomes: Skills shortage in the workforce and reforms in education, which have been underlined.

Alignment: Analyzing the work results, it can be stated that using both qualitative and quantitative approaches meets the problem and questions.

Alternative Approach: The study could have used a more modern data set to propose further longitudinal measures on the reformation that may be proposed.

Ethical Issues: This paper sought to establish how the consent of the participant in the workforce surveys can be granted while at the same time protecting their privacy in the process.

3. Furnell, S. (2021)

Identified Problem: Current and potential issues that may be witnessed in the global cybersecurity workforce.

Research Questions: Which are the essential competencies in the cybersecurity field, and how can these be trained?

Methodology: Literature synthesis and survey analysis.

Outcomes: Shed light on core skills that needed to be filled and suggested concrete training activities.

Alignment: The chosen methodology was relevant to the problem area, but involved extensive use of secondary data sources.

Alternative Approach: The methodology could have been enriched with primary data from specific interviews with industry leaders.

Ethical Issues: This section takes some measures towards reducing biases inherent in survey sampling and interpretation of results.

4. Handa, A. & Sharma, A. & Shukla, S. K. (2019)

Identified Problem: Machine learning (ML) is not deployed as a primary proactive cybersecurity measure.

Research Questions: Which specific strategies can be used to apply the concept of ML in the realm of cybersecurity in order to protect computer networks and disrupt cyberattacks?

Methodology: Review of the selected ML techniques in cybersecurity applications.

Outcomes: Gave a brief of ML methods and recognized possible directions in the aim of the research.

Alignment: The systematic review complemented the presented text, but more practice-oriented references were missing.

Alternative Approach: Perhaps empirical credibility tests for ML models could also improve the reliability.

Ethical Issues: Presentation of prejudices in the choice of review studies.

5. Li, L., H, W., Xu, L., Ash, I., Anwar, M., & Yuan, X. (2019).

Identified Problem: Lack of cybersecurity policies in the organization or employees are not aware of policies in the organization.

Research Questions: What happens when employees are made aware of company policies?

Methodology: Quantitative surveys.

Outcomes: Shown that people who were more aware of the policies in play were more likely to act more securely.

Alignment: The survey method was suitable to obtain employees’ attitudes and perceptions.

Alternative Approach: Adding qualitative interviews could give a deeper rationale for stock-picking decisions.

Ethical Issues: Preservation of employee anonymity in the responses.

6. Li, Y., & Liu, Q. (2021)

Identified Problem: New threats and threats’ insufficient control.

Research Questions: What are the phenomena evident from recent cyber unrest?

Methodology: Literature review.

Outcomes: These include: Some of the trends that have been identified here include; Some of the voids that have been determined from the study include;

Alignment: While the presented approach fitted well, there was no confirmation in the paper.

Alternative Approach: Implementing this by including a survey of what other industry programs are doing could go a long way in offering practical relativity.

Ethical Issues: Preventing plagiarism in synthesizing results gathered from literature research.

7. Nizich, M. (2023)

Identified Problem: Cybersecurity: Training the workforce for the future.

Research Questions: This study aims to identify relevant competencies for the future cybersecurity workforce.

Methodology: Case studies and workforce are the commonly used methods in undertaking a philosophy of the workforce.

Outcomes: Proposed guidelines for training frameworks addressed toward future development.

Alignment: The methodology was successful in answering the questions with the exception that they were cross-sectional; therefore a longitudinal tracking should be incorporated.

Alternative Approach: Including global perspectives could improve the results' applicability.

Ethical Issues: Promoting paradigms that respect workforce diversity: a comment on Hamlin et al.

8. Safitra, M. F., Lubis, M., & Fakhrurroja, H (2023)

Identified Problem: Lack of proficient structures on managing and reducing cybersecurity threats.

Research Questions: How do proactive frameworks help to mitigate cybersecurity threats?

Methodology: Crossover of quantitative type of analyses and qualitative case studies.

Outcomes: Suggested the implementation of a mixed approach for the enhancement of risk management.

Alignment: Qualitative and quantitative approaches were appropriate for studying emergent theories and confirming developed theories.

Alternative Approach: The incorporation of field trials may have a way of proving practical applicability.

Ethical Issues: How best to maintain the bibliographic framework numerical evaluation transparency.

9. Shaukat, K., Luo, L., Varadharajan, Varadharajan, K., Hameed, I. A., & Xu, M. (2020)

Identified Problem: Lacking and ineffective methods in employing it during behavior-based threat estimation.

Research Questions: Which is the best and most efficient ML method for cybersecurity?

Methodology: Introduction to the machinery learning techniques and cases.

Outcomes: Recognized the best data learning approaches and further enhancements.

Alignment: The survey approach correlated well with the problem and its exploratory nature.

Alternative Approach: Introducing practical tests regarding ML models could enhance the realism of the applicability.

Ethical Issues: Countering malicious use of the ML implementation in cybersecurity.

10. Xu, S. (2019)

Identified Problem: Lack of comprehension of the security environment in cyberspace.

Research Questions: Understanding the determinants of cybersecurity dynamics:

Methodology: Theoretical modeling.

Outcomes: Written the basic hypotheses on dynamic network protection.

Alignment: Theoretical modeling was appropriate to the conceptual problem that was posed.

Alternative Approach: Pointing at possible additions, it is possible to strengthen the study's findings by employing empirical validation at this stage.

Ethical Issues: Puzzle of transparency to model development.

References

Admass, W. S., Munaye, Y. Y., & Diro, A. A. (2024). Cyber security: State of the art, challenges and future directions. Cyber Security and Applications, 2, 100031.

Dillon, R., & Tan, K. L. (2024). Cybersecurity workforce landscape, education, and industry growth prospects in Southeast Asia. Journal of Tropical Futures, 1(2), 172-181.

Furnell, S. (2021). The cybersecurity workforce and skills. Computers & Security, 100, 102080.

Handa, A., Sharma, A., & Shukla, S. K. (2019). Machine learning in cybersecurity: A review. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(4), e1306.

Li, L., He, W., Xu, L., Ash, I., Anwar, M., & Yuan, X. (2019). Investigating the impact of cybersecurity policy awareness on employees’ cybersecurity behavior. International Journal of Information Management, 45, 13-24.

Li, Y., & Liu, Q. (2021). A comprehensive review study of cyber-attacks and cybersecurity: Emerging trends and recent developments. Energy Reports, 7, 8176-8186.

Nizich, M. (2023). Preparing the cybersecurity workforce of tomorrow. The Cybersecurity Workforce of Tomorrow, 117-146.

Safitra, M. F., Lubis, M., & Fakhrurroja, H. (2023). Counterattacking cyber threats: A framework for the future of cybersecurity. Sustainability, 15(18), 13369.

Shaukat, K., Luo, S., Varadharajan, V., Hameed, I. A., & Xu, M. (2020). A survey on machine learning techniques for cyber security in the last decade. IEEE Access, 8, 222310-222354.

Xu, S. (2019). Cybersecurity dynamics: A foundation for the science of cybersecurity. Proactive and Dynamic Network Defense, 1-31.