Cyber Security And Risk Management - Read At Least Two (2) A ✓ Solved

Cyber Security and Risk Management Read at least two (2) academ

Read at least two (2) academically reviewed articles on Cyber Security and Risk Management and complete the following activities: (Wikipedia articles will not be accepted.)

1. Summarize the two (2) articles in 300 words or more. Please use your own words. No copy-and-paste.

2. Based on your article review and the assigned reading, discuss the relationship between cyber security and risk management.

3. As an IT manager, discuss how you will use the concepts discussed in the four articles in the management of IT risks within your company.

4. Dashboards are used in thousands of businesses every day. Review this dashboard and discuss how the government, hospitals, and others could benefit by something like this: Discuss how risk management comes into play here.

Paper For Above Instructions

Introduction

Cybersecurity and risk management are critical fields that have garnered significant attention in recent years due to the rising number of cyber threats affecting organizations worldwide. This paper will summarize two academically reviewed articles that explore key aspects of these fields and discuss their interrelationship. Furthermore, it will examine how an IT manager can leverage these concepts to address IT risks within a company and evaluate the benefits of risk management dashboards in various sectors.

Article Summaries

The first article reviewed is titled "An Integrated Cyber Security Risk Management Approach for a Cyber-Physical System" by Halima Ibrahim Kure (2018). This study presents a comprehensive framework for managing cybersecurity risks in cyber-physical systems (CPS). The author emphasizes the importance of integrating cybersecurity measures with risk management practices to protect CPS from potential threats. The article discusses various methods for risk assessment, including qualitative and quantitative approaches, and highlights the need for continuous monitoring and updating of security measures to adapt to evolving threats. The author concludes that adopting an integrated approach allows organizations to mitigate risks more effectively and enhance overall resilience against cyber-attacks.

The second article, "Machine learning and deep learning methods for cybersecurity" by Xin et al. (2018), explores innovative approaches to cybersecurity using advanced technologies. The authors examine how machine learning and deep learning can be utilized to detect and respond to cyber threats dynamically. The article discusses various algorithms and their applications in different layers of cybersecurity, stressing the significance of data analysis in identifying patterns indicative of potential threats. The authors suggest that leveraging AI technologies can significantly improve the efficiency and effectiveness of cybersecurity measures, thus contributing to a more robust risk management framework.

Relationship between Cybersecurity and Risk Management

Cybersecurity and risk management share a symbiotic relationship, as effective risk management is essential for enhancing an organization's cybersecurity posture. Cybersecurity focuses on protecting information integrity, confidentiality, and availability, while risk management involves identifying, assessing, and mitigating potential threats and vulnerabilities. Organizations expose themselves to risks when they fail to adequately protect sensitive data, leading to significant repercussions, including financial losses and reputational damage. Therefore, risk management practices are indispensable for organizations to anticipate cybersecurity threats and develop strategies to minimize their impact (Li et al., 2019). This relationship underscores the necessity of integrating cybersecurity measures within risk management frameworks to ensure comprehensive protection against cyber threats.

Application as an IT Manager

As an IT manager, the insights derived from the reviewed articles are invaluable for managing IT risks within an organization. Firstly, integrating a robust cybersecurity risk management framework, such as the one proposed by Kure (2018), will facilitate a systematic approach to identifying and assessing cybersecurity threats. By employing a combination of qualitative and quantitative risk assessment techniques, I can prioritize risks based on their potential impact and likelihood, enabling targeted interventions to mitigate high-priority threats.

Secondly, the implementation of machine learning and deep learning technologies, as discussed by Xin et al. (2018), presents an opportunity to enhance threat detection capabilities. By automating the analysis of network traffic and user behavior, these technologies can provide real-time insights into potential threats, allowing for proactive defense measures. Training staff on recognizing cybersecurity threats and employing advanced tools will create a culture of security awareness within the organization.

Benefits of Risk Management Dashboards

Dashboards play a pivotal role in aiding organizations, including governments and hospitals, in visualizing and managing risks effectively. These dashboards aggregate data from various sources, providing stakeholders with a comprehensive overview of risk indicators and cybersecurity metrics. For example, a government agency can utilize a dashboard to monitor cyber attacks in real-time, ensuring timely responses to potential breaches (Sun et al., 2018). In hospitals, dashboards can be instrumental in tracking patient data security, helping administrators identify vulnerabilities and take proactive measures to bolster defenses against cyber threats.

In conclusion, the interplay between cybersecurity and risk management is vital for organizations to navigate the complexities of the digital landscape. By harnessing the insights from academic literature and employing innovative technologies, IT managers can develop effective strategies for managing IT risks, thereby safeguarding sensitive information and maintaining organizational integrity.

References

  • Kure, H. I. (2018). An Integrated Cyber Security Risk Management Approach for a Cyber-Physical System.
  • Xin, Y., Kong, L., Liu, Z., Chen, Y., Li, Y., Zhu, H., & Wang, C. (2018). Machine learning and deep learning methods for cybersecurity. IEEE Access, 6.
  • Finnemore, M., & Hollis, D. B. (2016). Constructing norms for global cybersecurity. American Journal of International Law, 110(3).
  • Li, L. et al. (2019). Investigating the impact of cybersecurity policy awareness on employees’ cybersecurity behavior. International Journal of Information Management, 45, 13-24.
  • Sun, N., Zhang, J., Rimba, P., Gao, S., Zhang, L. Y., & Xiang, Y. (2018). Data-driven cybersecurity incident prediction: A survey. IEEE Communications Surveys & Tutorials, 21(2).
  • ISO/IEC 27001. (2013). Information technology — Security techniques — Information security management systems — Requirements.
  • Stoneburner, G., Goguen, A., & Feringa, A. (2002). Risk Management Guide for Information Technology Systems. NIST Special Publication 800-30.
  • Anderson, R. (2020). Security Engineering: A Guide to Building Dependable Distributed Systems. Wiley.
  • Gordon, L. A., Loeb, M. P., & Zhou, L. (2016). Integrating Cybersecurity and Business Strategy. Journal of Business Strategy, 37(3).
  • Kumar, R. et al. (2020). A Survey on Cybersecurity Risk Management Frameworks. Journal of Information Security and Applications, 54.

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