Week 6 Full Objectives Describe Threat Modeling Identify several ✓ Solved

Assignment: Threat Modeling

A new medium-sized health care facility just opened, and you are hired as the CIO. The CEO is somewhat technical and has tasked you with creating a threat model. The CEO needs to decide from three selected models but needs your recommendation.

Review this week’s readings, conduct your own research, then choose a model to recommend with proper justifications. Items to include (at a minimum) are:

  • User authentication and credentials with third-party applications

  • Three common security risks with ratings: low, medium, or high

  • Justification of your threat model (why it was chosen over the other two: compare and contrast)

You will research several threat models as they apply to the health care industry, summarize three models, and choose one as a recommendation to the CEO in a summary with a model using UML Diagrams (Do not copy and paste images from the Internet).

In your research paper, be sure to discuss the security risks and assign a label of low, medium, or high risks, and the CEO will make the determination to accept the risks or mitigate them.

Paper For Above Instructions

Introduction

Threat modeling is a crucial aspect of security management in healthcare settings, where the protection of sensitive patient information is paramount. As the Chief Information Officer (CIO) of a newly established medium-sized healthcare facility, it is essential to create a robust threat model that can guide our security architecture and decision-making processes. This paper will evaluate three distinct security models, assess their applicability to our environment, and recommend the most suitable framework for our needs.

Overview of the Security Models

In selecting a threat model, three established frameworks are considered: the Bell-LaPadula Model, the Biba Model, and the Clark-Wilson Model. Each of these models approaches information security with different principles and focuses, which will be analyzed in this section.

1. Bell-LaPadula Model: This model emphasizes confidentiality and operates on the principle that unauthorized users should not read classified information. It uses a lattice structure with access controls that enforce "no read up" and "no write down" policies. This model is mainly suited for environments where data confidentiality is critical and is effective in preventing forced breaches from lower to higher classified information levels (Bishop, 2003).

2. Biba Model: In contrast to the Bell-LaPadula Model, the Biba Model focuses on integrity rather than confidentiality. It operates on rules that ensure that users cannot modify data at a higher integrity level or read data from a lower integrity level. This model is vital for systems where the integrity of data is necessary for maintaining trustworthiness in information (Bishop, 2003).

3. Clark-Wilson Model: This model stresses the necessity of well-formed transactions and separation of duties. It is designed to maintain data integrity through controlled access and auditing (Huang & O'Connor, 2017). By implementing this model, organizations can ensure that operations are conducted in a manner that protects data integrity while also complying with regulatory standards.

User Authentication and Credentials

User authentication is crucial in the healthcare industry, particularly when dealing with third-party applications that may access sensitive patient data. A robust authentication system that includes multi-factor authentication (MFA) can mitigate the risk of unauthorized access. It is essential to establish protocols that require strong passwords and possibly biometric verification, ensuring that only authorized personnel are able to handle sensitive information.

Identification of Security Risks

When evaluating the health facility’s cybersecurity posture, three common security risks were identified and categorized as follows:

  • Risk of Data Breaches (High): Given the valuable nature of healthcare data, unauthorized access can lead to severe financial and reputational damage.

  • Ransomware Attacks (Medium): The healthcare sector has been a popular target for ransomware attacks, which can disrupt services and cause data loss.

  • Insider Threats (Low): While less frequent, insider incidents can compromise data by either negligence or malicious intent from within the organization.

Justification of the Recommended Threat Model

After thorough consideration of the models outlined, the Clark-Wilson Model is recommended for the healthcare facility. This decision is based on several factors:

1. Integrity Focus: The integrity of healthcare data is paramount; therefore, a model that emphasizes well-formed transactions and separation of duties will effectively safeguard against potential breaches and data manipulation.

2. Compliance and Regulatory Requirements: The Clark-Wilson Model aligns well with compliance frameworks, such as HIPAA, which mandates stringent measures to protect patient data integrity and privacy (Huang & O'Connor, 2017).

3. Practical Implementation: The model's structure allows for straightforward implementation of security controls and auditing measures, which are essential for ongoing security assessments in the healthcare setting.

Conclusion

In conclusion, the Clark-Wilson Model offers a strong combination of security, integrity, and compliance, making it the ideal choice for the new healthcare facility's threat model. By adopting this model, we can establish a proactive security framework that not only protects sensitive data but also instills trust with our patients and stakeholders. Implementing robust user authentication systems and effectively evaluating security risks will further bolster our defenses against the ever-evolving cyber threat landscape.

References

  • Bishop, M. (2003). Computer Security: Art and Science. Boston: Addison-Wesley.

  • Huang, J., & O'Connor, L. (2017). Ensuring Data Integrity: A Multi-Factor Approach. Journal of Healthcare Protection Management, 33(1), 32-45.

  • Ruiz, N., Bargal, S.A., & Sclaroff, S. (2020). Disrupting DeepFakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems. Journal of Computer Vision.

  • Cagnazzo, M., Hertlein, M., Holz, T., & Pohlmann, N. (2018). Threat Modeling for Mobile Health Systems. Security and Privacy in Mobile Health.

  • Harris, S. (2016). All-in-One CISSP Certification Exam Guide. New York: McGraw-Hill.

  • Yuan, H., & He, D. (2021). Cybersecurity Risks and Solutions in Healthcare Sector: A Comprehensive Review. Health Informatics Journal.

  • Hadnagy, C. (2018). Social Engineering: The Science of Human Hacking. Wiley.

  • Gordon, L.A., & Loeb, M.P. (2002). The Economics of Information Security Investment. ACM Transactions on Information Systems Security.

  • McCarty, M. (2014). Understanding What Medical Data Breaches Cost Hospitals. Journal of Medical Systems.

  • Apte, A., & Mason, S. (2013). Data Security and Privacy in Healthcare: Issues, Challenges and Solutions. Health Information Management Journal.