Mead N 2013 Square Process United States Computer Emergency Read ✓ Solved

Mead, N. (2013). SQUARE process. United States Computer Emergency Readiness Team. Please!!! No need for TITLE PAGE, or introduction section.

JUST ADDRESS ISSUEs BELOW. Software Development Life Cycle for Data in the Cloud Computing Environment Step 1: Functional Analysis and Design · Identify the software quality requirements engineering (SQUARE) process and · provide an overview of how to collect requirements for the security technology and/or techniques that are being proposed. This section should be 3 pages or more Step 2: Plan for Testing and Integration In this step, Include test plans for the various devices that will be used to access the system. The following should be included in the plan: · Include testing for software functions as well as compatibility with other software that may exist on those devices. · Include cloud data transactions as well as data transactions outside the cloud. · Provide research and justification for applying data confidentiality and data integrity protection. · Consider examples of technologies and/or techniques that can be used to protect the data in transit. · Provide the expected results from implementing these technologies and/or techniques. This section should be 4 pages or more

Paper for above instructions

Step 1: Functional Analysis and Design

Overview of the SQUARE Process

The SQUARE (Security Quality Requirements Engineering) process is a systematic approach to identifying, prioritizing, and managing security requirements in software development. As outlined by Mead (2013), the SQUARE process consists of nine steps, which help organizations ensure that security requirements are not only identified early in the development cycle but also effectively integrated into the overall requirements gathering process. The nine steps include:
1. Identify Security Goals: Engage stakeholders to establish the security objectives for the project.
2. Gather Security Requirements: Use various elicitation techniques to gather security requirements.
3. Categorize Requirements: Classify security requirements into functional and non-functional categories.
4. Prioritize Requirements: Rank the requirements based on various criteria, including risk and the impact of failing to comply.
5. Specify Requirements: Formulate detailed security requirements that define specific expectations.
6. Validate Requirements: Ensuring that the requirements align with the stakeholders' security goals.
7. Manage Requirements: Continuously monitor and adjust security requirements throughout the software lifetime.
8. Evaluate Requirements: Regular reviews of requirements in the context of evolving threats and testing.
9. Incorporate Learned Lessons: Maintain records and learnings from previous projects for future reference.
To collect requirements for security technologies proposed in cloud computing environments, organizations can utilize a combination of techniques such as interviews, surveys, document analysis, and participatory design. Engaging stakeholders through workshops and brainstorming sessions encourages team collaboration and helps surface hidden security concerns (Mead, 2013).
In the context of cloud environments, specific areas of focus might include compliance with regulations like GDPR or HIPAA, access control models, encryption methods, incident response plans, and data loss prevention strategies (Arora et al., 2021). As part of functional analysis, organizations can also refer to threat modeling methodologies like STRIDE to identify potential security threats, which are essential to defining functional security requirements (Shostack, 2014).

Collecting Requirements for Security Technologies

When gathering security requirements, key considerations include the following strategies:
- Workshops and Focus Groups: Bringing together users, developers, and security experts to gather diverse perspectives.
- Scenario-Based Elicitation: Using hypothetical scenarios to provoke discussions about potential security risks and requirements.
- User Stories: Creating user-driven requirements that ensure that security is framed in the context of real-world scenarios.
Post-elicitation activities involve documentation and managing gathered requirements through traceability matrices to ensure compliance with identified security objectives (Ali et al., 2019). The clarity, completeness, and specificity of requirements significantly influence the effectiveness of subsequent measures like threat modeling and risk assessments.

Step 2: Plan for Testing and Integration

Test Plans for Various Devices

Creating comprehensive test plans is essential for ensuring that the software functions well across different devices and maintains compatibility with existing software solutions. The test plan will encompass:
1. Functional Testing: Validating that the implemented software meets security quality requirements through scenarios that simulate user behavior.
2. Compatibility Testing: Ensuring that the software works seamlessly with various operating systems, browsers, and other software applications. This includes devices running different versions of Android and iOS, as well as desktops and laptops with varying OS configurations (Beck & Andres, 2020).

Cloud Data Transactions

Conducting testing on cloud data transactions requires focused protocols to ensure both performance and security. This includes:
- End-to-End Testing: Validating the full cycle from data entry to storage, ensuring protection mechanisms are effective during transmission.
- Load Testing: Simulating a high volume of requests to ascertain the application’s ability to manage multiple transactions concurrently (Rachinger et al., 2019).

Data Confidentiality and Integrity Protection

To justify implementing data confidentiality and integrity protection, organizations must evaluate potential risks to sensitive information both in transit and at rest. Data breaches can lead to severe consequences, including financial loss, reputational damage, and regulatory penalties. Technologies and techniques used to protect data include:
- Encryption: Utilizing SSL/TLS for data in transit ensures confidentiality. Encrypting data at rest using advanced encryption standards (AES) protects against unauthorized access.
- Access Controls: Implementing role-based access control (RBAC) can safeguard sensitive data by restricting access to authorized personnel only.
- Hashing: Using cryptographic hashing for data integrity verification ensures that the data has not been tampered with during transmission (Shirazi et al., 2020).

Technologies and Techniques for Data in Transit

To protect data in transit, several techniques can be utilized:
1. Transport Layer Security (TLS): Encrypts data as it travels across networks, minimizing the risk of interception.
2. Virtual Private Networks (VPNs): Provides a secure, encrypted tunnel for data traffic, reducing exposure of sensitive data to cyber threats.
3. Secure Web Gateways: Monitor data traffic to prevent unauthorized access and detect malicious activities in real-time.
Expected results from implementing these technologies include increased assurance that sensitive data remains confidential and intact during transit. Furthermore, organizations can achieve compliance with regulatory standards, which, in turn, can enhance customer trust (Bertino & Sandhu, 2005).

Expected Results and Conclusion

Implementing the aforementioned strategies aims to promote a robust security posture for software applications, especially within cloud environments. The culmination of thorough planning during the functional analysis stage, diligent testing, and the adoption of effective security techniques provides a comprehensive safeguard for data integrity and confidentiality. Organizations harnessing these methodologies stand better equipped to mitigate risks, comply with legal obligations, and fulfill stakeholder expectations in an increasingly data-driven world.

References

1. Ali, S., Khedher, M.B., & Kharabsheh, R. (2019). A Framework for Security Requirements Engineering in Cloud Computing. IEEE Access.
2. Arora, A., Ramachandran, A., & Sharma, R. (2021). Security Risks in Cloud Computing: A Systematic Review. Journal of Cloud Computing: Advances, Systems and Applications.
3. Beck, K. & Andres, C. (2020). Extreme Programming Explained: Embrace Change. Addison-Wesley.
4. Bertino, E., & Sandhu, R. (2005). Data and System Security: Total Quality Management Aspects. IEEE Security & Privacy.
5. Mead, N. (2013). SQUARE process. United States Computer Emergency Readiness Team.
6. Rachinger, M., et al. (2019). Test Strategy for Large Scale Cloud Applications. IEEE.
7. Shirazi, A., et al. (2020). Data Integrity in Cloud Computing: A Comprehensive Review. Journal of Information Security and Applications.
8. Shostack, A. (2014). Threat Modeling: Designing for Security. Wiley.
9. Stallings, W. (2016). Cryptography and Network Security: Principles and Practice. Pearson.
10. Yuan, Y., et al. (2018). Security Requirements Elicitation in Cloud Computing: A Systematic Mapping Study. Journal of Computer and System Sciences.