CISA-KR 문제 411
The greatest resulting impact of project reporting not accurately reflecting current progress is that the project steering committee cannot provide effective governance. The project steering committee is a group of senior executives or stakeholders who oversee the project and provide strategic direction, guidance, and support. The project steering committee relies on accurate and timely project reporting to monitor the project's status, performance, risks, issues, and changes. If the project reporting is inaccurate, the project steering committee cannot make informed decisions, resolve problems, allocate resources, or ensure alignment with the organizational goals and objectives.
The other options are not as impactful as option C. The project manager will have to be replaced is a possible consequence, but not the greatest impact, of inaccurate project reporting. The project manager is responsible for planning, executing, monitoring, controlling, and closing the project. The project manager may face disciplinary actions or termination if they fail to provide accurate and honest project reporting. However, this does not necessarily affect the overall governance of the project. The project reporting to the board of directors will be incomplete is a potential risk, but not the greatest impact, of inaccurate project reporting.
The board of directors is the highest governing body of an organization that sets the vision, mission, values, and policies. The board of directors may receive periodic or ad hoc project reporting to ensure that the project is aligned with the organizational strategy and delivers value. If the project reporting is inaccurate, the board of directors may lose confidence in the project or intervene in its management. However, this does not directly affect the day-to-day governance of the project. The project will not withstand a quality assurance (QA) review is a possible outcome, but not the greatest impact, of inaccurate project reporting. A quality assurance review is a process to evaluate the quality of the project's processes and deliverables against predefined standards and criteria. A quality assurance review may reveal discrepancies or errors in the project reporting that may affect the credibility and reliability of the project. However, this does not necessarily affect the governance of the project. References: Project Steering Committee - Roles & Responsibilities, Project Reporting Best Practices, Quality Assurance in Project Management
CISA-KR 문제 412
Hashing is a technique that transforms data into a fixed-length value, called a hash or a digest, that uniquely represents the original data. Hashing can be used to validate the integrity of data communicated between production databases and a big data analytics system by comparing the hash values of the data before and after the communication. If the hash values match, the data has not been altered; if they differ, the data has been tampered with or corrupted. Hashing is a better security control than encrypting, running and comparing the count function, or hosting a digital certificate for this purpose because:
Encrypting in-scope data sets can protect the confidentiality of the data, but not necessarily the integrity.
Encryption algorithms can be broken or bypassed by malicious actors, or encryption keys can be compromised or lost. Moreover, encryption adds overhead to the communication process and may affect the performance of the big data analytics system.
Running and comparing the count function within the in-scope data sets can only verify the number of records or elements in the data sets, but not the content or quality of the data. The count function cannot detect any changes or errors in the data values, such as missing, duplicated, corrupted, or manipulated data.
Hosting a digital certificate for in-scope data sets can provide authentication and non-repudiation for the data sources, but not integrity for the data itself. A digital certificate is a document that contains information about the identity and public key of an entity, such as a person, organization, or device. A digital certificate does not contain or verify the actual data that is communicated between production databases and a big data analytics system.
References:
Ensuring Data Integrity with Hash Codes
Database Security: An Essential Guide
Control methods of Database Security
CISA-KR 문제 413
Developing a risk-based plan considering each entity's business processes would best help to ensure that IS audit still covers key risk areas within the IT environment as part of its annual plan. A risk-based plan is a plan that prioritizes the audit activities based on the level of risk associated with each area or process. A risk-based plan can help to allocate the audit resources more efficiently and effectively, and provide more assurance and value to the stakeholders1.
By considering each entity's business processes, the IS audit can identify and assess the specific risks and controls that affect the IT environment of each entity, and tailor the audit objectives, scope, and procedures accordingly. This can help to address the unique needs and expectations of each entity, and ensure that the IS audit covers the key risk areas that are relevant and significant to each entity's operations, performance, and compliance2.
The other options are not as effective as developing a risk-based plan considering each entity's business processes in ensuring that IS audit still covers key risk areas within the IT environment as part of its annual plan. Option A, increasing the frequency of risk-based IS audits for each business entity, is not a feasible or efficient solution, as it may increase the audit costs and workload, and create duplication or overlap of audit efforts. Option C, conducting an audit of newly introduced IT policies and procedures, is a limited and narrow approach, as it may not cover all the aspects or dimensions of the IT environment that may have changed or been affected by the split. Option D, revising IS audit plans to focus on IT changes introduced after the split, is a reactive and short-term approach, as it may not reflect the current or future state of the IT environment or the business objectives of each entity.
References:
ISACA, CISA Review Manual, 27th Edition, 2019
ISACA, CISA Review Questions, Answers & Explanations Database - 12 Month Subscription Risk-Based Audit Planning: A Guide for Internal Audit1 Risk-Based Audit Approach: Definition & Example
CISA-KR 문제 414
Stress testing is a type of performance testing that evaluates the behavior and reliability of a system under extreme conditions, such as high workload, limited resources, or concurrent users. Stress testing should ideally be carried out under a test environment with production workloads, as this would simulate the most realistic and demanding scenario for the system without affecting the actual production environment. A production environment with production workloads is not suitable for stress testing, as it could cause disruption or damage to the system and its users. A production environment with test data is not suitable for stress testing, as it could compromise the integrity and security of the production data. A test environment with test data is not suitable for stress testing, as it could underestimate the potential issues and risks that could occur in the production environment. References:
CISA Review Manual, 27th Edition, pages 471-4721
CISA Review Questions, Answers & Explanations Database, Question ID: 261
CISA-KR 문제 415
The audit team's most important course of action is to consult the legal department to understand the procedure for requesting data from a different jurisdiction, as this will ensure that the data analytics techniques are compliant with the applicable laws and regulations of both countries12. Requesting data from a foreign branch may involve legal risks such as data privacy, data sovereignty, and data protection34, and the audit team should seek legal guidance before proceeding with the data extraction and analysis.
References
1: Data Analytics and Auditing Standards 2: Data Analytics and the Audit Process 3: Data Privacy and Data Protection: US Law and Legislation 4: Data Sovereignty: What It Is and Why It Matters
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