Isaca CISA Practice Test - Questions Answers, Page 48

The best way to verify the effectiveness of a data restoration process is to perform periodic complete data restorations. This is the process of transferring backup data to the primary system or data center and verifying that the restored data is accurate, complete, and functional. By performing periodic complete data restorations, the auditee can test the reliability and validity of the backup data, the functionality and performance of the restoration tools and procedures, and the compatibility and integrity of the restored data with the primary system. This will also help identify and resolve any issues or errors that may occur during the restoration process, such as corrupted or missing files, incompatible formats, or configuration problems.

Performing periodic reviews of physical access to backup media (option A) is not the best way to verify the effectiveness of a data restoration process, as it only ensures the security and availability of the backup media, not the quality or usability of the backup data. Physical access reviews are important for preventing unauthorized access, theft, damage, or loss of backup media, but they do not test the actual restoration process or verify that the backup data can be successfully restored.

Validating offline backups using software utilities (option C) is also not the best way to verify the effectiveness of a data restoration process, as it only checks the integrity and consistency of the backup data, not the functionality or compatibility of the restored data. Software utilities can help detect and correct any errors or inconsistencies in the backup data, such as checksum errors, duplicate files, or incomplete backups, but they do not test the actual restoration process or verify that the restored data can work with the primary system.

Reviewing and updating data restoration policies annually (option D) is also not the best way to verify the effectiveness of a data restoration process, as it only ensures that the policies are current and relevant, not that they are implemented and followed. Data restoration policies are important for defining roles and responsibilities, objectives and scope, standards and procedures, and metrics and reporting for the restoration process, but they do not test the actual restoration process or verify that it meets the expected outcomes.

Therefore, option B is the correct answer.

What is backup and disaster recovery? | IBM

Backup and Recovery of Data: The Essential Guide | Veritas

Database Backup and Recovery Best Practices - ISACA

The planning phase is the stage of the internal audit process where contact is established with the individuals responsible for the business processes in scope for review. The planning phase involves defining the objectives, scope, and criteria of the audit, as well as identifying the key risks and controls related to the audited area. The planning phase also involves communicating with the auditee to obtain relevant information, documents, and data, as well as to schedule interviews, walkthroughs, and meetings. The planning phase aims to ensure that the audit team has a clear understanding of the audited area and its context, and that the audit plan is aligned with the expectations and needs of the auditee and other stakeholders.

The execution phase is the stage of the internal audit process where the audit team performs the audit procedures according to the audit plan. The execution phase involves testing the design and operating effectiveness of the controls, collecting and analyzing evidence, documenting the audit work and results, and identifying any issues or findings. The execution phase aims to provide sufficient and appropriate evidence to support the audit conclusions and recommendations.

The follow-up phase is the stage of the internal audit process where the audit team monitors and verifies the implementation of the corrective actions agreed upon by the auditee in response to the audit findings. The follow-up phase involves reviewing the evidence provided by the auditee, conducting additional tests or interviews if necessary, and evaluating whether the corrective actions have adequately addressed the root causes of the findings. The follow-up phase aims to ensure that the auditee has taken timely and effective actions to improve its processes and controls.

The selection phase is not a standard stage of the internal audit process, but it may refer to the process of selecting which areas or functions to audit based on a risk assessment or an annual audit plan. The selection phase involves evaluating the inherent and residual risks of each potential auditable area, considering the impact, likelihood, and frequency of those risks, as well as other factors such as regulatory requirements, stakeholder expectations, previous audit results, and available resources. The selection phase aims to prioritize and allocate the audit resources to those areas that present the highest risks or opportunities for improvement.

Therefore, option A is the correct answer.

Stages and phases of internal audit - piranirisk.com

Step-by-Step Internal Audit Checklist | AuditBoard

Audit Process | The Office of Internal Audit - University of Oregon

Stratified mean per unit sampling is a method of audit sampling that divides the population into subgroups (strata) based on some characteristic, such as monetary value, and then selects a sample from each stratum using mean per unit sampling. Mean per unit sampling is a method of audit sampling that estimates the total value of a population by multiplying the average value of the sample items by the number of items in the population. Stratified mean per unit sampling is suitable for populations that have a high variability or a skewed distribution, such as the bank accounts in this question. By stratifying the population, the auditor can reduce the sampling error and increase the precision of the estimate.

Difference estimation sampling (option A) is not the best sampling approach for these accounts. Difference estimation sampling is a method of audit sampling that estimates the total error or misstatement in a population by multiplying the average difference between the book value and the audited value of the sample items by the number of items in the population. Difference estimation sampling is suitable for populations that have a low variability and a symmetrical distribution, which is not the case for the bank accounts in this question.

Customer unit sampling (option C) is not a sampling approach, but a type of monetary unit sampling. Monetary unit sampling is a method of audit sampling that selects sample items based on their monetary value, rather than their physical units. Customer unit sampling is a variation of monetary unit sampling that treats each customer account as a single unit, regardless of how many transactions or balances it contains. Customer unit sampling may be appropriate for testing existence or occurrence assertions, but not for estimating total values.

Unstratified mean per unit sampling (option D) is not the best sampling approach for these accounts. Unstratified mean per unit sampling is a method of audit sampling that applies mean per unit sampling to the entire population without dividing it into subgroups. Unstratified mean per unit sampling may result in a larger sample size and a lower precision than stratified mean per unit sampling, especially for populations that have a high variability or a skewed distribution, such as the bank accounts in this question.

Therefore, option B is the correct answer.

Audit Sampling - AICPA

Audit Sampling: Examples and Guidance To The Sampling Methods

Audit Sampling | Audit | Financial Audit - Scribd

The first step to successfully implement a corporate data classification program is to approve a data classification policy. A data classification policy is a document that defines the objectives, scope, principles, roles, responsibilities, and procedures for classifying data based on its sensitivity and value to the organization. A data classification policy is essential for establishing a common understanding and a consistent approach for data classification across the organization, as well as for ensuring compliance with relevant regulatory and contractual requirements.

Selecting a data loss prevention (DLP) product (option B) is not the first step to implement a data classification program, as it is a technical solution that supports the enforcement of the data classification policy, not the definition of it. A DLP product can help prevent unauthorized access, use, or disclosure of sensitive data by monitoring, detecting, and blocking data flows that violate the data classification policy. However, before selecting a DLP product, the organization needs to have a clear and approved data classification policy that specifies the criteria and rules for data classification.

Confirming that adequate resources are available for the project (option C) is also not the first step to implement a data classification program, as it is a project management activity that ensures the feasibility and sustainability of the project, not the design of it. Confirming that adequate resources are available for the project involves estimating and securing the necessary budget, staff, time, and tools for implementing and maintaining the data classification program. However, before confirming that adequate resources are available for the project, the organization needs to have a clear and approved data classification policy that defines the scope and objectives of the project.

Checking for the required regulatory requirements (option D) is also not the first step to implement a data classification program, as it is an input to the development of the data classification policy, not an output of it. Checking for the required regulatory requirements involves identifying and analyzing the applicable laws, regulations, standards, and contracts that govern the protection and handling of sensitive data. However, checking for the required regulatory requirements is not enough to implement a data classification program; the organization also needs to have a clear and approved data classification policy that incorporates and complies with those requirements.

Therefore, option A is the correct answer.

Data Classification: What It Is and How to Implement It

Create a well-designed data classification framework

7 Steps to Effective Data Classification | CDW

Data Classification: The Basics and a 6-Step Checklist - NetApp

Private and confidential February 2021 - Deloitte US

The most important thing to consider before including an audit of IT capacity management in the program is whether the system's performance poses a significant risk to the organization. IT capacity management is a process that ensures that IT resources are sufficient to meet current and future business needs, and that they are optimized for cost and performance. A poor IT capacity management can result in system slowdowns, outages, failures, or breaches, which can affect the availability, reliability, security, and efficiency of IT services and business processes. Therefore, before conducting an audit of IT capacity management, the auditor should assess the potential impact and likelihood of these risks on the organization's objectives, reputation, compliance, and customer satisfaction.

Whether system delays result in more frequent use of manual processing (option A) is not the most important thing to consider before including an audit of IT capacity management in the program, as it is only one possible consequence of poor IT capacity management. Manual processing can introduce errors, delays, inefficiencies, and inconsistencies in the data and reports, which can affect the quality and accuracy of financial information. However, manual processing is not the only or the worst outcome of poor IT capacity management; there may be other more severe or frequent risks that need to be considered.

Whether stakeholders are committed to assisting with the audit (option C) is also not the most important thing to consider before including an audit of IT capacity management in the program, as it is a factor that affects the feasibility and effectiveness of the audit, not the necessity or priority of it. Stakeholder commitment is important for ensuring that the auditor has access to relevant information, documents, data, and personnel, as well as for facilitating communication, collaboration, and feedback during the audit process. However, stakeholder commitment is not a sufficient reason to conduct an audit of IT capacity management; there must be a clear risk-based rationale for selecting this area for audit.

Whether internal auditors have the required skills to perform the audit (option D) is also not the most important thing to consider before including an audit of IT capacity management in the program, as it is a factor that affects the quality and credibility of the audit, not the urgency or importance of it. Internal auditors should have the appropriate knowledge, skills, and experience to perform an audit of IT capacity management, which may include technical, business, analytical, and communication skills. However, internal auditors can also acquire or supplement these skills through training, coaching, consulting, or outsourcing. Therefore, internal auditors' skills are not a decisive factor for choosing this area for audit.

Therefore, option B is the correct answer.

Guide to IT Capacity Management | Smartsheet

ISO 27001 capacity management: How to implement control A.12.1.3 - Advisera

ISO 27002:2022 -- Control 8.6 -- Capacity Management

Application containers are a form of operating system virtualization that share the same kernel as the host operating system. This means that any vulnerability or compromise in the kernel can affect all the containers running on the same host, as well as the host itself. Additionally, containers may have privileged access to the kernel resources and functions, which can pose a risk of unauthorized or malicious actions by the container processes. Therefore, securing the kernel is a critical aspect of application container security.

Shared registries (option A) are not an inherent risk in the application container infrastructure, but they are a potential risk that depends on how they are configured and managed. Shared registries are repositories that store and distribute container images. They can be public or private, and they can have different levels of security and access controls. Shared registries can pose a risk of exposing sensitive data, distributing malicious or vulnerable images, or allowing unauthorized access to images. However, these risks can be mitigated by using secure connections, authentication and authorization mechanisms, image signing and scanning, and encryption.

Host operating system (option B) is not an inherent risk in the application container infrastructure, but it is a potential risk that depends on how it is configured and maintained. Host operating system is the underlying platform that runs the application containers and provides them with the necessary resources and services. Host operating system can pose a risk of exposing vulnerabilities, misconfigurations, or malware that can affect the containers or the host itself. However, these risks can be mitigated by using minimal and hardened operating systems, applying patches and updates, enforcing security policies and controls, and isolating and monitoring the host.

Shared data (option C) is not an inherent risk in the application container infrastructure, but it is a potential risk that depends on how it is stored and accessed. Shared data is the information that is used or generated by the application containers and that may be shared among them or with external entities. Shared data can pose a risk of leaking confidential or sensitive data, corrupting or losing data integrity, or violating data privacy or compliance requirements. However, these risks can be mitigated by using secure storage solutions, encryption and decryption mechanisms, access control and auditing policies, and backup and recovery procedures.

Therefore, option D is the correct answer.

Application Container Security Guide | NIST

CSA for a Secure Application Container Architecture

Application Container Security: Risks and Countermeasures

Attribute sampling is a method of audit sampling that is used to test the effectiveness of controls by measuring the rate of deviation from a prescribed procedure or attribute. Attribute sampling is suitable for testing compliance with the data center's physical access log system, as the auditor can compare the identification document numbers and photos of the visitors with the records in the system and determine whether there are any discrepancies or errors. Attribute sampling can also provide an estimate of the deviation rate in the population and allow the auditor to draw a conclusion about the operating effectiveness of the control.

Variable sampling, on the other hand, is a method of audit sampling that is used to estimate the amount or value of a population by measuring a characteristic of interest, such as monetary value, quantity, or size. Variable sampling is not appropriate for testing compliance with the data center's physical access log system, as the auditor is not interested in estimating the value of the population, but rather in testing whether the system is operating as intended.

Quota sampling and haphazard sampling are both examples of non-statistical sampling methods that do not use probability theory to select a sample. Quota sampling involves selecting a sample based on certain criteria or quotas, such as age, gender, or location. Haphazard sampling involves selecting a sample without any specific plan or method. Both methods are not suitable for testing compliance with the data center's physical access log system, as they do not ensure that the sample is representative of the population and do not allow the auditor to measure the sampling risk or project the results to the population.

Therefore, attribute sampling is the most useful sampling method for an IS auditor conducting compliance testing for the effectiveness of the data center's physical access log system.

Audit Sampling - What Is It, Methods, Example, Advantage, Reason

ISA 530: Audit sampling | ICAEW

Change management is the process of planning, implementing, monitoring, and evaluating changes to an organization's information systems and related components. Change management aims to ensure that changes are aligned with the business objectives, minimize risks and disruptions, and maximize benefits and value.

One of the key aspects of change management is measuring its effectiveness, which means assessing whether the changes have achieved the desired outcomes and met the expectations of the stakeholders. There are various indicators that can be used to measure change management effectiveness, such as time, cost, quality, scope, satisfaction, and performance.

Among the four options given, the most appropriate indicator of change management effectiveness is the number of incidents resulting from changes. An incident is an unplanned event or interruption that affects the normal operation or service delivery of an information system. Incidents can be caused by various factors, such as errors, defects, failures, malfunctions, or malicious attacks. Incidents can have negative impacts on the organization, such as loss of data, productivity, reputation, or revenue.

The number of incidents resulting from changes is a direct measure of how well the changes have been planned, implemented, monitored, and evaluated. A high number of incidents indicates that the changes have not been properly tested, verified, communicated, or controlled. A low number of incidents indicates that the changes have been executed smoothly and successfully. Therefore, the number of incidents resulting from changes reflects the quality and effectiveness of the change management process.

The other three options are not as appropriate indicators of change management effectiveness as the number of incidents resulting from changes. The time lag between changes to the configuration and the update of records is a measure of how timely and accurate the configuration management process is. Configuration management is a subset of change management that focuses on identifying, documenting, and controlling the configuration items (CIs) that make up an information system. The time lag between changes and updates of documentation materials is a measure of how well the documentation process is aligned with the change management process. Documentation is an important aspect of change management that provides information and guidance to the stakeholders involved in or affected by the changes. The number of system software changes is a measure of how frequently and extensively the system software is modified or updated. System software changes are a type of change that affects the operating system, middleware, or utilities that support an information system.

While these three indicators are relevant and useful for measuring certain aspects of change management, they do not directly measure the outcomes or impacts of the changes on the organization. They are more related to the inputs or activities of change management than to its outputs or results. Therefore, they are not as appropriate indicators of change management effectiveness as the number of incidents resulting from changes.

Metrics for Measuring Change Management - Prosci

How to Measure Change Management Effectiveness: Metrics, Tools & Processes

Metrics for Measuring Change Management 2023 - Zendesk

Change control is the process of managing and documenting changes to an information system or its components. Change control aims to ensure that changes are authorized, tested, approved, implemented, and reviewed in a controlled and consistent manner. Change control is an essential part of ensuring the security, reliability, and quality of an information system.

One of the key elements of change control is testing and approval from quality assurance (QA). QA is the function that verifies that the changes meet the requirements and specifications, comply with the standards and policies, and do not introduce any errors or vulnerabilities. QA testing and approval provide assurance that the changes are fit for purpose, function as expected, and do not compromise the security or performance of the system.

An organization that has recently moved to an agile model for deploying custom code to its in-house accounting software system should still follow change control procedures, including QA testing and approval. Agile development methods emphasize flexibility, speed, and collaboration, but they do not eliminate the need for quality and security checks. In fact, agile methods can facilitate change control by enabling frequent and iterative testing and feedback throughout the development cycle.

However, if change control does not include testing and approval from QA, this poses a significant security concern for the organization. Without QA testing and approval, the changes may not be properly validated, verified, or evaluated before being deployed to production. This could result in introducing bugs, defects, or vulnerabilities that could affect the functionality, availability, integrity, or confidentiality of the accounting software system. For example, a change could cause data corruption, performance degradation, unauthorized access, or data leakage. These risks could have serious consequences for the organization's financial operations, compliance obligations, reputation, or legal liabilities.

Therefore, change control that does not include testing and approval from QA is the most significant security concern to address when reviewing the procedures in place for production code deployment in an agile model.

Change Control - ISACA

Quality Assurance - ISACA

Agile Development - ISACA

10 Agile Software Development Security Concerns You Need to Know