CISA Exam Dumps - Certified Information Systems Auditor

 An organization considering the outsourcing of a business application should first conduct a cost-benefit analysis to evaluate the feasibility, viability and desirability of the outsourcing decision. A cost-benefit analysis should compare the costs and benefits of outsourcing versus keeping the application in-house, taking into account factors such as financial, operational, strategic, legal, regulatory, security and quality aspects. A cost-benefit analysis should also identify the risks and opportunities associated with outsourcing, and provide a basis for defining the service level requirements, performing a vulnerability assessment, and issuing a request for proposal (RFP) in the subsequent stages of the outsourcing process. References: Info Technology andSystems Resources | COBIT, Risk, Governance … - ISACA, CISACertification | Certified Information Systems Auditor | ISACA

The scanning will not degrade system performance. This is the most important consideration when establishing vulnerability scanning on critical IT infrastructure, because any degradation of system performance could affect the availability, reliability, and functionality of the IT services that depend on the infrastructure. Scanning during non-peak hours (A) could reduce the impact of scanning on system performance, but it does not guarantee that the scanning will not cause any degradation. Scanning followed by penetration testing (B) could provide more in-depth information about the vulnerabilities and their exploitability, but it does not address the potential impact of scanning on system performance. Scanning cost-effectiveness © is a relevant factor for choosing a scanning service or tool, but it is not as important as ensuring that the scanning will not compromise the system performance.

Benford ' s Law analyzes numerical data to detect anomalies based on the frequency distribution of leading digits. For it to be effective, the dataset must follow specific criteria, including consistency in measurement units. If transactions are in different currencies, the leading digits can vary due to currency conversion rates, invalidating the analysis.

Double Integer Format (Option A):Benford’s Law applies to any set of numerical data, not specifically double integers.

Random Selection of Transactions (Option B):The data set must represent the entire population, not a random selection.

Limiting Analysis to Standard Deviations (Option C):This is irrelevant to the application of Benford ' s Law.

A digital envelope combines the strengths of symmetric and asymmetric cryptography. The message itself is encrypted using a fast symmetric algorithm. The session key used for symmetric encryption is then encrypted using the recipient’s public key. This ensures efficiency (large data encrypted quickly with symmetric keys) and security (session key securely transmitted using asymmetric encryption). Options A, C, and D describe other cryptographic processes (compression, hashing, or digital signatures) but do not correctly represent a digital envelope. ISACA training materials and CISA manuals highlight this hybrid approach as the standard method for secure data transmission.

References (ISACA): CISA Review Manual – Cryptography Concepts; ISACA Glossary.

Data analytics is the process of collecting, transforming, analyzing, and visualizing data to gain insights and support decision making1. Data analytics can be used to facilitate the testing of a new account creation process by applying various techniques and methods to evaluate the quality, functionality, performance, and security of the process. One of the approaches that would utilize data analytics to test the new account creation process is to review new account applications submitted in the past month for invalid dates of birth. This approach would involve the following steps:

Extract the data of new account applications from the source system, such as a database or a web service, using appropriate tools and methods.

Transform and clean the data to ensure its accuracy, completeness, consistency, and validity, using techniques such as data profiling, data cleansing, data mapping, and data validation2.

Analyze the data to identify any anomalies, errors, or outliers in the date of birth field, using methods such as descriptive statistics, exploratory data analysis, hypothesis testing, or anomaly detection3.

Visualize the data to present the findings and insights in a clear and understandable way, using tools and techniques such as charts, graphs, dashboards, or reports.

By reviewing new account applications submitted in the past month for invalid dates of birth, the tester can use data analytics to:

Verify if the new account creation process is working as expected and meets the business requirements and specifications for the date of birth field.

Detect any defects or issues in the new account creation process that may cause invalid dates of birth to be accepted or rejected incorrectly.

Measure and monitor the performance and reliability of the new account creation process in terms of data quality, accuracy, and completeness.

Evaluate and improve the test coverage and effectiveness of the new account creation process by identifying any gaps or risks in the test cases or scenarios.

Therefore, option C is the correct answer.

Option A is not correct because attempting to submit new account applications with invalid dates of birth is not a data analytics approach, but a functional testing approach that involves executing test cases or scenarios manually or automatically to validate the behavior and functionality of the new account creation process. Option B is not correct because reviewing the business requirements document for date of birth field requirements is not a data analytics approach, but a requirements analysis approach that involves examining and understanding the needs and expectations of the stakeholders for the new account creation process. Option D is not correct because evaluating configuration settings for date of birth field requirements is not a data analytics approach, but a configuration testing approach that involves verifying if the settings and parameters of the new account creation process are correct and consistent with the requirements.

The central goal of DLP is to prevent sensitive data—such as PII, PHI, or intellectual property—from leaving the organization through unauthorized channels. DLP solutions monitor, detect, and block potential data exfiltration via email, endpoints, cloud applications, or removable media. While compliance (D) is often a driver, it is a secondary outcome of implementing DLP. Enhancing performance (A) and recovery automation (B) are not objectives of DLP. ISACA positions DLP as a critical control for confidentiality under DSS05 (Managed Security Services).

References (ISACA): COBIT® 2019, DSS05 Managed Security Services.

 An IS auditor reviewing the threat assessment for a data center would be most concerned if the exercise was completed by local management, because this could introduce bias, conflict of interest, or lack of expertise in the assessment process. A threat assessment is a systematic method of identifying and evaluating the potential threats that could affect the availability, integrity, or confidentiality of the data center and its assets. A threat assessmentshould be conducted by an independent and qualified team that has the necessary skills, knowledge, and experience to perform a comprehensive and objective analysis of the data center’s environment, vulnerabilities, and risks1.

The other options are not as concerning as option C for an IS auditor reviewing the threat assessment for a data center. Option A, some of the identified threats are unlikely to occur, is not a problem as long as the likelihood and impact of each threat are properly estimated and prioritized. A threat assessment should consider all possible scenarios, even if they have a low probability of occurrence, to ensure that the data center is prepared for any eventuality2. Option B, all identified threats relate to external entities, is not a flaw as long as the assessment also considers internal threats, such as human errors, malicious insiders, or equipment failures. External threats are often more visible and severe than internal threats, butthey are not the only source of risk for a data center3. Option D, neighboring organizations’ operations have been included, is not a mistake as long as the assessment also focuses on the data center’s own operations. Neighboring organizations’ operations may have an impact on the data center’s security and availability, especially if they share physical or network infrastructure or resources. A threat assessmentshould take into account the interdependencies and interactions between the data center and its external environment4.