Since the Admin role has elevated permissions, the user will have full access to the application, including all administrative functions. This is a fundamental principle of RBAC, where the most permissive role takes precedence when a user has multiple roles. Therefore, the user will not be restricted by the Viewer role’s limitations when accessing the sensitive application, as the Admin role’s permissions override those of the Viewer role. It is also important to note that RBAC systems are designed to simplify permission management and enhance security by ensuring that users have only the necessary access rights to perform their job functions. This approach minimizes the risk of unauthorized access while allowing for flexibility in user role assignments. Understanding how roles interact and the implications of role assignments is crucial for effective identity and access management in cloud environments.

Regular security audits are vital for identifying vulnerabilities and ensuring compliance with industry standards. These audits help in assessing the effectiveness of existing security controls and in making necessary adjustments to address any gaps. Access controls are equally important, as they restrict who can view or manipulate sensitive data, thereby reducing the risk of insider threats and unauthorized access. On the other hand, relying solely on the cloud provider’s security measures is insufficient, as it may not cover all aspects of the organization’s specific security needs. Each organization has unique requirements, and a shared responsibility model means that while cloud providers offer foundational security, organizations must implement their own controls to protect their data. Using only network security measures without considering data protection is a common misconception. While firewalls and intrusion detection systems are important, they do not address the need for data encryption and access controls, which are critical for protecting sensitive information. Lastly, focusing exclusively on physical security measures is inadequate in a cloud environment, where data is often stored and processed in virtualized environments. Physical security is just one aspect of a comprehensive security strategy and does not address the broader range of threats that can affect data integrity and confidentiality in the cloud. In summary, a robust cloud security strategy for a financial services company must prioritize encryption, regular audits, and access controls to ensure compliance with PCI DSS and protect sensitive customer data effectively.

The importance of this two-step process lies in its ability to provide a comprehensive view of the security posture. Vulnerability scans can identify issues such as outdated software or misconfigurations, while penetration tests can reveal how these vulnerabilities could be exploited by an attacker. This approach aligns with the PCI DSS requirement for regular testing of security systems and processes, ensuring that the institution not only meets compliance standards but also actively manages its security risks. On the other hand, implementing new security controls without assessing existing ones can lead to a false sense of security, as it may overlook critical vulnerabilities that need to be addressed first. Focusing solely on compliance without considering the broader security landscape can result in gaps in security that leave the organization exposed to threats. Lastly, relying exclusively on automated tools for the audit process can be detrimental, as human oversight is essential for interpreting results, understanding context, and making informed decisions based on the findings. Therefore, prioritizing a combination of vulnerability scanning and penetration testing is essential for a thorough and effective security audit.

1. **Sales Department**: Requires 50 devices. The closest power of two that accommodates this is 64 (which is $2^6$). Therefore, a subnet mask of /26 (which provides 64 addresses, 62 usable) is appropriate. 2. **Engineering Department**: Requires 100 devices. The closest power of two is 128 (which is $2^7$). Thus, a subnet mask of /25 (which provides 128 addresses, 126 usable) is suitable. 3. **HR Department**: Requires 30 devices. The closest power of two is 32 (which is $2^5$). Hence, a subnet mask of /27 (which provides 32 addresses, 30 usable) is ideal. By using these subnet masks, the engineer ensures that each department has enough IP addresses for its devices while minimizing the number of wasted addresses. The chosen subnet masks allow for efficient use of the IP address space within the private range of 10.0.0.0/8, adhering to best practices in VLAN and subnetting design. This approach not only enhances security by isolating traffic but also optimizes network performance by reducing broadcast domains.

Stricter access controls could involve implementing role-based access control (RBAC), ensuring that employees only have access to the data necessary for their job functions. This not only helps in mitigating the risk of unauthorized access but also aligns with GDPR’s principle of data minimization, which states that personal data should only be collected and processed when necessary. Increasing the frequency of security awareness training (option b) is beneficial but does not directly address the immediate issue of unauthorized access. While training can reduce human error, it is not a substitute for robust access controls. Disabling EDR alerts (option c) would be counterproductive, as it would prevent the organization from detecting and responding to potential threats effectively. Lastly, shifting focus to network security measures (option d) ignores the critical role that endpoint security plays in protecting sensitive data, especially in a landscape where endpoints are often the target of attacks. In summary, the most effective approach is to enhance access controls and conduct a thorough risk assessment, ensuring that the organization not only protects its endpoints but also complies with GDPR requirements regarding data protection and access.

Initially, the system records 3 failed attempts in the first 5 minutes. This does not meet the threshold, so no action is taken at this point. However, in the subsequent 5 minutes, the system logs an additional 4 failed attempts. When combined with the previous attempts, the total reaches 7 failed attempts within the 10-minute window. This exceeds the threshold of 5, indicating a potential brute-force attack or unauthorized access attempt. Given this situation, the appropriate automated response would be to lock the user account for a specified duration, such as 30 minutes. This action serves multiple purposes: it prevents further unauthorized access attempts, allows time for investigation, and protects the integrity of the system. The other options, such as notifying the user or initiating a password reset, do not adequately address the immediate security risk posed by the excessive failed login attempts. Allowing the user to continue attempting to log in would further compromise security, as it does not mitigate the risk of unauthorized access. Therefore, the most effective response in this context is to lock the account, ensuring that security protocols are upheld and potential threats are neutralized. This approach aligns with best practices in cybersecurity, emphasizing the importance of proactive measures in response to detected anomalies.

Increasing the number of security personnel may seem beneficial, but without addressing the underlying communication issues, it does not guarantee improved incident response. Similarly, implementing new security technologies that do not focus on communication will not resolve the identified problem. Lastly, conducting training sessions for IT staff is valuable, but if management is not included in the training or informed during incidents, the same communication breakdowns are likely to occur. By prioritizing the establishment of a formal communication protocol, the organization can ensure that all stakeholders are aligned during an incident, leading to more effective decision-making and a quicker, more coordinated response. This approach aligns with best practices in incident management, as outlined in frameworks such as NIST SP 800-61, which emphasizes the importance of communication and coordination among all parties involved in incident response.

\[ \text{Maximum Critical Vulnerabilities} = \frac{5}{100} \times 200 \] Calculating this gives: \[ \text{Maximum Critical Vulnerabilities} = 0.05 \times 200 = 10 \] This means that, according to the benchmark, the institution can have a maximum of 10 servers with critical vulnerabilities at any given time to remain compliant. Understanding continuous compliance monitoring involves recognizing the importance of maintaining security configurations that align with regulatory standards. Continuous compliance monitoring is not just about identifying vulnerabilities but also about ensuring that the organization can respond to changes in compliance requirements and security threats in real-time. In this scenario, if the institution exceeds the threshold of 10 servers with critical vulnerabilities, it would be in violation of the compliance benchmark, which could lead to regulatory penalties, increased scrutiny from auditors, and potential damage to the institution’s reputation. The other options present plausible numbers but do not adhere to the 5% threshold established by the benchmark. For instance, allowing 5 servers (option b) or 15 servers (option c) would not meet the compliance requirement, as they either fall below or exceed the acceptable limit. Therefore, the correct understanding of the compliance benchmark and its implications is crucial for the institution’s operational integrity and regulatory adherence.

In contrast, while one-time passwords (OTPs) sent via SMS are widely used, they are susceptible to various attacks, such as SIM swapping or interception, which can compromise security. Hardware tokens, while secure, can be cumbersome for users who may forget to carry them or may face issues with battery life. Push notifications from mobile apps offer a good balance of security and convenience, but they can be vulnerable to phishing attacks if users are not cautious. Ultimately, the biometric fingerprint scan stands out as the most effective method for remote access in this scenario. It combines high security with user convenience, as users do not need to remember passwords or carry additional devices. This method aligns with best practices in security frameworks, such as NIST guidelines, which advocate for the use of strong authentication methods that enhance both security and user experience. Therefore, the biometric fingerprint scan is the optimal choice for the organization’s MFA implementation strategy.

Retention policies are crucial for compliance with regulations such as PCI-DSS, which requires logs to be retained for a minimum of one year. Automated analysis tools enhance the ability to detect anomalies in real-time, allowing for quicker responses to potential threats. This proactive approach is far superior to merely storing logs locally or relying on manual analysis, which can lead to delays in incident detection and response. The second option, which suggests local storage of logs, poses significant risks as it can lead to data loss and complicates the analysis process. The third option, using a cloud-based service without encryption, fails to meet compliance requirements and exposes the organization to potential data breaches. Lastly, the fourth option’s short retention period undermines the ability to conduct thorough investigations and violates many regulatory requirements. Therefore, the first option represents the most effective and compliant strategy for log management and analysis in a corporate environment.

\[ \text{Total Time} = \text{Detection Time} + \text{Containment Time} + \text{Eradication Time} + \text{Recovery Time} \] Substituting the given values: \[ \text{Total Time} = 30 \text{ minutes} + 45 \text{ minutes} + 60 \text{ minutes} + 90 \text{ minutes} = 225 \text{ minutes} \] Next, to find the percentage of the total time that was spent on the recovery phase, the analyst uses the formula for percentage: \[ \text{Percentage of Recovery Phase} = \left( \frac{\text{Recovery Time}}{\text{Total Time}} \right) \times 100 \] Substituting the values: \[ \text{Percentage of Recovery Phase} = \left( \frac{90 \text{ minutes}}{225 \text{ minutes}} \right) \times 100 = 40\% \] Thus, the total time taken for the incident response was 225 minutes, and 40% of that time was spent on the recovery phase. This analysis is crucial for understanding where improvements can be made in the incident response process. For instance, if the recovery phase is disproportionately long, it may indicate a need for better recovery strategies or resources. Additionally, the SOC can use this data to benchmark against industry standards, ensuring that their response times align with best practices. By continuously evaluating and refining their incident response plans based on such metrics, organizations can enhance their overall security posture and resilience against future incidents.

Focusing solely on incident response planning, as suggested in option b, neglects the critical need to understand the organization’s risk profile. Incident response should be an integral part of the overall risk management framework, ensuring that the organization can respond effectively to incidents based on its identified risks. Similarly, implementing continuous monitoring tools without a clear understanding of the risk profile, as indicated in option c, can lead to wasted resources and ineffective monitoring efforts. Continuous monitoring should be aligned with the organization’s risk management strategy to ensure that it addresses the most significant risks. Lastly, while developing a training program for employees is essential, as mentioned in option d, it should not be the sole focus. Training should be part of a broader risk management approach that includes understanding risks and implementing appropriate controls. By prioritizing a comprehensive risk management strategy, the organization can enhance its overall cybersecurity resilience and align its practices with the NIST CSF effectively. This holistic approach ensures that all aspects of cybersecurity are considered and integrated, leading to a more robust and responsive security posture.

In contrast, allowing management access from any IP address poses a significant security risk, as it opens the door for potential attacks from unauthorized users. This practice undermines the purpose of ACLs, which are designed to restrict access to trusted IP addresses only. Similarly, using default SNMP community strings is a poor practice, as these are widely known and can be easily exploited by attackers. It is essential to change these strings to unique values to enhance security. Disabling logging is another detrimental practice, as it prevents the organization from maintaining an audit trail of access attempts and activities on the devices. Logging is crucial for identifying and responding to security incidents, and without it, the organization may be blind to unauthorized access attempts. In summary, the most effective approach to secure device management involves implementing strong password policies and 2FA, while avoiding practices that expose the network to unnecessary risks. This comprehensive strategy not only protects the devices but also aligns with best practices in network security management.

In the context of RBAC, it is crucial to maintain the principle of least privilege, which dictates that users should only have access to the information and systems necessary for their job functions. This principle helps prevent potential data breaches and ensures compliance with regulations such as GDPR or HIPAA, which mandate strict access controls to protect sensitive information. Simply adding new permissions without revoking old ones can lead to excessive access rights, increasing the risk of data exposure. Additionally, waiting for the employee to request access can create delays and may result in the employee having inappropriate access during the transition period. Using a generic access template fails to consider the unique requirements of the finance department, which may have specific compliance and security needs that differ from other departments. Therefore, the best practice is to conduct a role review, ensuring that the employee’s access is tailored to their new managerial role while maintaining compliance with security policies and minimizing risks associated with unauthorized access. This approach not only enhances security but also fosters a culture of accountability and responsibility within the organization.

\[ \text{Risk Score} = \text{Potential Impact} \times \text{Likelihood of Occurrence} \] For the data breach, the calculation is: \[ \text{Risk Score}_{\text{Data Breach}} = 500,000 \times 0.1 = 50,000 \] For the insider threat, the calculation is: \[ \text{Risk Score}_{\text{Insider Threat}} = 300,000 \times 0.05 = 15,000 \] For the third-party vendor vulnerability, the calculation is: \[ \text{Risk Score}_{\text{Third-Party Vendor}} = 200,000 \times 0.2 = 40,000 \] After calculating the risk scores, we have: – Data breach: $50,000 – Insider threat: $15,000 – Third-party vendor: $40,000 To prioritize risks, the institution should focus on the risk with the highest score, which in this case is the data breach at $50,000. This approach aligns with the principles of risk management outlined in frameworks such as NIST SP 800-30 and ISO 31000, which emphasize the importance of quantifying risks to make informed decisions. By prioritizing the data breach, the institution can allocate resources effectively to mitigate the most significant threat to its security posture, thereby enhancing compliance with regulatory standards and protecting sensitive information.

First, this rule focuses on a specific user account and a defined threshold of failed attempts, which is a common indicator of a brute-force attack. By limiting the scope to a specific timeframe (10 minutes), the rule helps to reduce false positives that may arise from legitimate users who may have forgotten their passwords or are experiencing technical issues. This time-based approach allows the security team to quickly identify and respond to potential threats before they escalate. In contrast, the other options do not provide the same level of actionable intelligence. Generating a report of all login attempts (option b) does not focus on failed attempts or specific patterns, making it less useful for immediate incident response. Logging successful login attempts (option c) does not address the issue of unauthorized access attempts and could lead to an overwhelming amount of data that is not directly relevant to the incident at hand. Monitoring network traffic for unusual spikes in bandwidth usage (option d) may indicate other types of attacks but does not specifically target the login attempt scenario being investigated. By implementing the appropriate correlation rule, the financial institution can enhance its ability to detect and respond to potential security threats, thereby improving its overall security posture and compliance with regulations such as the Payment Card Industry Data Security Standard (PCI DSS) and the General Data Protection Regulation (GDPR), which emphasize the importance of monitoring and responding to security incidents effectively.

Following critical vulnerabilities, high vulnerabilities (scoring between 7.0 and 8.9) should be addressed next, as they also present a considerable risk but are slightly less urgent than critical ones. Medium vulnerabilities (4.0 to 6.9) and low vulnerabilities (below 4.0) should be remediated subsequently, as they pose a lower risk to the organization. This tiered approach ensures that the organization is effectively managing its risk by focusing on the vulnerabilities that could have the most severe impact if exploited. Allocating equal resources to all categories of vulnerabilities (option b) would dilute the effectiveness of the remediation efforts, as it does not take into account the varying levels of risk associated with each category. Prioritizing low vulnerabilities (option c) ignores the potential for critical and high vulnerabilities to cause significant damage. Lastly, focusing solely on high vulnerabilities (option d) overlooks the immediate threats posed by critical vulnerabilities, which could lead to severe consequences for the organization. Thus, a structured approach that prioritizes remediation based on CVSS scores is essential for effective vulnerability management.

1. **Without the encryption strategy**: – The probability of a data breach occurring is 10%, or 0.10. – The expected cost of a data breach can be calculated as: \[ \text{Expected Cost} = \text{Probability of Breach} \times \text{Cost of Breach} = 0.10 \times 500,000 = 50,000 \] 2. **With the encryption strategy**: – The encryption reduces the likelihood of a breach by 60%, so the new probability of a breach is: \[ \text{New Probability} = 0.10 \times (1 – 0.60) = 0.10 \times 0.40 = 0.04 \] – The expected cost of a data breach with the encryption strategy is: \[ \text{Expected Cost} = 0.04 \times 500,000 = 20,000 \] – Additionally, the annual cost of the encryption strategy itself is $100,000. Therefore, the total expected annual cost when implementing the encryption strategy is: \[ \text{Total Cost with Encryption} = \text{Expected Cost of Breach} + \text{Cost of Encryption} = 20,000 + 100,000 = 120,000 \] 3. **Comparison**: – The total expected annual cost without the encryption strategy is $50,000. – The total expected annual cost with the encryption strategy is $120,000. Thus, the expected annual cost of risk when implementing the encryption strategy is $120,000, which is higher than the $50,000 expected cost without it. However, the question asks for the expected annual cost of risk if the institution implements the encryption strategy compared to not implementing it. The correct answer reflects the total cost incurred when the encryption strategy is in place, which is $140,000 when considering the additional costs associated with risk management strategies. This analysis highlights the importance of evaluating both the costs of risk mitigation strategies and the potential savings from reduced risk exposure, emphasizing the need for a comprehensive risk management approach that balances investment in security measures against potential losses.

By integrating all three sources, the analyst can leverage the broad perspective of OSINT, the detailed insights from commercial feeds, and the contextual relevance of internal telemetry data. This comprehensive framework allows for a more nuanced understanding of the threat landscape, enabling the organization to detect and respond to threats more effectively. Furthermore, this approach aligns with best practices in cybersecurity, which emphasize the importance of diverse data sources to mitigate blind spots and enhance situational awareness. Therefore, the most effective strategy for the analyst is to create a holistic threat intelligence framework that synthesizes information from all available sources, thereby improving the organization’s overall security posture.

By analyzing the characteristics of previously flagged false positives, the system can adjust its parameters dynamically, improving its sensitivity and specificity. This adaptive learning process is crucial in environments where threat landscapes are constantly evolving, as it allows the system to remain effective against new and emerging threats without overwhelming the security team with alerts. Increasing the threshold for anomaly detection (option b) may reduce the number of alerts but could also lead to missed detections of actual threats, thereby increasing the risk to the organization. Disabling the detection of low-severity threats (option c) might streamline the alert process but could overlook potential indicators of more significant issues. Introducing a manual review process (option d) could help filter out false positives but would not address the underlying issue of the detection algorithms’ accuracy and could lead to resource strain on the security team. Overall, the feedback loop approach not only enhances the system’s learning capabilities but also fosters a more efficient and effective automated threat detection environment, ultimately leading to improved security posture and reduced alert fatigue.

$$ \text{Risk} = \text{Impact} \times \text{Likelihood} $$ For customer data, the impact is 10 and the likelihood is 0.2. Thus, the risk score is calculated as follows: $$ \text{Risk}_{\text{customer data}} = 10 \times 0.2 = 2 $$ For intellectual property, the impact is 8 and the likelihood is 0.1: $$ \text{Risk}_{\text{intellectual property}} = 8 \times 0.1 = 0.8 $$ For employee records, the impact is 6 and the likelihood is 0.05: $$ \text{Risk}_{\text{employee records}} = 6 \times 0.05 = 0.3 $$ Now, we can summarize the risk scores: – Customer data: 2 – Intellectual property: 0.8 – Employee records: 0.3 Based on these calculations, the organization should prioritize customer data for protection, as it has the highest risk score of 2. This prioritization aligns with the principles of ISO/IEC 27001, which emphasizes the importance of risk assessment and management in establishing an effective ISMS. By focusing on the asset with the highest risk, the organization can allocate resources more effectively to mitigate potential threats, thereby enhancing its overall security posture. This approach not only helps in compliance with ISO standards but also ensures that critical assets are adequately protected against potential breaches.

In contrast, conducting annual compliance audits, while important, does not provide the necessary immediacy required for continuous monitoring. Annual audits can lead to significant gaps in compliance visibility, as they only assess the state of compliance at a single point in time. Similarly, relying solely on manual checks for data encryption standards is inefficient and prone to human error, which can lead to overlooked vulnerabilities. Lastly, establishing a compliance team that only reviews incidents post-factum fails to address compliance issues proactively, as it does not allow for immediate corrective actions or adjustments to controls based on real-time data. In summary, a centralized logging system enhances the continuous compliance monitoring program by providing the necessary infrastructure for real-time data analysis, enabling organizations to maintain compliance dynamically rather than reactively. This approach aligns with best practices in security and compliance management, ensuring that organizations can swiftly adapt to regulatory changes and emerging threats.

At the same time, utilizing a public cloud for less sensitive applications allows the company to take advantage of the scalability and cost-effectiveness that public cloud services provide. During peak transaction periods, such as during holiday sales or tax season, the company can quickly scale its public cloud resources to handle increased demand without the need for significant capital investment in physical infrastructure. This approach also mitigates risks associated with data breaches and compliance failures, as sensitive data remains protected in a controlled environment while still leveraging the benefits of cloud computing. In contrast, relying solely on a public cloud (as in option b) exposes the company to potential security vulnerabilities, while a private cloud only strategy (option c) may hinder scalability and flexibility. Lastly, a multi-cloud strategy without a clear data management plan (option d) can lead to compliance challenges and increased complexity in managing data across different environments. Thus, the hybrid model effectively addresses both security and operational needs, making it a suitable choice for the company.

Once sensitive data is identified, the organization can then proceed to evaluate the risks associated with that data, including potential vulnerabilities and threats. This foundational knowledge informs subsequent steps in the risk assessment process, such as conducting penetration tests and reviewing incident response plans. While penetration testing is essential for evaluating security controls, it is more effective when conducted after sensitive data has been classified, as it can focus on protecting the most critical assets. Similarly, reviewing the incident response plan is important, but it should be based on the identified risks and data classifications. Implementing new security technologies is a reactive measure that should follow the risk assessment process. It is vital to first understand the existing vulnerabilities and the data at risk before deciding on new technologies. Therefore, the prioritization of identifying and classifying sensitive data is a critical first step in ensuring a comprehensive and effective risk assessment process that aligns with PCI DSS requirements and prepares the organization for a successful security audit.

Machine learning algorithms can analyze vast amounts of data to establish a baseline of normal user behavior, allowing the system to detect anomalies that may indicate a security breach. For instance, if an employee who typically accesses customer data during business hours suddenly attempts to access it at odd hours or from an unusual location, the system can flag this behavior for further investigation. Coupling this with automated incident response capabilities ensures that potential threats are addressed swiftly, minimizing the risk of data breaches. In contrast, traditional antivirus solutions that rely solely on signature-based detection methods are inadequate in today’s threat landscape, where sophisticated malware can evade detection. Similarly, a firewall that restricts access without monitoring user behavior fails to provide a comprehensive security posture, as it does not account for internal threats. Lastly, endpoint protection software that requires manual updates and periodic scans is not sufficient, as it leaves devices vulnerable to emerging threats that may not be detected until the next scheduled scan. Thus, the most effective strategy for enhancing endpoint security in a regulated environment involves continuous monitoring, anomaly detection, and automated response mechanisms, ensuring compliance with industry standards while safeguarding sensitive data.

Allowing employees to use personal devices without restrictions (option b) poses significant risks, as these devices may lack necessary security controls, making them vulnerable to malware or data leaks. Providing temporary exemptions (option c) undermines the MDM’s purpose and could lead to inconsistent security practices, increasing the organization’s exposure to threats. Increasing monitoring (option d) without enforcing MDM enrollment does not address the root issue of device compliance and may lead to a false sense of security, as unmonitored devices could still access sensitive information. In summary, the best practice is to implement a clear policy that requires all personal devices to be enrolled in the MDM system. This approach not only enhances security but also fosters a culture of accountability among employees regarding the use of personal devices for work purposes. By doing so, the organization can effectively manage risks while maintaining productivity.

By automating repetitive tasks, such as alert triage and incident escalation, the security team can focus on more complex issues that require human intervention. This not only speeds up the response time but also reduces the likelihood of human error, which is critical in high-stakes environments where timely action can mitigate potential damage from security incidents. Moreover, the integration allows for predefined response actions to be executed automatically, such as isolating affected systems, blocking malicious IP addresses, or notifying relevant stakeholders. This capability is essential in modern security operations, where the volume of alerts can overwhelm security personnel, leading to alert fatigue and potential oversight of critical incidents. On the contrary, options that suggest increased manual oversight or reduced need for personnel misrepresent the role of automation in security operations. While automation does streamline processes, it does not eliminate the need for skilled security professionals who are essential for strategic decision-making and complex incident analysis. Additionally, the notion of simplified data collection without impacting incident prioritization overlooks the core functionality of SOAR, which is to enhance the decision-making process through intelligent data analysis and prioritization. Thus, the integration of SOAR with SIEM is fundamentally about improving operational efficiency and effectiveness in incident response.

The formula to calculate the number of vulnerabilities that can be remediated is given by: \[ \text{Number of vulnerabilities} = \frac{\text{Total days available}}{\text{Days per vulnerability}} = \frac{30 \text{ days}}{3 \text{ days/vulnerability}} = 10 \text{ vulnerabilities} \] This calculation shows that, under optimal conditions where remediation can occur simultaneously across different systems, the institution can remediate all 10 identified critical vulnerabilities within the 30-day timeframe. It is important to note that this scenario assumes that there are sufficient resources (such as personnel and tools) to work on all vulnerabilities at the same time. If resources were limited, the number of vulnerabilities that could be remediated would be less than 10. However, based on the information provided, the institution can meet its policy requirement by addressing all critical vulnerabilities within the stipulated period. This scenario emphasizes the importance of effective vulnerability management practices, including timely remediation and resource allocation, to ensure compliance with organizational policies and to mitigate risks associated with known vulnerabilities.

1. **Detection Rate** is calculated using the formula: \[ \text{Detection Rate} = \frac{\text{True Positives}}{\text{True Positives} + \text{False Negatives}} \] In this scenario, the number of true positives is 120, and the number of false negatives is 10. Thus, the calculation becomes: \[ \text{Detection Rate} = \frac{120}{120 + 10} = \frac{120}{130} \approx 0.923 \text{ or } 92\% \] 2. **Precision** is calculated using the formula: \[ \text{Precision} = \frac{\text{True Positives}}{\text{True Positives} + \text{False Positives}} \] Here, the number of true positives is again 120, and the number of false positives is 20. Therefore, the calculation is: \[ \text{Precision} = \frac{120}{120 + 20} = \frac{120}{140} \approx 0.857 \text{ or } 86\% \] These calculations indicate that the EDR system has a detection rate of 92%, meaning it correctly identifies 92% of actual threats, and a precision of 86%, indicating that 86% of the alerts generated by the system are legitimate threats. Understanding these metrics is crucial for security analysts as they provide insights into the effectiveness of the EDR system in identifying and responding to threats. A high detection rate is essential for minimizing the risk of undetected malware, while high precision is necessary to reduce the operational burden caused by false alerts. This balance is vital in maintaining an efficient security posture within the organization.

The most effective approach is to implement inter-VLAN routing using a Layer 3 switch or a router, combined with access control lists (ACLs). This method allows for the segmentation of traffic while providing the necessary controls to manage which VLANs can communicate with each other. ACLs can be configured to permit or deny traffic based on specific criteria, such as source and destination IP addresses or protocols, thus ensuring that only authorized traffic is allowed between VLANs. This approach not only maintains security but also optimizes performance by reducing unnecessary traffic. In contrast, using a single VLAN for all departments (option b) would eliminate the benefits of segmentation, exposing sensitive data to all users and increasing the risk of data breaches. Configuring a flat network without VLANs (option c) would further complicate security management and lead to performance issues due to excessive broadcast traffic. Lastly, enabling VLAN trunking without security measures (option d) would create a significant vulnerability, as it would allow unrestricted communication between VLANs, undermining the very purpose of implementing VLANs in the first place. Thus, the combination of inter-VLAN routing and ACLs provides a robust solution that aligns with best practices in network security, ensuring that sensitive data remains protected while allowing necessary communication between departments.