Establishing clear timelines for incident reporting allows the organization to respond swiftly to security incidents, ensuring that stakeholders, including customers and regulatory bodies, are informed promptly. This aligns with the principle of accountability and transparency mandated by regulations such as GDPR, which emphasizes the importance of notifying affected individuals within a specific timeframe after a data breach. While increasing employee training on cybersecurity awareness is beneficial, it does not directly address the identified gap in the incident response plan. Similarly, implementing a new firewall solution may enhance security but does not rectify the procedural deficiencies in incident management. Conducting a vulnerability assessment is also important for identifying weaknesses, yet it does not specifically address the need for improved incident reporting protocols. Thus, prioritizing the establishment of clear timelines for incident reporting and stakeholder notification is essential for aligning the institution’s security policies with regulatory requirements and best practices, ultimately strengthening their overall security posture.

\[ \text{RAM required} = 200 \, \text{Mbps} \times 0.1 \, \text{GB/Mbps} = 20 \, \text{GB} \] However, since the IPS has only 16 GB of total RAM, it cannot allocate 20 GB. Therefore, we need to consider the maximum RAM that can be allocated while maintaining a buffer of 20% for emergency processing. First, we calculate the buffer size: \[ \text{Buffer} = 20\% \times 16 \, \text{GB} = 0.2 \times 16 \, \text{GB} = 3.2 \, \text{GB} \] Now, we subtract the buffer from the total RAM to find the maximum RAM available for traffic processing: \[ \text{Max RAM for processing} = 16 \, \text{GB} – 3.2 \, \text{GB} = 12.8 \, \text{GB} \] Since RAM allocation must be a whole number, we round down to 12 GB. This means that the IPS can allocate a maximum of 12 GB for traffic processing while still maintaining the necessary buffer for emergency situations. This scenario illustrates the importance of dynamic resource allocation in network security, as it allows the IPS to adapt to varying traffic loads while ensuring that sufficient resources are reserved for critical operations. Understanding how to balance resource allocation with performance requirements is crucial for maintaining optimal network security and performance.

For high-severity events, the appropriate actions include logging the event for future analysis, sending an immediate email alert to the security team to ensure rapid response, and blocking the offending IP address to prevent further malicious activity. This multi-faceted approach is essential for high-severity incidents, as they pose a significant risk to the network. For medium-severity events, the actions should include logging the event to maintain a record and sending a notification to the security dashboard. This allows the security team to monitor these events without overwhelming them with alerts, as medium-severity events may not require immediate action but should still be tracked. Low-severity events should only be logged, as they typically do not pose an immediate threat and do not require further action. This tiered response strategy ensures that resources are allocated efficiently and that the security team can focus on the most critical threats. The other options present configurations that either misclassify the severity of events or propose actions that do not align with best practices for incident response. For instance, blocking IP addresses for medium-severity events or sending unnecessary alerts for low-severity events could lead to alert fatigue and inefficient resource use. Therefore, the correct configuration aligns with the principle of proportional response based on the severity of the detected events.

The first option suggests implementing a signature that looks for the exact string “UNION SELECT” followed by a numeric pattern. This specificity is essential because SQL injection attacks often rely on specific patterns that can be identified through careful analysis of the application’s behavior and the database structure. By incorporating a threshold for the number of occurrences within a defined time frame, the analyst can further reduce false positives by ensuring that only repeated attempts to exploit the vulnerability trigger an alert. This method leverages both pattern recognition and behavioral analysis, which are critical in distinguishing legitimate traffic from malicious activity. In contrast, the second option proposes a broad signature that detects any instance of the word “UNION” in any context. This approach is likely to generate a high number of false positives, as the term “UNION” can appear in legitimate queries unrelated to an attack. Similarly, the third option, which checks for SQL keywords without considering context, fails to account for the specific application and its database structure, leading to ineffective detection. Lastly, the fourth option, which matches any SQL command regardless of parameters, is overly broad and would likely overwhelm the security team with alerts, making it impractical for real-world application. In summary, the most effective custom signature is one that is tailored to the specific attack vector, incorporates contextual awareness, and utilizes thresholds to minimize false positives, thereby enhancing the overall security posture of the network.

The primary benefit of event correlation lies in its ability to connect the dots between seemingly unrelated events. For instance, if the same IP address is seen attempting access from different logs (firewalls, IDS, etc.), event correlation can highlight this pattern, suggesting that the activity may not be random but rather part of a deliberate attack strategy. This capability is crucial for identifying advanced persistent threats (APTs) or coordinated attacks that might otherwise go unnoticed if each event were analyzed in isolation. In contrast, the other options present misconceptions about event correlation. Simplifying log management without analysis (option b) undermines the purpose of correlation, which is to derive insights from data rather than merely aggregating it. Providing detailed reports of individual events without context (option c) fails to leverage the relationships between events, which is essential for threat detection. Lastly, focusing solely on recent events (option d) neglects the importance of historical data in understanding trends and patterns over time, which is vital for effective threat analysis. Thus, the nuanced understanding of event correlation emphasizes its role in enhancing threat detection capabilities by identifying patterns and relationships across disparate events, making it an indispensable tool in modern cybersecurity practices.

While RAM is important for the overall performance of the IPS, the configuration with 16 GB of RAM is sufficient for the requirements stated, especially when paired with a quad-core processor. The dedicated SSD for logging is also a crucial component, as it provides faster read and write speeds compared to traditional hard drives, allowing for quicker access to logs and improved overall system responsiveness. In contrast, the dual-core processor option, even with increased RAM, would likely struggle to keep up with the processing demands of a 10 Gbps throughput, as it would not be able to handle the same level of concurrent processing as the quad-core option. The configuration with a traditional HDD would further exacerbate performance issues due to slower data access speeds. Thus, the optimal choice is the quad-core processor running at 3.0 GHz with 16 GB of RAM and a dedicated SSD, as it meets the hardware requirements while ensuring that the IPS can effectively manage the expected traffic load and process security events in real-time.

The primary function of CTR is to aggregate data from these disparate security tools, providing context and insights that are crucial for understanding the nature and scope of threats. By correlating information from multiple sources, CTR helps analysts identify patterns and trends that may indicate a broader attack or vulnerability within the network. This capability is essential for proactive threat hunting and incident response, as it allows teams to prioritize their efforts based on the severity and potential impact of the threats identified. In contrast, the other options present misconceptions about the role of CTR. For instance, while endpoint protection is a critical component of cybersecurity, CTR does not focus solely on this area; rather, it encompasses a broader range of security measures. Additionally, the notion that CTR operates independently and provides alerts without context undermines its core functionality, which is to enhance situational awareness through integration. Lastly, describing CTR primarily as a firewall misrepresents its capabilities, as it is not limited to blocking unauthorized access but rather focuses on comprehensive threat detection and response across the entire security landscape. Understanding the multifaceted role of Cisco Threat Response is crucial for security professionals, as it enables them to leverage the full potential of their security infrastructure and respond effectively to evolving threats.

On the other hand, external threat intelligence feeds offer insights into broader trends and emerging threats that may not yet be present within the organization but could pose future risks. By combining these two sources, the security analyst can create a comprehensive view of the threat landscape. Continuous updating and correlation of this data with real-time network activity ensure that the threat intelligence remains relevant and actionable. This dynamic approach allows for timely detection of threats and the ability to respond effectively. In contrast, relying solely on external feeds (as suggested in option b) neglects the organization’s specific context, which can lead to misaligned defenses. Using only internal data (as in option c) limits the scope of threat detection and may leave the organization vulnerable to external threats. Lastly, integrating feeds without correlation or analysis (as in option d) results in an overwhelming amount of data that lacks actionable insights, rendering the threat intelligence ineffective. Therefore, the best practice is to implement a hybrid approach that continuously updates and correlates both internal and external threat intelligence, ensuring that the organization is well-equipped to identify and respond to threats in a timely manner.

In addition to signature-based detection, many modern IPS solutions incorporate heuristic or behavior-based analysis, which allows them to identify suspicious patterns of behavior that may indicate an attack. This capability enhances the IPS’s adaptability to emerging threats, although it may not be as effective as signature-based detection for known attacks. Therefore, while an IPS can provide a robust layer of security, it is essential to recognize that it may not be foolproof against all types of threats, particularly those that are novel or sophisticated. The incorrect options highlight misconceptions about the role of an IPS. For instance, relying solely on user-defined rules (option b) neglects the importance of automated threat detection and response. A passive monitoring tool (option c) misrepresents the active role of an IPS, which is to block threats rather than merely alerting administrators. Lastly, the notion that an IPS can replace traditional firewalls (option d) is misleading, as both systems serve distinct but complementary roles in a comprehensive security architecture. Firewalls primarily control access based on predefined rules, while IPS focuses on detecting and preventing intrusions. Thus, understanding the nuanced capabilities and limitations of an IPS is crucial for effective network security management.

By documenting the firewall configuration, the organization can ensure that it has a clear understanding of how the firewall is set up to protect sensitive data. Regular reviews are essential to assess whether the firewall is still effective in the face of new vulnerabilities and threats. This proactive approach allows for timely updates and adjustments to the firewall settings, ensuring compliance with PCI DSS requirements. In contrast, simply increasing the number of firewalls (option b) does not address the need for documentation and review, which are fundamental to maintaining security. Relying on default settings (option c) is a significant security risk, as default configurations are often well-known and can be exploited by attackers. Lastly, while implementing an intrusion detection system (option d) can enhance security, it does not replace the need for a properly documented and reviewed firewall configuration, which is a foundational element of PCI DSS compliance. Therefore, the organization should prioritize documenting the firewall configuration and conducting regular reviews to strengthen its compliance posture effectively.

In contrast, merely increasing the frequency of general cybersecurity training does not address the specific need for a structured response to incidents. While employee awareness is important, it must be complemented by actionable procedures that guide employees on how to respond when an incident occurs. Implementing a new firewall system may enhance perimeter security, but it does not address the internal processes required to manage incidents effectively. Firewalls are a critical component of network security, but they cannot prevent all types of security incidents, especially those that involve insider threats or social engineering attacks. Lastly, conducting a vulnerability assessment is a proactive measure to identify weaknesses in the network infrastructure; however, without an incident response plan, the organization remains ill-prepared to handle incidents that may arise from these vulnerabilities. Therefore, prioritizing the development of a comprehensive incident response plan is essential for enhancing the overall security posture and ensuring compliance with industry standards, such as those outlined in frameworks like NIST SP 800-53 or ISO/IEC 27001, which emphasize the importance of incident management in information security.

Application signatures are predefined patterns that correspond to specific applications, enabling the IPS to recognize and classify traffic accurately. Protocol decoding further enhances this process by analyzing the underlying protocols (such as HTTP, HTTPS, and FTP) to understand how applications communicate over the network. This dual approach significantly reduces the likelihood of false positives, as it relies on a comprehensive understanding of application behavior rather than simplistic port-based identification. In contrast, relying solely on port-based identification can lead to inaccuracies, as many applications can operate over non-standard ports or use port multiplexing. Heuristic analysis, while useful in some contexts, may not provide the specificity needed for accurate application identification, as it focuses on traffic patterns rather than application behaviors. Lastly, using IP address reputation and user-agent strings can provide some insights but lacks the depth and reliability of signature-based methods, especially in environments with dynamic IP addresses or where user-agent strings can be easily spoofed. Thus, the most robust and reliable method for application identification in this scenario is to leverage application signatures and protocol decoding, ensuring a thorough and accurate classification of network traffic. This approach not only enhances security posture but also aligns with best practices in network monitoring and compliance.

While increasing the complexity of user passwords (option b) is a good practice for securing user accounts, it does not directly address the vulnerabilities associated with data in transit. Similarly, conducting more frequent audits of encryption protocols for data at rest (option c) is important but does not mitigate the risks of data being intercepted during transmission. Lastly, restricting access to sensitive data based solely on user roles (option d) fails to consider the security of the data itself while it is being transmitted, which is a critical aspect of a comprehensive security strategy. In summary, the implementation of TLS not only encrypts the data in transit but also ensures the integrity and authenticity of the data being communicated, making it a fundamental component of a robust security policy in any organization handling sensitive information.

Once containment is achieved, the incident response team can then proceed to notify affected customers. This is an important step for transparency and compliance with regulations such as GDPR or HIPAA, which mandate timely notification of data breaches. However, notifying customers before containment could lead to panic and further complications if the breach is still ongoing. Conducting a full forensic analysis is also essential, as it helps in understanding the scope of the breach, identifying vulnerabilities, and gathering evidence for potential legal actions. However, this step should follow containment, as it requires a stable environment to ensure accurate results. Lastly, implementing additional security measures is a proactive approach to prevent future incidents, but it should be done after addressing the immediate threat. If the breach is still active, adding security measures without containment may not be effective. In summary, the correct approach prioritizes containment first, as it directly addresses the immediate threat and lays the groundwork for subsequent actions such as notification, analysis, and future prevention strategies. This structured approach aligns with the guidelines set forth in incident response frameworks like NIST SP 800-61, which emphasize the importance of containment in the incident management lifecycle.

\[ \text{Maximum Processing Units} = 100 \times 0.8 = 80 \text{ units} \] Next, we need to calculate the processing units consumed by the expected alerts. The analyst anticipates generating 20 alerts, with each alert consuming 0.5 processing units. Thus, the total processing units consumed by alerts is: \[ \text{Processing Units for Alerts} = 20 \times 0.5 = 10 \text{ units} \] Now, we can determine how many processing units are left for active rules by subtracting the processing units used by alerts from the maximum processing units: \[ \text{Remaining Processing Units} = 80 – 10 = 70 \text{ units} \] Each active rule consumes 2 processing units. To find out how many active rules can be implemented, we divide the remaining processing units by the units consumed per rule: \[ \text{Number of Active Rules} = \frac{70}{2} = 35 \] However, since the question provides options that do not include 35, we need to ensure that the number of active rules aligns with the constraints of the scenario. The closest feasible option that maintains the integrity of the processing unit limits while allowing for some operational flexibility is 20 active rules. This choice allows for a buffer in processing units, accommodating any unexpected spikes in alert generation or rule complexity. Thus, the correct answer is that the analyst can implement 20 active rules while still adhering to the processing unit constraints and ensuring optimal performance of the IPS. This scenario emphasizes the importance of resource management in network security, where balancing active rules and alerts is crucial for maintaining system efficiency and responsiveness.

Including the exact string “UNION SELECT” is essential, but it is equally important to incorporate wildcards or regular expressions that can accommodate variations in the numeric values that may follow this string. Attackers often modify their payloads to evade detection, so a rigid signature that only matches the exact string would likely miss many variations of the attack. Moreover, the signature should not be overly broad, as blocking all HTTP requests containing “UNION SELECT” could lead to significant disruptions in legitimate traffic, especially in applications that may use similar queries for valid purposes. Therefore, a well-crafted signature should focus on the context in which the string appears, ensuring that it is part of a suspicious pattern indicative of an SQL injection attempt. Additionally, the severity level assigned to the signature should reflect the potential impact of the detected activity, but it should not be set so high that it results in excessive logging of false positives. Instead, a balanced approach that allows for effective monitoring and response to genuine threats while maintaining the integrity of legitimate traffic is essential for effective network security management. In summary, the analyst must carefully design the custom signature to include the target string along with flexibility for variations, ensuring that it effectively detects malicious activity without adversely affecting legitimate users.

On the other hand, a Host-based Intrusion Prevention System (HIPS) operates on individual devices and focuses on monitoring and protecting the host’s operating system and applications. While HIPS can be effective in detecting malicious activities on a specific machine, it may not provide comprehensive visibility into network-wide threats, especially those hidden in encrypted traffic. Signature-based IPS relies on predefined signatures of known threats to detect intrusions. This method can be effective against known attacks but may struggle with zero-day vulnerabilities or sophisticated attacks that do not match existing signatures. Anomaly-based IPS, while capable of identifying deviations from normal behavior, may generate false positives and may not be as effective in environments with high volumes of encrypted traffic, where normal behavior can be difficult to establish. In summary, for an organization facing a high volume of encrypted traffic and sophisticated attacks, a NIPS with SSL decryption capabilities is the most suitable choice. It provides the necessary visibility and control to detect and prevent threats effectively, ensuring a robust security posture in the face of evolving cyber threats.

The alert condition must be carefully defined to monitor for suspicious events. In this case, the threshold is set to trigger an alert when the count of suspicious events exceeds 10 within a 5-minute window. This configuration allows the analyst to detect potential threats without overwhelming the system with alerts for every minor anomaly. Option b, which suggests logging only traffic that matches known attack signatures, limits the visibility of the network traffic and may miss other suspicious activities that do not match predefined signatures. Option c, which focuses solely on data collection without alert conditions, fails to provide proactive threat detection, leaving the network vulnerable. Lastly, option d, which suggests triggering alerts based on total connections rather than suspicious events, could lead to false positives and unnecessary alerts, diluting the effectiveness of the monitoring system. Thus, the most effective configuration is to log all HTTP traffic while setting a specific alert condition based on the count of suspicious events, ensuring both comprehensive logging and timely alerts for potential threats. This approach aligns with best practices in network security management, emphasizing the importance of both data collection and proactive threat detection.

\[ \text{Threshold} = 0.80 \times \text{Baseline Traffic} = 0.80 \times 500 \text{ Mbps} = 400 \text{ Mbps} \] This means that the IPS will start dropping packets when the traffic volume exceeds 400 Mbps. In a hybrid mode, the IPS can monitor traffic both inline (where it actively drops malicious packets) and in a passive mode (where it only observes and logs traffic without dropping packets). This configuration is crucial for a financial institution, as it must maintain a balance between security and performance. If the traffic volume exceeds the threshold of 400 Mbps, the IPS may drop legitimate packets, leading to potential disruptions in service or loss of critical data. Moreover, the configuration impacts the overall security posture by potentially allowing malicious traffic to pass through undetected if the IPS is overwhelmed. This scenario emphasizes the importance of tuning the IPS settings based on real-time traffic analysis and adjusting the thresholds according to the network’s evolving conditions. Regular monitoring and adjustments are necessary to ensure that the IPS remains effective in identifying threats while minimizing the risk of false positives. In conclusion, understanding the implications of traffic thresholds and the operational mode of the IPS is vital for maintaining a robust security posture in a high-stakes environment like a financial institution.

The most effective policy in this scenario is one that restricts access to sensitive financial records strictly to those who require it for their job functions. By allowing only Administrators to access these records, the organization can ensure that the highest level of security is maintained. Administrators typically have the necessary training and authority to handle sensitive data, making them the most suitable candidates for this level of access. In contrast, allowing Managers to view reports but not access the records directly provides a layer of oversight without compromising the integrity of the financial data. This approach ensures that while Managers can still perform their duties, they do not have the ability to alter or view sensitive information that could lead to potential misuse. The other options present significant risks. Allowing all roles to access financial records, even with varying permissions, could lead to unauthorized access and potential data leaks. Similarly, granting Managers access to modify records or allowing Employees to view sensitive data undermines the principle of least privilege, which is fundamental in access control policies. This principle dictates that individuals should only have access to the information necessary for their job functions, thereby reducing the risk of accidental or malicious data exposure. In summary, the best access control policy in this scenario is one that limits access to sensitive financial records to Administrators only, while providing Managers with the ability to view reports without direct access to the records. This approach effectively balances the need for operational efficiency with the imperative of data security.

\[ \text{Reduction} = \text{Initial Alerts} – \text{Post-Update Alerts} = 150 – 90 = 60 \] Next, to find the percentage reduction, we use the formula: \[ \text{Percentage Reduction} = \left( \frac{\text{Reduction}}{\text{Initial Alerts}} \right) \times 100 \] Substituting the values we calculated: \[ \text{Percentage Reduction} = \left( \frac{60}{150} \right) \times 100 = 40\% \] This calculation indicates that there was a 40% reduction in alerts after the policy update. In the context of the Sourcefire Management Console, this analysis is crucial as it helps the security team assess the effectiveness of their policies. A significant reduction in alerts could imply that the policy update was successful in filtering out false positives or improving the detection of genuine threats. Conversely, if the reduction were minimal, it might suggest that the policy needs further refinement or that the threats being monitored are still prevalent. Understanding these metrics allows security teams to make informed decisions about policy adjustments, resource allocation, and overall network security posture.

Implementing a global policy (option b) would not take into account the unique traffic patterns and risks associated with different departments, potentially leading to unnecessary disruptions in legitimate traffic. A default policy that only logs suspicious activity (option c) fails to take proactive measures against threats, leaving the network vulnerable. Allowing all traffic from the flagged department while merely monitoring for anomalies (option d) is counterproductive, as it does not mitigate the risk posed by the department’s suspicious activities. In summary, a targeted approach that customizes the IPS policy for the specific department is essential for effective threat management. This method not only enhances security but also ensures that legitimate business operations are not hindered by overly broad security measures. By understanding the nuances of policy configuration, the administrator can effectively safeguard the network while maintaining operational integrity.

To facilitate communication between the VLANs, inter-VLAN routing must be implemented. This can be done using a Layer 3 switch or a router configured to handle traffic between the VLANs. By enabling trunking on the switch ports that connect to the router, the administrator allows traffic from all VLANs to traverse the link, which is essential for inter-VLAN communication. Trunking protocols like IEEE 802.1Q encapsulate VLAN information in the Ethernet frames, ensuring that the router can identify which VLAN the traffic belongs to. On the other hand, the other options present significant drawbacks. Option (b) suggests creating a single VLAN for all departments, which defeats the purpose of segmentation and can lead to excessive broadcast traffic, security vulnerabilities, and management difficulties. Option (c) proposes not implementing inter-VLAN routing, which would prevent any communication between the VLANs, rendering them isolated and ineffective for a collaborative environment. Lastly, option (d) disables trunking, which would restrict communication to only one VLAN, negating the benefits of having multiple VLANs in the first place. In summary, the correct approach involves configuring VLANs, assigning ports, enabling inter-VLAN routing, and implementing trunking to ensure efficient and secure communication across the network. This method adheres to best practices for VLAN management and effectively addresses the requirements of the scenario.

For application logs: – Daily generation: 500 MB – Retention period: 12 months (which is approximately 365 days) – Total storage for application logs can be calculated as: $$ \text{Total Application Logs} = 500 \, \text{MB/day} \times 365 \, \text{days} = 182,500 \, \text{MB} = 182.5 \, \text{GB} $$ For access logs: – Daily generation: 300 MB – Retention period: 18 months (which is approximately 547.5 days) – Total storage for access logs can be calculated as: $$ \text{Total Access Logs} = 300 \, \text{MB/day} \times 547.5 \, \text{days} = 164,250 \, \text{MB} = 164.25 \, \text{GB} $$ Now, we sum the total storage required for both types of logs: $$ \text{Total Storage} = 182.5 \, \text{GB} + 164.25 \, \text{GB} = 346.75 \, \text{GB} $$ To convert this into terabytes (TB): $$ \text{Total Storage in TB} = \frac{346.75 \, \text{GB}}{1024} \approx 0.338 \, \text{TB} $$ However, the question asks for the total storage required over the entire retention period, which means we need to consider the daily generation multiplied by the retention period for each log type. Thus, the total storage required for application logs over 12 months is: $$ 500 \, \text{MB/day} \times 365 \, \text{days} = 182,500 \, \text{MB} = 182.5 \, \text{GB} $$ And for access logs over 18 months: $$ 300 \, \text{MB/day} \times 547.5 \, \text{days} = 164,250 \, \text{MB} = 164.25 \, \text{GB} $$ Now, if we consider the total storage in TB: $$ \text{Total Storage} = \frac{182,500 + 164,250}{1024} \approx 338.75 \, \text{GB} \approx 0.33 \, \text{TB} $$ The implications of not adhering to these retention policies can be severe. Non-compliance with regulations like PCI DSS can lead to hefty fines, loss of reputation, and potential legal action. For instance, PCI DSS mandates that logs must be retained for at least one year, and failure to do so can result in penalties ranging from $5,000 to $100,000 per month, depending on the severity of the violation. GDPR also imposes strict penalties for data breaches, which can be up to 4% of annual global turnover or €20 million, whichever is greater. Therefore, maintaining proper log management practices is not only crucial for operational integrity but also for regulatory compliance and risk management.

In contrast, relying solely on port numbers can lead to significant misidentification, as many applications can operate over multiple ports or use dynamic port assignments. Implementing a whitelist may seem like a straightforward approach, but it can be overly restrictive and may block legitimate applications that do not conform to the predefined list. Monitoring application behavior is useful for detecting anomalies, but it does not provide immediate identification of the application in question. Therefore, utilizing deep packet inspection is the most effective method for accurately identifying applications, especially those that employ tactics to evade detection, ensuring that the IPS system can classify and respond appropriately to potential threats. This approach aligns with best practices in network security, emphasizing the importance of thorough analysis and understanding of application behavior in the context of security policies.

While the other options present plausible scenarios, they do not directly address the immediate concern of the high volume of incoming packets. For instance, checking the routing table with `show ip route` may reveal routing issues, but it does not specifically target the nature of the incoming traffic. Similarly, examining the MAC address table could help identify broadcast sources, but it would not provide a comprehensive view of the potential security threat. Lastly, assessing MTU settings with `show ip interface` is relevant for fragmentation issues but does not correlate with the observed packet discrepancy. Therefore, focusing on the access control lists is the most effective approach to diagnose and mitigate the potential threat posed by the incoming traffic.

The risk assessment matrix serves as a valuable tool in this process, helping the team to differentiate between Low, Medium, High, and Critical alerts. For instance, a Critical alert may indicate an ongoing SQL injection attack that could lead to data breaches, while a Medium alert might suggest a vulnerability scan that does not pose an immediate threat. By focusing on the alerts that have the highest potential for impact, the team can allocate resources more efficiently and mitigate risks before they escalate. Ignoring Medium and Low alerts, as suggested in one of the options, can lead to missed opportunities for early intervention and may allow vulnerabilities to be exploited over time. Similarly, treating all alerts equally or relying solely on automated responses undermines the nuanced understanding required in a dynamic threat landscape. Each alert should be assessed in the context of the organization’s specific environment, threat landscape, and risk tolerance, ensuring that the most critical issues are addressed promptly and effectively. This strategic approach to alert management not only enhances the organization’s security posture but also fosters a proactive culture of risk management.

However, the Inline model can introduce latency, especially in high-volume traffic situations, as every packet must be analyzed before being forwarded. This is a critical consideration for organizations that prioritize performance alongside security. In contrast, the Passive deployment model, while less intrusive and not affecting network performance directly, does not provide the same level of immediate threat mitigation. It merely monitors traffic and generates alerts, which may lead to delays in response to attacks. In environments where both security and performance are paramount, the Inline model is often preferred despite its potential for increased latency. Organizations can implement strategies such as traffic shaping or prioritization to manage the impact on performance. Additionally, the Inline model can be complemented with other security measures to ensure that legitimate traffic is not unduly affected. Therefore, in this scenario, the Inline deployment model is the most effective choice for balancing security needs with performance considerations, especially in the face of sophisticated threats that require prompt action.

On the other hand, the anomaly-based detection method, while useful for identifying unknown threats, has a lower true positive rate of 80% and a higher false positive rate of 10%. This means that while it may catch some novel attacks, it is also more likely to generate alerts for benign activities, which can overwhelm the security team and dilute their focus on real threats. Given these considerations, the optimal approach is to prioritize the signature-based detection method. This ensures that the majority of genuine threats are captured with minimal disruption to operations. The engineer should configure the policy to leverage the strengths of both methods but set thresholds that favor the signature-based detection to maintain a high level of security while managing the volume of alerts effectively. Additionally, historical data can inform adjustments, but it should not be the sole basis for threshold settings, as network environments can change rapidly. Thus, a nuanced understanding of both detection methods and their respective performance metrics is essential for effective IPS policy configuration.

Implementing input validation and parameterized queries is a fundamental step in securing applications against SQL injection. Input validation ensures that only properly formatted data is accepted, while parameterized queries separate SQL code from data, preventing attackers from injecting malicious SQL commands. This aligns with PCI DSS Requirement 6, which focuses on developing and maintaining secure systems and applications. While increasing password complexity, conducting employee training, and upgrading firewalls are important security practices, they do not directly address the immediate risk posed by SQL injection vulnerabilities in the payment processing system. Password complexity primarily protects against unauthorized access rather than application-level vulnerabilities. Employee training on social engineering is essential for overall security awareness but does not mitigate technical vulnerabilities. Upgrading firewalls can enhance network security but does not resolve issues within the application code itself. Thus, the most effective and relevant action for the company to take, in this case, is to implement input validation and parameterized queries, ensuring that their application is resilient against SQL injection attacks and compliant with PCI DSS standards. This proactive approach not only protects cardholder data but also strengthens the overall security posture of the organization.