An intrusion detection system (IDS) is a network security tool that monitors network traffic and devices for known malicious activity, suspicious activity or security policy violations1. An IDS can generate alerts when it detects any potential threats, but not all alerts are accurate or relevant. There are two types of errors that can affect the performance and reliability of an IDS: false positives and false negatives2.
A false positive is when an IDS incorrectly flags a benign or normal activity as malicious or suspicious. For example, an IDS may alert on a legitimate network scan or a harmless software update. False positives can reduce the credibility and efficiency of an IDS, as they can overwhelm the security team with unnecessary alerts, distract them from the real threats, and cause them to ignore or disable the IDS3.
A false negative is when an IDS fails to flag a malicious or suspicious activity as such. For example, an IDS may miss a stealthy or novel attack that does not match any known signatures or patterns. False negatives can compromise the security and integrity of the network, as they can allow attackers to bypass the IDS and cause damage or steal data without being detected4.
The risk practitioner should recommend to analyze the alerts to minimize the false positives, because this is the best way to improve the accuracy and usefulness of the IDS. By analyzing the alerts, the risk practitioner can:
Identify the sources and causes of the false positives, such as misconfigured or outdated IDS rules, network anomalies, or legitimate traffic that resembles malicious traffic5.
Adjust or fine-tune the IDS settings, such as the alert threshold, the sensitivity level, the detection method, or the rule base, to reduce the number of false positives without increasing the risk of false negatives.
Validate or verify the alerts with other sources of information, such as logs, network traffic analysis, or threat intelligence, to confirm or dismiss the alerts as true or false positives.
Prioritize or classify the alerts based on their severity, impact, or likelihood, to focus on the most critical or relevant alerts and avoid alert fatigue.
The other options are not the best course of action, because:
Resetting the alert threshold based on peak traffic is not a reliable or effective way to minimize the false positives, as it may also increase the risk of false negatives. The alert threshold is the level of activity or deviation that triggers an alert from the IDS. If the threshold is set too high, the IDS may miss some malicious or suspicious activity that occurs below the threshold. If the threshold is set too low, the IDS may generate too many alerts for normal or benign activity that exceeds the threshold. The optimal threshold depends on various factors, such as the network size, topology, traffic volume, and baseline. Peak traffic is not a good indicator of the optimal threshold, as it may vary depending on the time, day, or season, and it may not reflect the normal or expected network behavior.
Analyzing the traffic to minimize the false negatives is not the main issue or goal in this scenario, as the problem is the high number of alerts, not the low number of alerts. Analyzing thetraffic can help to identify the malicious or suspicious activity that the IDS may have missed, but it does not address the root cause of the false positives or improve the IDS performance. Moreover, analyzing the traffic can be time-consuming and resource-intensive, especially for large or complex networks, and it may require specialized tools or skills that the risk practitioner may not have.
Sniffing the traffic using a network analyzer is not a suitable or feasible option in this scenario, as it may violate the privacy or security policies of the network or the organization. Sniffing the traffic means capturing and inspecting the network packets that are transmitted or received by the devices on the network. A network analyzer is a tool that can perform this function and display the packet data in a readable format. However, sniffing the traffic can also expose sensitive or confidential information, such as passwords, usernames, or credit card numbers, that may be contained in the packets. Therefore, sniffing the traffic may require authorization or consent from the network owners or users, and it may be restricted or prohibited by law or regulation.
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What is an intrusion detection system (IDS)? - IBM
Intrusion detection system - Wikipedia
What Are Intrusion Detection Systems? - MUO
12 Best Intrusion Detection System (IDS) Software 2024 - Comparitech
What is an Intrusion Detection System (IDS)? - Fortinet
[False Positive and False Negative in Intrusion Detection System]
[False Positives and False Negatives in Intrusion Detection Systems]
[How to Reduce False Positives for Your IDS/IPS]
[How to Set the Right Alert Thresholds for Your IDS/IPS]
[Network Traffic Analysis: What It Is and How It Works]
[What is a Network Analyzer? - Definition from Techopedia]
