(CYB220) RESPOND TO BOTH OF THE PEER POSTS BELOW IN ONE PARAGRAPH EACH ANSWERING THE FOLLOWING QUESTION(S)

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QUESTION(S): In response to your peers, apply a systems thinking approach and provide recommendations at a different intelligence cycle step to resolve the issue or reduce the impact of false positives or negatives.

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(CYB220) RESPOND TO BOTH OF THE PEER POSTS BELOW IN ONE PARAGRAPH EACH ANSWERING THE FOLLOWING QUESTION(S)
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PEER POST # 1

The Intelligence Cycle for Network Security Monitoring (NSM) is a critical aspect of protecting an organization’s digital assets. It includes steps like planning, collection, processing, analysis, dissemination, and feedback. For this discussion, let’s focus on the analysis step. In the analysis phase, data collected from various sources, including Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS), are studied to identify trends, patterns, and anomalies. This step is crucial because it translates raw data into actionable intelligence. However, the effectiveness of this phase can be significantly impacted by false positives and negatives from IDS/IPS systems. False positives, where the system incorrectly identifies benign activity as malicious, can lead to ‘alert fatigue’. This is when security teams are overwhelmed by the number of alerts and may start ignoring them or may not have the resources to investigate each one thoroughly. This can lead to important alerts being overlooked and potential threats slipping through the net. On the other hand, false negatives, where the system fails to detect actual malicious activity, are even more dangerous. They represent a direct failure of the security system. If a threat is not detected, it can’t be analyzed, and therefore, it can’t be mitigated. This leaves the network vulnerable to attacks, potentially leading to data breaches, downtime, and financial losses. Therefore, it’s crucial to continually fine-tune IDS/IPS systems to minimize false positives and negatives. This could involve adjusting the sensitivity of the system, regularly updating threat databases, and using machine learning techniques to improve threat detection accuracy. This will ensure that the analysis phase of the intelligence cycle is as effective and accurate as possible, leading to better decision making and more robust network security.

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PEER POST # 2

In this week’s discussion we will look at two factors “Intelligence Cycle for NSM” section and how IDS and IPS technologies help you gather data about activities in your network” and describe the steps of intelligence cycle and how IDS/IPS false positive or negative impacts. Network Security Monitoring (NSM) is a modern corporate security approach that identifies IT network breaches by gathering and analyzing security data. It links unlawful activities to established threats and prioritizes vulnerability-centric defense, detection-focused network data collection, signature-based detection, and automation-focused data collection. NSM is more effective against zero-day vulnerabilities and ensures network security.

The analysis phase of the intelligence cycle involves analyzing data to extract insights, spot trends, and evaluate potential threats or threats. This process combines unprocessed data to provide useful intelligence that can assist defense strategies and decision-making. However, IDS/IPS systems can produce false positives or negatives, which can contaminate the dataset, waste time and resources, and reduce confidence in the system’s accuracy. False positives can expose organizations to risks, while false negatives can compromise situational awareness and impair the accuracy of threat assessments, leaving sensitive data and assets open to abuse by hostile actors.