IPS and IDS Explained – Know the Variances and Use Cases

IDS solutions look for patterns in network traffic and alert IT personnel when those patterns appear. This approach can be practical, but it depends on the size of a signature database and leaves room for gaps that exploits can use to slip past. IPS solutions take the next step and try to stop detected threats from impacting the network. They also log incidents and alert security admins.


What is IPS vs IDS? While IPS and IDS are similar in that they monitor, alert, learn, and log attacks, the main difference is that IPS goes one step further than IDS and prevents threats from impacting your business. IPS uses signature-based detection or an ML-powered behavior model to detect and thwart cybersecurity breaches before they cause damage. IDS is a diagnostic tool that recognizes malicious network packets and creates notifications for the user to take action upon. An IPS takes this further and is configured with automated responses that execute during an incident response event. This gives an IPS a significant advantage over IDS solutions as the latter requires users to take the initiative after receiving an alert about an incident. IDS solutions can be susceptible to the same attacks they are designed to identify due to their reliance on IP attribution, which can be falsified or scrambled, and lack of the ability to process encrypted packets. Also, depending on the method of detection used, an IDS can face a lag between the discovery of new attack vectors and their inclusion in a signature database. Anomaly detection can mitigate this issue by spotting malicious data organically rather than referencing previous attacks, but, of course, these tools need to be configured appropriately for this to work.

False Positives

A false positive occurs when an IDS or IPS system incorrectly flags legitimate activity as a threat. This can lead to unnecessary alerts, traffic slowdowns, and unauthorized actions that require a lot of work from your security team to resolve. This problem typically comes from network IDS technologies that don’t consider the host vulnerability profile when identifying an attack. For example, if your network is only comprised of Linux systems, a Windows remote procedure call attack might trigger an alert on a nonvulnerable system, causing it to slow down and possibly even prevent other systems from functioning correctly. Newer IDS products use passive operating system fingerprinting to build host profile information into their detection frameworks to reduce this false positive. Unlike IDS, an IPS works in real-time and can take swift action to stop attacks before they can do damage. Depending on your IPS settings and policy, it may even quarantine or block the malicious data. This level of protection reduces the workload for your security department while reducing the opportunity for attackers to continue embedding themselves in the network. IPS solutions detect threats by analyzing the content of current network traffic. They can use several techniques, including signature-based detection, which compares unique signatures in exploit code with observed events. This can deflect previously spotted exploits but could be more effective regarding zero-day exploits and other novel attacks. Behavioral-based IPS uses a baseline model of normal behavior to identify anomalous activity and can be more accurate than signature-based detection. However, they still suffer from many false positives and can be difficult to adjudicate.

Blind Spots

Signature-based detection identifies malicious code by matching its characteristics to patterns found in network traffic. This approach requires a comprehensive signature database regularly updated to include new attack patterns. But it also increases the risk of false positives (benign packets mistaken for threats). IPS detects and protects against malware, ransomware, phishing, denial-of-service attacks, and other cyberattacks that exploit vulnerabilities or spoof security protocols. These solutions operate at the nexus of your internal network and public internet and monitor every network packet to identify signs of an intrusion. They can detect unauthorized servers and clients, rogue applications, port scanning tools, network eavesdropping, and other suspicious activities. IDS and IPS are often deployed on critical devices and host your organization wants to secure, such as a firewall or a router. This reduces the burden on human security teams by allowing them to focus on more critical tasks, such as ensuring compliance with regulatory directives. The main advantage of an IDS is that it can scan and observe traffic throughout the entire network, including wireless networks. IDS solutions typically work as standalone appliances but can be integrated into a gateway device or firewall to align with your network. This way, IDS and IPS can intercept a suspicious or unauthorized packet before it enters the more extensive network and alert your team for further investigation.


An IPS can prevent attacks from taking hold by stopping them at the detection phase. It does this with automated responses, allowing IT to reduce the number of security incidents that need manual remediation. IPS can also stop threats from spreading by changing the content of malicious traffic. This is typically accomplished by removing infected file attachments and other elements that would otherwise trigger antivirus software. While IPS solutions can prevent attacks from taking hold, they cannot block all attack vectors. For example, some IPS technologies cannot detect SSL-encrypted traffic. This can be problematic since attackers can use SSL to conceal their identity. In other cases, an IPS might not process encrypted packets correctly, which could result in a loss of information. IDS and IPS can detect phishing, ransomware, malware installation and download, denial of service (DoS), man-in-the-middle attacks, zero-day attacks, SQL injection, and other cyber-attacks. They can also detect unauthorized network access by monitoring internal traffic. The main issue is that these programs must be configured appropriately to avoid false positives. Signature-based detection relies on an enormous trove of known signature patterns that characterize existing threats. However, it can take some time between when a new type of attack is discovered and when its signature is added to the signature database.

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