An intrusion detection system (IDS) is a software application or hardware appliance designed for monitoring a network to identify suspicious activities or known threats. It can also monitor for network policy violations.
An IDS is a passive monitoring system as it only reports malicious activity but cannot proactively block such activity in a network.
Intrusion detection systems (IDS) are broadly two types:
- Network-based: A network-based IDS (NIDS) monitors and analyzes network data packets, usually at the router level, and alerts about suspicious activity.
- Host-based: A host-based IDS (HIDS) is deployed on the host its monitoring and analyzes the dynamic behavior and state of the host and its network interfaces. It also monitors various parts of the host, including log files, file systems, and RAM.
Network intrusion detection systems can further be categorized based on the detection method used:
- Signature-based: A signature-based IDS uses a database or reference of the fingerprints of known threats, malicious content, and malware to analyze the traffic or content it monitors. The fingerprint database is updated whenever new malware is detected. This helps a signature-based IDS detect suspicious activity more accurately and eliminate most false positives. However, this type of IDS is inefficient in detecting zero-day exploits as it only relies on the signatures of known threats.
- Anomaly-based: An anomaly-based IDS initially establishes a baseline of acceptable behavior on the system or network it monitors. It then compares the activity in the network/system with the baseline to identify abnormalities. Due to this approach, an anomaly-based IDS can identify previously unknown threats and zero-day exploits. However, it requires deliberate efforts to build a more accurate baseline behavioral model as an inefficient model can lead to false positives and negatives.
- Hybrid-IDS: A hybrid-IDS uses a hybrid method of signature- and anomaly-based detection to identify suspicious activity more accurately and reduce error rates. This approach is potentially better than using signature- or anomaly-based detection in isolation.
Along with the above classifications, there are additional IDS classifications based on their functionality and capabilities, such as VM-based and stack-based IDS.
An IDS is typically placed on a network or host as per the monitoring requirements. It then examines the data packets flowing through the network and reports any activity seeming suspicious.
An IDS only monitors and does not block malicious activity. Therefore, it requires attention from security analysts to understand an ongoing attack and stop it from becoming a security breach.
More and more organizations are using IDS as a part of their security solution suite instead of deploying it as a standalone tool. It is essential to strategize how an organization handles its IDS alerts, as taking action is critical after identifying an ongoing attack.
Typically, managing an IDS presents three challenges:
- False positives and false negatives: An IDS can occasionally identify acceptable traffic as malicious. However, the rate of false positives can go up if it is not managed or adapted to the usual behavior in the network.
On the other hand, it may not identify malicious data packets accurately, leading to inefficient monitoring and exposing the organization to more significant risks.
- Security analysts: Any alert from an IDS requires further analysis and mitigation from a security analyst. Accordingly, staffing security analysts—who are generally in more demand—can be challenging.
- Encrypted traffic: If an IDS is monitoring encrypted data packets, it can become challenging to differentiate suspicious activity from acceptable behavior. This inefficiency presents a more significant threat risk to an organization.
It also presents challenges when expanding a network beyond the capacity of an IDS. For example, if an IDS can handle 1 Gbps of network traffic, expanding the network to 2 Gbps can severely impact the efficiency of the IDS.
An IDS is an essential part of an organization’s cybersecurity posture. As a passive monitoring tool, it can deliver increased benefits when well integrated into a broader network security strategy.
Generally, organizations use a Security Information and Event Management (SIEM) system to centrally collect, monitor, analyze, and manage security logs and events. By connecting an IDS with a SIEM system, an organization can centrally manage IDS alerts on broader security events and correlate them more effectively to deduce more meaningful, actionable threat information.
Some organizations use next-generation firewalls and intrusion prevention systems (IPS), which extends IDS functionally by introducing blocking mechanisms. This helps to identify suspicious activity and proactively block such behavior; however, due to the possibility of false positives, an IPS may also block legitimate network traffic—which could disrupt business operations.
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