A system that monitors important operating system files is an example of a HIDS, while a system what is intrusion detection system pdf analyzes incoming network traffic is an example of a NIDS. Some IDS have the ability to respond to detected intrusions.

Firewalls limit access between networks to prevent intrusion and do not signal an attack from inside the network. An IDS describes a suspected intrusion once it has taken place and signals an alarm. An IDS also watches for attacks that originate from within a system. Once an attack is identified, or abnormal behavior is sensed, the alert can be sent to the administrator. An example of an NIDS would be installing it on the subnet where firewalls are located in order to see if someone is trying to break into the firewall.

Ideally one would scan all inbound and outbound traffic, however doing so might create a bottleneck that would impair the overall speed of the network. NID Systems are also capable of comparing signatures for similar packets to link and drop harmful detected packets which have a signature matching the records in the NIDS. When we classify the design of the NIDS according to the system interactivity property, there are two types: on-line and off-line NIDS, often referred to as inline and tap mode, respectively. On-line NIDS deals with the network in real time.

Off-line NIDS deals with stored data and passes it through some processes to decide if it is an attack or not. A HIDS monitors the inbound and outbound packets from the device only and will alert the user or administrator if suspicious activity is detected. It takes a snapshot of existing system files and matches it to the previous snapshot. If the critical system files were modified or deleted, an alert is sent to the administrator to investigate. An example of HIDS usage can be seen on mission critical machines, which are not expected to change their configurations.

Signature-based IDS refers to the detection of attacks by looking for specific patterns, such as byte sequences in network traffic, or known malicious instruction sequences used by malware. Although signature-based IDS can easily detect known attacks, it is impossible to detect new attacks, for which no pattern is available. The basic approach is to use machine learning to create a model of trustworthy activity, and then compare new behavior against this model. In particular, NTA deals with malicious insiders as well as targeted external attacks that have compromised a user machine or account.