An Intrusion Detection System (IDS) is an additional protection measure that helps ward off computer intrusions. IDS systems can be software and hardware devices used to detect an attack. IDS products are used to monitor connection in determining whether attacks are been launched. Some IDS systems just monitor and alert of an attack, whereas others try to block the attack.
Intrusion detection is the act of detecting unwanted traffic on a network or a device. An IDS can be a piece of installed software or a physical appliance that monitors network traffic in order to detect unwanted activity and events such as illegal and malicious traffic, traffic that violates security policy, and traffic that violates acceptable use policies. Many IDS tools will also store a detected event in a log to be reviewed at a later date or will combine events with other data to make decisions regarding policies or damage control. An IPS is a type of IDS that can prevent or stop unwanted traffic. The IPS usually logs such events and related information.
Several types of IDS technologies exist due to the variance of network configurations. Each type has advantages and disadvantage in detection, configuration, and cost. Specific categories will be discussed in detail in Section 3, Technologies.
A Network Intrusion Detection System (NIDS) is one common type of IDS that analyzes network traffic at all layers of the Open Systems Interconnection (OSI) model and makes decisions about the purpose of the traffic, analyzing for suspicious activity. Most NIDSs are easy to deploy on a network and can often view traffic from many systems at once. A term becoming more widely used by vendors is “Wireless Intrusion Prevention System” (WIPS) to describe a network device that monitors and analyzes the wireless radio spectrum in a network for intrusions and performs countermeasures.
A wireless local area network (WLAN) IDS is similar to NIDS in that it can analyze network traffic. However, it will also analyze wireless-specific traffic, including scanning for external users trying to connect to access points (AP), rogue APs, users outside the physical area of the company, and WLAN IDSs built into APs. As networks increasingly support wireless technologies at various points of a topology, WLAN IDS will play larger roles in security. Many previous NIDS tools will include enhancements to support wireless traffic analysis.
- Network Behavior Anomaly Detection
Network behavior anomaly detection (NBAD) views traffic on network segments to determine if anomalies exist in the amount or type of traffic. Segments that usually see very little traffic or segments that see only a particular type of traffic may transform the amount or type of traffic if an unwanted event occurs. NBAD requires several sensors to create a good snapshot of a network and requires benchmarking and baselining to determine the nominal amount of a segment’s traffic.
Host-based intrusion detection systems (HIDS) analyze network traffic and system-specific settings such as software calls, local security policy, local log audits, and more. A HIDS must be installed on each machine and requires configuration specific to that operating system and software.
3.3. Detection Types
An IDS can use signature-based detection, relying on known traffic data to analyze potentially unwanted traffic. This type of detection is very fast and easy to configure. However, an attacker can slightly modify an attack to render it undetectable by a signaturebased IDS. Still, signature-based detection, although limited in its detection capability, can be very accurate
b). Anomaly-Based Detection
An IDS that looks at network traffic and detects data that is incorrect, not valid, or generally abnormal is called anomaly-based detection. This method is useful for detecting unwanted traffic that is not specifically known. For instance, an anomaly-based IDS will detect that an Internet protocol (IP) packet is malformed. It does not detect that it is malformed in a specific way, but indicates that it is anomalous.
c). Stateful Protocol Inspection
Stateful protocol inspection is similar to anomalybased detection, but it can also analyze traffic at the network and transport layer and vender-specific traffic at the application layer, which anomaly-based detection cannot do.
d). False Positives and Negatives
It is impossible for an IDS to be perfect, primarily because network traffic is so complicated. The erroneous results in an IDS are divided into two types: false positives and false negatives. False positives occur when the IDS erroneously detects a problem with benign traffic. False negatives occur when unwanted traffic is undetected by the IDS. Both create problems for security administrators and may require that the system be calibrated. A greater number of false positives are generally more acceptable but can burden a security administrator with cumbersome amounts of data to sift through. However, because it is undetected, false negatives do not afford a security administrator an opportunity to review the data.
3.4. System Components
IDSs are generally made up of the following main types of components—u Sensors—These are deployed in a network or on a device to collect data. They take input from various sources, including network packets, log files, and system call traces. Input is collected, organized, and then forwarded to one or more analyzers. u Analyzers—Analyzers in an IDS collect data forwarded by sensors and then determine if an intrusion has actually occurred. Output from the. analyzers should include evidence supporting the intrusion report. The analyzers may also provide recommendations and guidance on mitigation steps. u User interface—The user interface of the IDS provides the end user a view and way to interact with the system. Through the interface the user can control and configure the system. Many user interfaces can generate reports as well. u Honeypot—In a fully deployed IDS, some administrators may choose to install a “honeypot,” essentially a system component set up as bait or decoy for intruders. Honeypots can be used as early warning systems of an attack, decoys from critical systems, and data collection sources for attack analyses. Many IDS vendors maintain honeypots for research purposes, and to develop new intrusion signatures. Note that a honeypot should only be deployed when the organization has the resources to maintain it. A honeypot left unmanaged may become a significant liability because attackers may use a compromised honeypot to attack other systems.