Intrusion Detection System(IDS) and What are the types of IDS

In this blog, we will learn about the IDS i.e. Intrusion Detection System which is one of the most important threats which is attacked by intruders. So we will learn how to detect it and which tool is being used. So let’s get started with the blog.

Introduction to Intrusion Detection System
Define Intruders
Define Intrusion
Types of Intrusion Detection Systems
- A) Network-based Intrusion Detection System (NIDS)
- B) Host-based Intrusion Detection System (HIDS)
Methods for Intrusion Detection System
- A) Signature-based Intrusion Detection System (IDS)
- B) Anomaly-based Intrusion Detection System (IDS)
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Introduction to Intrusion Detection System

Intrusion Detection System (IDS) is a security technology that monitors and analyzes network traffic or system events to identify and respond to potential security breaches or unauthorized activities within a computer network or system. It serves as an additional layer of defense to complement other security measures like firewalls and antivirus software.

The primary purpose of an IDS is to detect and alert administrators or security personnel about suspicious or malicious activities that may indicate an ongoing or attempted intrusion.

It examines network packets, log files, or system events in real-time or retrospectively. IDS can be deployed at various points within a network, such as at the network perimeter, on individual hosts, or at critical network segments.

Define Intruders

An intruder refers to an individual or entity that attempts to gain unauthorized access to a computer system, network, or data. Intruders can be classified into different categories based on their intentions, expertise, and motivations.

There are two types of Intruders in Ethical Hacking:

A) Inside Intruder (Misfeasor):

Inside intruders, also known as insider threats, are individuals who have authorized access to a computer system, network, or data within an organization. These individuals may be employees, contractors, or business partners who abuse their privileges or misuse their access for malicious purposes.

Inside intruders have knowledge of the organization’s infrastructure, security mechanisms, and sensitive information, making their attacks potentially more damaging. They may steal confidential data, sabotage systems, introduce malware, or cause other harm from within the organization.

B) Outside Intruder (Masquerader):

Outside intruders are individuals or entities who attempt to gain unauthorized access to a computer system, network, or data from outside the organization. They are external to the targeted organization and typically operate from remote locations. Outside intruders can include hackers, crackers, script kiddies, state-sponsored actors, or organized crime groups.

These attackers exploit vulnerabilities in the organization’s defenses, such as weak passwords, unpatched software, or misconfigured systems, to gain unauthorized access, steal data, disrupt services, or carry out other malicious activities.

Outside intruders are a common focus of security measures like firewalls, intrusion detection systems, and external-facing security controls.

Define Intrusion

An intrusion refers to an unauthorized or malicious activity that breaches the security measures of a computer system, network, or application. It involves an attempt to gain unauthorized access, manipulate data, disrupt services, or perform other malicious actions that compromise the targeted system’s confidentiality, integrity, or availability.

Intrusions can take various forms, including:

Unauthorized Access: Intruders may attempt to gain access to a computer system or network without proper authorization. This can involve exploiting vulnerabilities in software, leveraging weak or compromised credentials, or bypassing security controls.
Malware Infections: Intrusions can occur through the introduction of malicious software, commonly known as malware. Malware can be introduced through email attachments, infected websites, removable media, or compromised software. Once installed, malware can perform various malicious activities, such as stealing sensitive information, encrypting files for ransom, or enabling unauthorized remote access.
Network Attacks: Intruders can target computer networks using various attack techniques. This includes activities like network scanning, probing for vulnerabilities, exploiting weaknesses in network protocols, or launching distributed denial-of-service (DDoS) attacks to overwhelm network resources.

Detecting and responding to intrusions is a critical aspect of computer security. Intrusion detection systems (IDS) and intrusion prevention systems (IPS) are employed to monitor and analyze network traffic, system logs, and other indicators for signs of unauthorized activities.

When an intrusion is detected, appropriate incident response procedures are initiated to mitigate the impact, remove the intruder’s presence, and restore the affected systems’ security.

Types of Intrusion Detection Systems

There are two types of Intrusion Detection Systems which are as follows:

A) Network-based Intrusion Detection System (NIDS)

A Network-based Intrusion Detection System (NIDS) is a security technology that monitors network traffic to detect and respond to potential security threats and intrusions. It is designed to analyze network packets in real time as they flow through specific points within a computer network, such as switches or routers.

The primary goal of NIDS is to identify malicious or suspicious activities by examining the contents and characteristics of network packets. It compares the observed network traffic against known attack signatures or predefined behavioral patterns to detect potential intrusions. NIDS can operate in either a passive or active mode.

Here are the key components and functionalities of a NIDS:

A) Anomaly-based Detection: In addition to signature-based detection, NIDS can also employ anomaly-based detection techniques. This involves establishing a baseline of normal network behavior by analyzing historical network traffic patterns. Any deviations from the established baseline can indicate potential intrusions or abnormal activities. Anomaly-based detection helps identify previously unseen or zero-day attacks that don’t have known signatures.

B) Traffic Analysis: NIDS performs deep packet inspection to analyze the contents of network packets, including application-layer protocols, payload contents, and other relevant information. It helps identify specific attack methods, such as port scanning, DoS attacks, SQL injection, or buffer overflow attempts.

C) Alert Generation and Response: When a potential intrusion is detected, NIDS generates alerts to notify security administrators or personnel. These alerts provide details about the detected threat, including the type of attack, source IP address, destination IP address, and other relevant information. Security teams can then investigate the alerts, assess the severity of the intrusion, and initiate appropriate incident response procedures to mitigate the threat.

NIDS plays a crucial role in network security by providing real-time monitoring and detection capabilities. It helps organizations identify and respond to potential intrusions, protect sensitive data, and maintain the integrity and availability of their computer networks.

B) Host-based Intrusion Detection System (HIDS)

A Host-based Intrusion Detection System (HIDS) is a security technology that focuses on monitoring and analyzing activities occurring on individual host systems to detect potential security breaches or unauthorized activities. Unlike network-based intrusion detection systems (NIDS) that monitor network traffic, HIDS operates directly on the host, examining system logs, file integrity, and other host-specific events.

Here are the key components and functionalities of a HIDS:

File Integrity Monitoring (FIM): HIDS monitors the integrity of critical system files and directories by regularly comparing them against known secure baselines or checksum values. Any unauthorized modifications or tampering of files can indicate a potential intrusion or compromise.

Behavior Analysis: HIDS establishes a baseline of normal host behavior by analyzing historical data and activities on the system. It then compares current activities and behaviors against the established baseline. Any deviations or anomalies, such as unusual network connections, abnormal process activities, or unauthorized system changes, can indicate a potential intrusion.

Malware Detection: HIDS can incorporate malware detection capabilities by scanning files, processes, and memory for known malware signatures or suspicious behavior associated with malware activity. This helps identify and respond to malware infections on the host system.

Alert Generation and Response: When a potential intrusion or suspicious activity is detected, HIDS generates alerts or notifications to inform administrators or security personnel. These alerts provide details about the detected event, including the affected host, type of activity, severity level, and any other relevant information. Security teams can then investigate the alerts, assess the impact of the intrusion, and take appropriate response measures to mitigate the threat.

HIDS provides an additional layer of defense by focusing on host-specific activities and events. It helps organizations detect unauthorized access, malware infections, insider threats, or other suspicious activities occurring at the individual host level. By monitoring and analyzing host-based events, HIDS enhances the overall security posture and helps protect critical assets and data residing on the host systems.

Methods for Intrusion Detection System

There are two methods for an Intrusion Detection System which are as follows:

A) Signature-based Intrusion Detection System (IDS)

A Signature-based Intrusion Detection System (IDS) is a type of IDS that relies on known attack signatures or patterns to detect potential intrusions or malicious activities. It compares network traffic or system events against a database of pre-defined signatures, which are specific characteristics or sequences of data associated with known attacks or malicious behavior.

Here are the key components and functionalities of a Signature-based IDS:

Signature Database: The IDS maintains a database of signatures, which are essentially patterns or rules that represent known attack patterns or malicious activities. These signatures can be created based on analyzing network traffic, system logs, or other sources of security intelligence.
Packet or Log Analysis: The IDS analyzes network packets or system logs in real-time or retrospectively to compare them against the signatures in the database. It examines the content, headers, and attributes of network packets or log entries to identify matches with the known attack signatures.
Alert Generation: When a match is found between the observed network traffic or system events and a signature in the database, the IDS generates an alert or notification. The alert provides information about the detected threat, including the type of attack, source IP address, destination IP address, timestamps, and any other relevant details.
Response and Mitigation: Upon receiving the alert, security administrators or personnel can investigate the detected intrusion, assess its severity, and take appropriate response actions. This may involve blocking network traffic from specific IP addresses, isolating compromised hosts, or initiating incident response procedures.

Advantages of Signature-based IDS:

Effectiveness: Signature-based IDS are highly effective in detecting known attacks and well-established patterns of malicious behavior. They can quickly identify and respond to known threats, such as common malware variants or network-based attacks with well-defined signatures.
Low False Positive Rate: Signature-based IDS typically have a lower false positive rate compared to other detection methods. Since they match observed activities against pre-defined signatures, the likelihood of generating false alarms due to normal network or system behavior is relatively low.
Easy Deployment: Signature-based IDS are relatively easy to deploy and configure. Once the signature database is created or obtained, it can be updated periodically to include new signatures or refine existing ones.

Limitations of Signature-based IDS:

Inability to Detect New or Unknown Attacks: Signature-based IDS are limited in their ability to detect new or previously unseen attacks, also known as zero-day exploits. If an attack does not match any signature in the database, it may go undetected.
Dependency on Signature Updates: Signature-based IDS require regular updates to the signature database to keep pace with new threats and attack techniques. If the database is not kept up-to-date, the IDS may fail to detect emerging threats.

Signature-based IDS plays an important role in network security by providing a fast and efficient means of detecting known attacks and malicious behavior. However, they should be used in conjunction with other detection methods, such as anomaly-based detection or behavioral analysis, to enhance overall security effectiveness.

B) Anomaly-based Intrusion Detection System (IDS)

An Anomaly-based Intrusion Detection System (IDS) is a type of IDS that focuses on detecting deviations or anomalies from normal patterns of behavior within a computer system, network, or application. Instead of relying on pre-defined attack signatures like signature-based IDS, anomaly-based IDS establishes a baseline of normal behavior and identifies activities that deviate from this baseline.

Here are the key components and functionalities of an Anomaly-based IDS:

Baseline Establishment: The IDS collects and analyzes historical data on system or network behavior to establish a baseline of normal activities. This baseline represents the expected behavior of the system or network under typical circumstances. It takes into account factors such as network traffic patterns, system resource usage, user behavior, and application interactions.
Behavior Monitoring: The IDS continuously monitors and analyzes ongoing activities within the system or network. It compares the observed behavior against the established baseline to identify deviations, anomalies, or unusual patterns. Any activity that falls outside the defined parameters is flagged as a potential intrusion or suspicious behavior.
Statistical Analysis: Anomaly-based IDS uses statistical analysis techniques to identify deviations from normal behavior. It may employ methods such as data clustering, time-series analysis, machine learning, or statistical modeling to detect patterns that indicate potential intrusions or abnormal activities.
Alert Generation: When an anomaly or deviation is detected, the IDS generates alerts or notifications to inform security administrators or personnel. The alerts provide details about the detected behavior, including the type of activity, severity level, timestamps, and any other relevant information.
Response and Mitigation: Upon receiving an alert, security teams can investigate the detected anomaly, assess its severity, and take appropriate response actions. This may involve further analysis, network traffic blocking, system isolation, or initiating incident response procedures.

Advantages of Anomaly-based IDS:

Detection of Unknown or Zero-day Attacks: Anomaly-based IDS can detect previously unseen attacks or zero-day exploits that do not have pre-defined signatures. It is not limited to detecting only known attack patterns and can identify abnormal behavior that may indicate new or emerging threats.
Flexibility and Adaptability: Anomaly-based IDS can adapt to changes in the system or network environment. They can learn and update the baseline as the system evolves or as new applications are introduced, ensuring ongoing detection of anomalies.
Reduced False Positives: Anomaly-based IDS typically have a lower false positive rate compared to signature-based IDS. By focusing on deviations from normal behavior, they can minimize false alarms triggered by benign or expected activities.

Limitations of Anomaly-based IDS:

Higher False Negative Rate: Anomaly-based IDS may have a higher false negative rate compared to signature-based IDS. Sophisticated attackers may deliberately mimic normal behavior to evade detection, making it challenging for the IDS to identify their activities as anomalies.

Anomaly-based IDS provides a valuable approach to detecting unknown or novel attacks and abnormal behavior within computer systems and networks. It complements other detection methods, such as signature-based IDS, to enhance overall security effectiveness.

Intrusion Detection System(IDS) and What are the types of IDS