Intrusion detection systems (IDS) were developed in 1990’s, when the network hackers and worms appeared, initially for the identification and reporting of such attacks. The intrusion detection systems didn’t have the ability to stop such attacks rather than detecting and reporting to the network personnel.
The Intrusion Prevention Systems got both characteristics i.e. threat detection and prevention. The detection process analyzes the events for any possible threats while the intrusion prevention stops the detected possible threats and reports the network administrator.
The main purpose of the project is to evaluate the security capabilities of different types of IDPS technologies in maintaining the network security. It provides detail information about the different classes & components of IDPS technologies, for example, detection methods, security capabilities, prevention capabilities & internals of IDPS. It is mainly focused on different detection techniques & responses by these technologies.
The information can be useful for computer network administrators, network security personnel, who have little knowledge about these IDPS technologies.
The project is organized into the following major structure:
The modern computer networks provide fast, reliable and critical information not only to small group of people but also to ever expanding group of users. This need led the development of redundant links, note book computers, wireless networks and many others. On one side, the development of these new technologies increased the importance and value of these access services and on other side they provide more paths to attacks.
During the past, In the presence of firewalls and anti-virus software, organizations suffered huge losses in minutes to their businesses in terms of their confidentiality and availability to the legitimate clients. These modern threats highlighted the need for more advance protection systems. Intrusion detection & prevention systems are designed to protect the systems and networks from any unauthorized access and damage.
An intrusion is an active sequence of related events that deliberately try to cause harm, such as rendering system unusable, accessing unauthorized information or manipulating such information. In computer terminology, Intrusion detection is the process of monitoring the events in a computer network or a host resource and analyzing them for signs of possible incidents, deliberately or incidentally. The primary functions of IDPS are the identification of incident, logging information about them, stopping them & preventing them from causing any damage. The security capabilities of IDPS can be divided into three main categories:
On the basis of location and type of events they monitor, there are two types IDPS technologies, host-based & network based. The network-based IDPS monitors traffic for particular network segment and analyze the network & application protocol activity for suspicious events. It is commonly deployed at the borders between networks. While on the other hand, host-based IDPS monitors the activity of a single host and events occurring within that host for suspicious activity.
There are two complementary approaches in detecting intrusions, knowledge-based approach and behavior based approach. In knowledge-based approach an IDPS looks for specific traffic patterns called Signatures, which indicates the malicious or suspicious content while in the behavior-based approach an intrusion can be detected by observing a deviation from normal or unexpected behavior of the user or the system.
The Intrusion Detection Systems (IDS) can be defined as: tools, methods & resources to identify, assess & report unauthorized or unapproved network activity.
It is the ability to detect attacks against a network or host and sending logs to management console providing the information about malicious attacks on the network and host resources. IDSs fall into two main categories:
The basic process for IDS is that it passively collects data and preprocesses and classifies them. Statistical analysis can be done to determine whether the information falls outside normal activity, and if so, it is then matched against a knowledge base. If a match is found, an alert is sent. Figure 1-1 outlines this activity.
Manager
Fig 1.1 Standard IDS System
IPS technology has all capabilities of an intrusion detection system and can also attempt to stop possible incidents. IPS technologies can be differentiated from the IDS by one characteristic, the prevention capability. Once a threat is detected, it prevents the threat from succeeding. IPS can be a host-based (HIPS), which work best at protecting applications, or a network-based IPS (NIPS) which sits inline, stops and prevents the attack.
A typical IPS performs the following actions upon the detection of an attack:
An IPS typically consists of four main components:
Figure 1.2 outlines this process:
FIG 1-2 Standard IPS
The identification of possible incidents is the main focus of an IDPS, for example, if an intruder has successfully compromised a system by exploiting the vulnerability in the system, the IDPS could report this to the security personnel. Logging of information is another important function of IDPS. This information is vital for security people for further investigation of attack. IDPS has also the ability to identify the violation of security policy of an organization which could be intentionally or unintentionally, for example, an unauthorized access to a host or application.
Identification of reconnaissance activity is one of the major capabilities of IDPS, which is the indication of an imminent attack, for example, scanning of hosts and ports for launching further attacks. In this case, an IDPS can either block the reconnaissance activity or it can alter the configurations of other network devices
The main difference between different types of IDPS technologies is the type of events they can recognize. Following are some main functions;
IDPS not only performs detection but it also performs prevention by stopping the threat to succeed. Following are some prevention capabilities:
IDPS technologies can be divided into following two major categories:
Network-based IDPS monitors network traffic for a particular network segment. They analyze the network and application protocol activity to identify any suspicious activity.
A network based IDPS is usually sits inline on the network and it analyzes network packets looking for attacks. It receives all packets on a particular network segment, including switched networks. It carefully reconstructs the streams of traffic to analyze them for patterns of malicious behavior. They are equipped with facilities to log their activities and report or alarm on questionable events. Main strengths of network-based IDPS are:
A Host-Based system monitors the characteristics of a single host and the events occurring within that host for suspicious activity. It require some software that resides on the system and monitors the network traffic, syslog, processes, file access & modification and configuration or system changes. It logs any activities it discovers to a secure database and check to see whether the events match any malicious event record listed in the knowledge base. Some of the major strengths of Host-Based IDPS are as under:
IDPSs Perform Analysis: This Chapter is about the Analysis Process- What Analysis does and Different Phases of Analysis.
In the context of intrusion detection & prevention, analysis is the organization of the constituent parts of data and their relationships to identify any anomalous activity of interest. Real time analysis is analysis done on the fly as the data travels the path to the network or host. The fundamental goal of intrusion-detection & prevention analysis is to improve an information system’s security.
This goal can be further broken down:
There are many possible analysis schemes but in order to understand them, the intrusion process can be broken down into following four phases:
Preprocessing is the key function once the data is collected from IDPS sensor. The data is organized in some fashion for classification. The preprocessing helps in determining the format the data are put into, which is usually some canonical format or could be a structured database. Once the data are formatted, they are broken down further into classifications.
These classifications can depend on the analysis schemes being used. For example, if rule-based detection is being used, the classification will involve rules and patterns descriptors. If anomaly detection is used, then statistical profile based on different algorithms in which the user behavior is baseline over the time and any behavior that falls outside of that classification is flagged as an anomaly.
Upon completion of the classification process, the data is concatenated and put into a defined version or detection template of some object by replacing variables with values. These detection templates populate the knowledgebase which are stored in the core analysis engine.
Once the processing is completed, the analysis stage begins. The data record is compared to the knowledge base, and the data record will either be logged as an intrusion event or it will be dropped. Then the next data record is analyzed. The next phase is response.
Once information is logged as an intrusion, a response is initiated. The inline sensor can provide real time prevention through an automated response. Response is specific to the nature of the intrusion or the different analysis schemes used. The response can be set to be automatically performed or it can be done manually after someone has manually analyzed the situation.
The final phase is the refinement stage. This is where the fine tuning of the system is done, based on the previous usage and detected intrusions. This gives the opportunity to reduce false-positive levels and to have a more accurate security tool.
The intrusion analysis process is solely depends on the detection method being used. Following is the information regarding the four phases of intrusion analysis by different detection methods:
Rule-based detection, also known as signature detection, pattern matching and misuse detection. Rule-based detection uses pattern matching to detect known attack patterns. The four phases of intrusion analysis process applied in rule-based detection system are as under:
The pattern descriptors are typically either content-based signatures, which examine the payload and header of packet, or context-based signatures that evaluate only the packet headers to identify an alert. The pattern descriptors can be atomic (single) or composite (multiple) descriptors. Atomic descriptor requires only one packet to be inspected to identify an alert, while composite descriptor requires multiple packets to be inspected to identify an alert. The pattern descriptors are then put into a knowledge base that contains the criteria for analysis.
An anomaly is something that is different from the norm or that cannot be easily classified. Anomaly detection, also referred to as Profile-based detection, creates a profile system that flags any events that strays from a normal pattern and passes this information on to output routines. The analysis process by profile-based detection is as following:
This section provides an overview of different technologies. It covers the major components, architecture, detection methodologies & security capabilities of IDPS.
Following are the major components and architecture of IDPS;
Sensor & Agents: Sensors & Agents monitors and analyze the network traffic for malicious traffic.
Sensor:The technologies that use sensors are network based intrusion detection & prevention systems, wireless based intrusion detection & prevention systems and network behavior analysis systems.
Agents: The term “Agent” is used for Host-Based Intrusion detection & prevention technologies.
IDPS components are usually connected with each other through organization’s network or through Management network. If they are connected through management network, each agent or sensor has additional interface known as management Interface that connects it to the management network. IDPS cannot pass any traffic between management interface and its network interface for security reasons. The components of an IDPS i.e. consoles and database servers are attached only with the Management network. The main advantage of this type of architecture is to hide its existence from hackers & intruders and ensure it has enough bandwidth to function under DoS attacks
Another way to conceal the information & communication is to create a separate VLAN for its communication with the management. This type of architecture doesn’t provide a much protection as the management network does.
IDPS provide different security capabilities. Common security capabilities are information gathering, logging, detection and prevention.
Some IDPS gather general characteristics of a network, for example, information of hosts and network. They identify the hosts, operating system and application they use, from observed activity.
When a malicious activity is detected by the IDPS, it performs logging. Logs contain date & time, event type, rating and prevention action if performed. This data is helpful in investigating the incident. Some network-based IDPS captures packet while host-based IDPS records user ID. IDPS technologies allow log to be store locally and send copies of centralized logging server i.e. syslog.
The main responsibility of an IDPS is to detect malicious activity. Most IDPS uses combination of detection techniques. The accuracy and types of events they detect greatly depends on the type of IDPS. IDPS gives great results once they are properly tuned. Tuning gives more accuracy, detection and prevention. Following are some the tuning capabilities:
IDPS offers multiple prevention capabilities. The prevention capability can be configured for each type of alert. Depending on the type of IDPS, some IDPS sensors are more intelligent. They have learning & simulation mode which enables them to know when an action should be performed-reducing the risk of blocking benign activity.
When IDPS detects an intrusion it generates some types of alarms but no IDPS generates 100% true alarm. An IDPS can generate alarm for legitimate activity and can be failed to alarm when an actual attack occurs. These alarms can be categorized as:
2. True Alarms: When an IDPS accurately indicates what is actually happening in the network, it generates true alarms. True alarms fall into two main categories:
Mostly IDPS are operated & maintained by user graphic interface called Console. It allows administrator to configure and update the sensors and servers as well as monitor their status. Console also allows users to monitor and analyze IDPS data and generate reports. Separate accounts could be setup for administrators and users.
Command Line Interface (CLI) is also used by some IDPS products. CLI is used for local administration but it can be used for remote access through encrypted tunnel.
Many consoles offer drill down facilities for example, if an IDPS generates an alert, it gives more detail information in layers. It also give extensive information to the user i.e. packet captures and related alerts.
Reporting is an important function of console. User can configured the console to send reports at set time. Reports can be transferred or emailed to appropriate user or host. Users can obtain and customized reports according to their needs.
There are two types of updates –software updates and signature updates. Software updates for enhancing the performance or functionality and fixing the bugs in IDPS while the signature updates for adding detection capabilities or refining existing capabilities.
Software updates are not limited for any special component but it could include all or one of them i.e. sensor, console, server and agents. Mostly updates are available from the vendor’s web site.
Most IDPS uses multiple detection methodologies for broad & accurate detection of threats but following are primary detection methodologies:
The term Signature refers to the pattern that corresponds to a known threat. In signature based detection, the predefined signatures, stored in a database, are compared with the network traffic for series of bytes or packet sequence known to be malicious, for example, an email with the subject of free screen savers and an attachment of screensavers.exe, which are characteristics of known form of malware Or a telnet
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