Options For Implementing Intrusion Detection Systems Essay

KDDCup99 dataset was introduced at the Third International Knowledge Discovery and Data Mining Tools Competition which was held by DARPA in 1999 .KDDCup99 is a refined data set from DARPA 1998 dataset as it contains only network data[3]. KDDCup99 is commonly used developers and implementers of new IDS to evaluate their systems. IDS systems take the KDDCup99 dataset as an input to train ,test the system and check performance of the IDS in classifying and detecting attack records. KDDCup99 dataset is used by most researchers because it contains 22 different attack types which could be classified into four main attack categories of the network discussed in the previous section. The full DARPA dataset consists of relatively 4,900,000 lines of connection vectors where each single connection vectors consists of 41 features and is marked as either normal or an attack, with exactly one particular attack type [38]. Among the 41 features of the connection, only sixteen significant attributes are considered which are: A1,A5,A6,A8, A9, A10, A11, A13, A16, A17, A18, A19, A23, A24, A32, A33[38] The KDD 99

Network Intrusion Detection: Software exists to watch traffic on your network to search for malicious intent. Is an Intrusion Detection System going to be implemented? An IDS is not a fire and forget type system. It requires constant monitoring. Smaller organizations will be overwhelmed by the amount of information it produces.

Intrusion detection and prevention systems monitor traffic/ logs either on the individual host or on the network in real time looking for signatures of common attacks or anomalies that will trigger an alarm either of an attack in motion or an attack that has already occurred.

The Intrusion Detection System (IDS) is a protection scheme which collect and analyze audit data for the entire network.

Interruption identification frameworks (IDS) take either system or host based methodology for perceiving and redirecting assaults. In either case, these items search for assault marks (particular examples) that for the most part demonstrate malignant or suspicious goal. At the point when an IDS searches for these examples in system activity then it is system based (figure 1). At the point when an IDS searches for assault marks in log records, then it is host based.

Perception for interruption location helps a security head to perceive irregular conduct in an intuitional way. Representation of interruption location empowers quick examination and reaction in light of the fact that an interruption is perceived intuitionally. In this way, it can overcome alarm flooding. Most interruption discovery strategies with perception are peculiarity based identification systems and envision review information as opposed to the ready itself. [5].The host-based perception strategy for interruption discovery is to learn ordinary conditions of recognizes or projects that is accomplished by the client and contrasts review information and profiles for representation.

A host-based Intrusion detection system monitors activities associated with a particular host [6] and aimed at collecting information about activity on a host system or within an individual computer system. In host based Intrusion detection system separate sensors would be needed for an individual computer system. Sensor monitors the event takes place on the system. Sensors collect the data from system logs, logs generated by operating system processes, application activity, file access and modification. These log file can be simple text file or operation on a system.

1)After the brief overview of our research in building predictive models for learning from rare classes, the paper gives a comparative study of several anomaly detection schemes for identifying novel network intrusions.

Internet has grown leap and bounds over the last few years. This has resulted in a number of computer security breaches on the Internet. Most of the computers that use Internet are vulnerable to attack. Due to this reason, Intrusion Detection systems have grown rapidly and there is an ongoing research since it’s a developing field. ID (Intrusion Detection) is a type of a security management system that gathers and analyzes information to identify security breaches, which include both, attacks from outside the organization and attacks from inside as well (misuse). ID includes analysis of abnormal activity, tracking user policy violations, assessing systems and file integrity and vulnerability. It helps us differentiate the normal behavior of system and helps us obtain any abnormal activity that is taking place. This can be done easily using data mining and it helps increase its sustainability to attacks.

Moreover, IPS systems are a great technology that reduces the threats of cyber-attacks. IPS is responsible for detecting intruders breaking into the network systems, or detecting misuse of network resources by authorized users. In addition, when a threat is detected, IPS performs an action in respond to the threat. In such incidents, IPS performs various actions to include sending an alarm to the administrator, stop the traffic coming from the source address, and/or resetting the connection.6

Intrusion Detection Systems (IDS) are software or hardware designed to automatically monitor activities within a network of computers and identify any security issues . IDS have been around for at least 30 years since increased enterprise network access produced a new challenge, the need for user access and monitoring. As day-to-day operations grew increasingly dependent upon shared use of information systems, levels of access to these systems and clear visibility into user activity was required to operate safely and securely.

In general, IDSs are using two fundamental approaches. The first one is misuse detection, also called signature-based detection. In this type of IDSs, the search for evidence of attacks is based on knowledge accumulated from known attacks. This knowledge is represented by attacks' signatures which are patterns or sets of rules that can uniquely identify an attack. Being designed based on the knowledge of the past intrusions or known vulnerabilities, misuse-based IDSs are also called knowledge-base detection. The advantages of knowledge-based approaches are that they have a very good accuracy and

However, both IDS approaches do some form of protocol parsing to give to the analysts the ability to finely control what they want to search for when examining a given protocol. Bro IDS includes a facility to perform signature-based detection and a tool called snort2bro that converts Snort signatures to Bro IDS signatures. Same, Snort IDS signatures can be written to search for anomalous traffic on a given network. However, this capability is limited by which “stream” based interpreter the signature system can understand when finding anomalous traffic.

In 1980, James Anderson’s paper, Computer Security Threat Monitoring and Surveillance, bore the notion of intrusion detection. Through government funding and serious corporate interest allowed for intrusion detection systems(IDS) to develope into their current state. So what exactly is IDS? An IDS is used to detect malicious network traffic and computer usage through attack signatures. The IDS watches for attacks not only from incoming internet traffic but also for attacks that originate in the system. When a potential attack is detected the IDS logs the information and sends an alert to the console. How the alert is detected and handled at is dependent on the type of IDS in place. Through this paper we

Intrusion Prevention System (IPS) is a proactive protection technology that provides security at the network level. It’s the first line of defense against malware. An organization can not protect their network with just a firewall. Additional protection is needed to avoid potential risks and attacks. An Intrusion Prevention System adds the extra layer of protection by examining all network traffic that is allowed through the firewall. Previously Intrusion Prevention Systems simply protected operating system threats or denial of service and distributed denial of service attacks. These threats exploited vulnerabilities that were mostly in the operating system stack and services. Over the years these operating system components have