IPv6 will inevitably take the place of IPv4 as the
next generation of the Internet Protocol. Despite IPv6 has better security than
IPv4, but there still have some security issues. So it is an urgent problem to
requirement of IDS for IPv6 networks.
Many intelligent information processing methods,
data mining technology and so on have been applied to improve detection accuracy
for IPv4 network. At first IPv6 security issues has been analysis in this
project, secondly discussed the IPv6 intrusion detection model, then we in
accordance with such a model present an intrusion detection model realization
for IPv6 network, and we propose a strategy for the system achieve and optimization.
The system can work well for intrusion detection for IPv6 network.
Network Intrusion Detection:
Modern computer
networks must be equipped with appropriate security mechanisms in order to
protect the information resources maintained by them. Intrusion detection
systems (IDSs) are integral parts of any well configured and managed computer
network systems. An IDS is a combination of software and hardware components,
capable of monitoring different activities in a network and analyze them for
signs of security threats. There are two major approaches to intrusion
detection: anomaly detection and misuse detection. Misuse detection uses
patterns of well known intrusions to match and identify unlabeled data sets. In
fact, many commercial and open source intrusion detection systems are misuse
based. Anomaly detection, on the other hand, consists of building models from
normal data which can be used to detect variations in the observed data from
the normal model. The advantage with anomaly detection algorithms is that they
can detect new forms of attacks which might deviate from the normal behaviour .
In this project, various supervised learning algorithms, particularly decision trees based on
ID3, J48, and Naïve Bayes algorithms are explored for network intrusion.Intrusion
detection is the art of detecting the break-ins of malicious attackers. Today,
computer security has grown in importance with the widespread use of the
Internet. Firewalls are commonly used to prevent attacks from occurring.
Antivirus and anti-spyware programs can help people to remove already existing
automated attacks from their computer. Access control limits physical and
networked use of a computer. However, an important component of setting up a
secure system is to have some way to analyze the activity on the computer and
determine whether an attack has been launched against the computer. Such a
system is called an intrusion detection system. This project uses Naive Bayes, a Decision
Tree algorithms to determine the relative strengths and weaknesses of using
these approaches. The purpose is to give an evaluation of the performance of
these algorithms that will allow someone who wishes to use one of these
approaches to understand how accurate the approach is and under what conditions
it works well. In addition, a novel evaluation technique will be considered.
Accuracy can be evaluated effectively by using Receiver Operating
Characteristic (ROC) curves. Cost curves
can indicate the conditions under which the algorithm works well.
A requirement is a feature that the system
must have or a constraint that it must satisfy to be accepted by client. Requirements
engineering aims at defining the requirements for the system under
construction. It includes two main activities: Requirements Elicitation and
Analysis.
Requirements elicitation is
about communication among developers, clients, and users for defining a new
system. It focuses on describing the purpose of the system. Such a definition
is called system specification.
Requirement elicitation is the more challenging of the two because it requires
the collaboration of several groups of participants with different backgrounds.
On the one hand, the client and the users are experts in their domain and have
a general idea of what the system should do, but they often have little
experience in software development. On the other hand, the developers have
experience in building systems, but often have little knowledge of everyday environment of
the users