3,883 research outputs found
AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments
This report considers the application of Articial Intelligence (AI) techniques to
the problem of misuse detection and misuse localisation within telecommunications
environments. A broad survey of techniques is provided, that covers inter alia
rule based systems, model-based systems, case based reasoning, pattern matching,
clustering and feature extraction, articial neural networks, genetic algorithms, arti
cial immune systems, agent based systems, data mining and a variety of hybrid
approaches. The report then considers the central issue of event correlation, that
is at the heart of many misuse detection and localisation systems. The notion of
being able to infer misuse by the correlation of individual temporally distributed
events within a multiple data stream environment is explored, and a range of techniques,
covering model based approaches, `programmed' AI and machine learning
paradigms. It is found that, in general, correlation is best achieved via rule based approaches,
but that these suffer from a number of drawbacks, such as the difculty of
developing and maintaining an appropriate knowledge base, and the lack of ability
to generalise from known misuses to new unseen misuses. Two distinct approaches
are evident. One attempts to encode knowledge of known misuses, typically within
rules, and use this to screen events. This approach cannot generally detect misuses
for which it has not been programmed, i.e. it is prone to issuing false negatives.
The other attempts to `learn' the features of event patterns that constitute normal
behaviour, and, by observing patterns that do not match expected behaviour, detect
when a misuse has occurred. This approach is prone to issuing false positives,
i.e. inferring misuse from innocent patterns of behaviour that the system was not
trained to recognise. Contemporary approaches are seen to favour hybridisation,
often combining detection or localisation mechanisms for both abnormal and normal
behaviour, the former to capture known cases of misuse, the latter to capture
unknown cases. In some systems, these mechanisms even work together to update
each other to increase detection rates and lower false positive rates. It is concluded
that hybridisation offers the most promising future direction, but that a rule or state
based component is likely to remain, being the most natural approach to the correlation
of complex events. The challenge, then, is to mitigate the weaknesses of
canonical programmed systems such that learning, generalisation and adaptation
are more readily facilitated
Detection of denial of service attacks using database queries
In the current intrusion detection world, most intrusion detection systems output data into flat files. This project was conducted in order to improve intrusion detection data and alerts by writing them into a database system and analyzing them with SQL. A database plug-in was developed that helps to transition the data from an intrusion detection system to a database. Storing, analyzing, categorizing, and accessing data are major advantages and reasons for using databases in intrusion detection. Security analysts have to constantly perform the difficult task of sorting through a haystack of attack alerts, many of which turn out to be inaccurate. It is possible to make the job of managing these alerts, analyzing data with high precision, and searching for attacks or intrusions easier by using SQL based analysis. In addition, a statistical analysis was conducted and proved that such a method can be effective in detecting intrusions and increasing the security of the network
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A survey of intrusion detection techniques in Cloud
Cloud computing provides scalable, virtualized on-demand services to the end users with greater flexibility and lesser infrastructural investment. These services are provided over the Internet using known networking protocols, standards and formats under the supervision of different managements. Existing bugs and vulnerabilities in underlying technologies and legacy protocols tend to open doors for intrusion. This paper, surveys different intrusions affecting availability, confidentiality and integrity of Cloud resources and services. It examines proposals incorporating Intrusion Detection Systems (IDS) in Cloud and discusses various types and techniques of IDS and Intrusion Prevention Systems (IPS), and recommends IDS/IPS positioning in Cloud architecture to achieve desired security in the next generation networks
Threshold Verification Technique for Network Intrusion Detection System
Internet has played a vital role in this modern world, the possibilities and
opportunities offered are limitless. Despite all the hype, Internet services
are liable to intrusion attack that could tamper the confidentiality and
integrity of important information. An attack started with gathering the
information of the attack target, this gathering of information activity can be
done as either fast or slow attack. The defensive measure network administrator
can take to overcome this liability is by introducing Intrusion Detection
Systems (IDSs) in their network. IDS have the capabilities to analyze the
network traffic and recognize incoming and on-going intrusion. Unfortunately
the combination of both modules in real time network traffic slowed down the
detection process. In real time network, early detection of fast attack can
prevent any further attack and reduce the unauthorized access on the targeted
machine. The suitable set of feature selection and the correct threshold value,
add an extra advantage for IDS to detect anomalies in the network. Therefore
this paper discusses a new technique for selecting static threshold value from
a minimum standard features in detecting fast attack from the victim
perspective. In order to increase the confidence of the threshold value the
result is verified using Statistical Process Control (SPC). The implementation
of this approach shows that the threshold selected is suitable for identifying
the fast attack in real time.Comment: 8 Pages, International Journal of Computer Science and Information
Securit
Analyze Different approaches for IDS using KDD 99 Data Set
the integrity, confidentiality, and availability of Network security is one of the challenging issue and so as Intrusion Detection system (IDS). IDS are an essential component of the network to be secured. Intrusion detection is the process of monitoring and analyzing the events occurring in a computer system in order to detect signs of security problems. Intrusion detection includes identifying a set of malicious actions that compromise information resources. Traditional methods for in trusion detection are based on extensive knowledge of signatures of known attacks . In the last three years, the networking revolution has finally come of age. More than ever before, we see that the Internet is changing computing, as we know it. The possibilities and opportunities are limitless; unfortunately, so too are the risks and chances of malicious intrusions There are two primary methods of monitoring these are signature - based and anomaly based. In this paper is to analyze different approaches of IDS . Some approach belongs to supervised method and some approach belongs to unsupervised method
Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems
Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious
attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection
based on sequences of system calls. The point is to construct a model that
describes normal or acceptable system activity using the classification trees
approach. The created database is utilized as a basis for distinguishing the
intrusive activity from the legal one using string metric algorithms. The
major results of the implemented simulation experiments are presented and
discussed as well
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