This research work proposes a model of network security systems aiming to prevent production system in a data center from being attacked by intrusions. Conceptually, we introduce a decoy system as a part of the security system for luring intrusions, and apply network intrusion detection (NIDS), coupled with the decoy system to perform intrusion prevention. When NIDS detects an activity of intru...

ISBN 555555555/$10.00  2002 IEEE Abstract – The normal and the abnormal behaviors in networked computers are hard to predict, as the boundaries cannot be well defined. This prediction process usually generates false alarms in many anomaly based intrusion detection systems. However, with fuzzy logic, the false alarm rate in determining intrusive activities can be reduced, where a set of fuzzy r...

A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial-Immune-System-based approaches attempt to leverage the adaptability, error tolerance, selfmonitoring and distributed nature of Human Immune Systems. The Soft-Computing-based approaches are instrumental in developing fuzzy-rule-based systems for detecting intrusions. T...

Intrusion detection technology is an effective approach to dealing with the problems of network security. In this paper, it presents an intrusion detection model based on hybrid neural network and SVM. The key idea is to aim at taking advantage of classification abilities of neural network for unknown attacks and the expertbased system for the known attacks. We employ data from the third intern...

A multivariate statistical method called Principal Component Analysis is used to detect Denial-of-Service and Network Probe attacks using the 1998 DARPA data set. Visualization of network activity and possible intrusions is achieved using Bi-plots, which are used as a graphical means for summarizing the statistics. The principal components are calculated for both attack and normal traffic, and ...

Magmatic intrusions and volcanic eruptions are intimately related phenomena. Shallow magma intrusion builds subsurface reservoirs that are drained by volcanic eruptions. Thus, the long-held view is that intrusions must precede and feed eruptions. Here we show that explosive eruptions can also cause magma intrusion. We provide an account of a rapidly emplaced laccolith during the 2011 rhyolite e...

A model for correct recall and intrusions in cued recall of word lists is introduced. Intrusions are false responses that were correct in an earlier list. The model assumes 3 exclusive states for memory traces after encoding: with a list tag (i.e., with information about list origin), without list tags, and missing. Across lists, a trace can lose its list tag or its content. For retrieval, an o...

The Mobile Agent Intrusion Detection System (MAIDS) is an agent based distributed Intrusion Detection System (IDS). A disciplined requirement engineering process is developed to build MAIDS. The starting point is a high level description of intrusions expressed as Software Fault Trees (SFTs). Then the SFTs are translated to Colored Petri Nets (CPNs) that specify the IDS design. Subsequently, th...

As the Internet spreads to each corner of the world, computers are exposed to miscellaneous intrusions from the World Wide Web. We need effective intrusion detection systems to protect our computers from these unauthorized or malicious actions. Traditional instance-based learning methods for Intrusion Detection can only detect known intrusions since these methods classify instances based on wha...

A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial Immune System based approaches attempt to leverage the adaptability, error tolerance, selfmonitoring and distributed nature of Human Immune Systems. Whereas Soft Computing based approaches are instrumental in developing fuzzy rule based systems for detecting intrusion...