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Ad Hoc network is a newly developed network without fixed infrastructure and a changing topology. Its vulnerability makes it prone to attacks, which brings greater challenges for intrusion detection for Ad Hoc. Through analyzing the existing intrusion detection techniques as well as the characteristics of Ad Hoc network, this paper has proposed an intrusion detection technique based on class association...
Intrusion detection system has been a powerful weapon to protect networks from attacks and has gained more and more attention. Data mining has been proven as an important method to detect intrusions. It has been the recent research focus and trend to apply data mining techniques in intrusion detection system for discovering new types of attacks, but it is still in its infancy. This paper reviews the...
Putting forward a system model based on association rule mining and improving the FP-Growth algorithm based on associative analysis. The experimental result shows that the network intrusion detection developed by this paper can work stably, find out intrusion activities accurately and promptly, improve the speed of data mining effectively, enhance the detective ability of intrusion detection greatly,...
In this article we discuss our research in developing general and systematic methods for intrusion detection. The key ideas are to use data mining techniques to discover consistent and useful patterns of system features that describe program and user behavior, and use the set of relevant system features to compute (inductively learned) classifiers that can recognize anomalies and known intrusions...
In Complex Event Processing (CEP), we deal with how to search through a sequence of incoming events to find a specified and desired pattern. CEP has a broad use in today enterprise. It can act on sent and/or received events. The result can generate other events that can be used in different layers of an enterprise system. Growing number of areas dealing with arisen events like Business Activity Monitoring...
This paper analyzes security problem of campus network, and an intrusion detection structure is proposed in order to detect attacks. Algorithm based on data mining is applied into intrusion detection system in campus network. Also association rules are created in intrusion detection to find association relation in network data stream in the algorithm. And the algorithm resolves the problem of frequent...
Malicious intrusion is the behavior that threats a large number of computers; therefore, recent research has focused on devising new techniques to detect and control internet intrusion with high efficiency and low cost. Unfortunately some anomaly detection system (ADS) over machine learning may get some false alarms if the results of machine learning cannot cover all the normal or abnormal data. In...
A technical scheme, which can properly arrange IDS and optimally apply the algorithms of detection and data mining to the Honeynet environment, is proposed in the building automation system completed by the author recently. In this specific environment, the position of IDS is deployed reasonably and the anomaly and misuse detection algorithm of IDS is designed and selected optimally. Meanwhile, the...
In this paper, intrusion detection approaches for relational database systems were studied. An immune based intrusion detection algorithm for relational databases was proposed. According to the algorithm, the data to be detected were encoded into binary strings after preprocessing. The philosophy of negative selection in biological immune systems was utilized to generate immune detectors. Intrusion...
This paper, first analyzes the method of wireless network intrusion detection, presents a wireless network intrusion detection algorithm based on association rule mining. The application of fuzzy association rules in the wireless network intrusion detection is mainly discussed, and the steps to implement the algorithm are expressed. A comparative analysis with the classical algorithm Apriori is made...
Intrusion detection analyzes unauthorized accesses and malicious behaviors and finds intrusion behaviors and attempts by detecting the state and activity of an operation system to provide an effective means for intrusion defense. Applying the intrusion detection technology to databases is an effective method of enabling databases to have positive and active security mechanisms. This paper makes an...
Fuzzy logic based methods together with the techniques from Artificial Intelligence have gained importance. Association rules together with fuzzy logic to model the fuzzy association rules are being used for classifying data. These together with the techniques of genetic algorithms like genetic programming are producing better results. Therefore, in this article, we firstly analyze the current situation...
Masqueraders commonly impersonate legitimate userpsilas account to gain access to computer systems that they are not authorized to enter. Normally users exhibit some regularity in their behavior such as command usage. We propose a new approach to mine user command associations. Since each user may have different usage behavior, using the built behavior pattern to predict a masqueraderpsilas next command...
Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS), may automatically discover the new pattern from the massive network data, to reduce the workload of the manual compilation intrusion behavior patterns and normal behavior patterns. This article reviewed the current intrusion detection...
Intrusion detection systems (IDSs) are increasingly a key part of systems defense. Various approaches to intrusion detection are currently being used, but they are relatively ineffective. Recently applying artificial intelligence, machine learning and data mining techniques to IDS are increasing. Artificial intelligence plays a driving role in security services. This paper proposes an Immune based...
Network intrusion detection system (IDS), as the main security defending technique, is second guard for a network after firewall. Since it can discern and respond to the hostile behavior of the computer and network resource, it is a hot area for research network security nowadays. Data mining technology is applied to the network intrusion detection, and Precision of the detection will be improved...
A main concern for network intrusion detection systems is the ability of an intruder to evade the detection by routing through a chain of intermediate stepping-stone hosts. The intruders have developed some evasion techniques such as injecting chaff packets or timing jitter. Such evasion techniques cause most of the previous timing-based detection algorithms to fail. In this paper, we address these...
The specification language Z is almost entirely applied to design of large software system. However, nothing is done in applying Z to developing security-critical systems. The intrusion detection technology is one of the most important dynamic security technologies, which can be used in the critical security system construction and the basic service protection. Apparently, applying formal specification...
Applying the basic fuzzy theory and method into intrusion detection has achieved a series success. In this paper, an intrusion detection model base on fuzzy sets is presented to avoid the sharp boundary problem in rules mining. Considering Apriori algorithm is time-consuming as well as space-consuming; moreover, we propose a new rule mining algorithm base prefix tree (PTBA). PTBA algorithm compress...
The network intrusion detection (NIDS) is faced with the question to detect many kinds of intrusion. In order to detect the complex attack, network intrusion detection system need to analysis massive data captured form different network safety equipments. So a new multi relational mining algorithm MRA2 is proposed. MRA2 depend on the association rules mining technology and the probability function...
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