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IDS (Intrusion Detection system) is an active and driving defense technology. This paper mainly focuses on intrusion detection based on data mining. The aim is to improve the detection rate and decrease the false alarm rate, and the main research method is clustering analysis. The algorithm and model of ID are proposed and corresponding simulation experiments are presented. Firstly, a method to reduce...
In this paper, building a prototype system and the Honeynet secure remote log server, based on the right on the remote log server log data analysis and mining, will Honeynet log mining analytical framework designed to achieve pre-processing of log data, through the IDA to the pre-log data mining, Finally, the results were analyzed to achieve the purpose of effectively preventing network attacks.
In this research, we developed a technique, the Swarm-based Visual Data Mining approach (SVDM), that will help user to gain insight into the Intrusion Detection System (IDS) alert event data stream, come up with new hypothesis, and verify the hypothesis via the interaction between the human and the system. This novel malicious user detection system can efficiently help security officer detect anomaly...
This paper analyzing the lastest research progress and mian problems existed of IDS, researching advantage of data mining technique applied to IDS, and analyzing disadvantage of IDS based on data mining technique, for the problem of time and space inefficient in intrusion detection based on data mining, and aims at the research of frequential pattern algorithm, inproved frequential pattern algorithm,...
Content and its associated information industry are going to become emerging market and content security has attracted more attention of researchers and enterprises. In order to solve these issues, starting with the information definition of Shannon, the paper defines and describes the content security architecture, which proposes a new layering model of information transmission and layering model...
The application and research of XML technology are mature, however, object-oriented XML technology is under development, and now the object-oriented XML research is concentrated on database. In this paper, we will study the application of object-oriented XML and its primary technology Extended DTD. First of all, analyze the internal mechanism of using Extended DTD to realize the object-oriented features...
Intrusion alert analysis system correlates alerts that generated by one or more IDS(s), and yields a succinct attack scenario which reflects an intrusion process. This paper presents an intrusion alert analysis model consists of four modules: alert formalization, alert filtering, alert fusion and correlation, and scenario visualization. Alerts are fused and correlated using approach based on finite...
Network IDS is a well-known security measure for network monitoring and protection. Unfortunately, IDSs are known to generate large amounts of alerts, with many of them being either false positives or of low importance. This makes it hard for the human to spot alerts which need more attention. In order to tackle this issue, this paper proposes an IDS alert classification method which is based on data...
The following topics are dealt with: intelligent system design; neural networks, AI and expert systems; evolutionary computation; genetic algorithms; natural language processing & machine translation; artificial life and artificial immune systems; rough and fuzzy rough set; gray system and cloud computing; cognitive radio and computer vision; pattern recognition and machine learning; fuzzy system...
Intrusion detection systems are deployed on hosts in a computing infrastructure to tackle undesired events in the course of usage of the systems. One of the promising domains of applying intrusion detection is the healthcare domain. A typical healthcare scenario is characterized by high degree of mobility, frequent interruptions and above all demands access to sensitive medical records by concerned...
It is estimated that over 8 million cell phones are lost or stolen each year [7]; often the loss of a cell phone means the loss of personal data, time and enormous aggravation. In this paper we present machine-learning based algorithms by which a cell phone can discern that it may be lost, and take steps to enhance its chances of being successfully recovered. We use data collected from the Reality...
Both Data hiding and data compression are very important technologies in the field of image processing. It seems that there is no relationship between data hiding and data compression because most of the data hiding mechanisms focus on information security and the data compression mechanisms emphasize the compression ratio. In fact, they are closely related. Until now, there are many literatures to...
The following topics are dealt with: Web services; multi-agent system; natural language processing; knowledge discovery; data mining; robotics; evolutionary computation; computer vision; scheduling; planning; ontology; information retrieval; knowledge representation; reasoning; software security; data warehouse; grid computing; and image processing.
The following topics are dealt with: genetic algorithm; information security; video and image processing; intelligent control; system theory and control theory; data mining; knowledge discovery; intelligent computing; intelligent systems; database engineering; software theory; and wireless and mobile computing.
Unknown protocol inference are useful for many security application, including intrusion detection which always depends on deep packet inspection. However, mining distinguishers with unknown protocol format generally turns to protocol reverse engineering. In this paper, we propose a novel method for automatically abstracting protocol distinguishers based on statistic and our method is proved to be...
The following topics are dealt with: clusters and grids computing; wireless sensor network; Web service; communication networks; distributed systems; P2P networks; computational intelligence; service-oriented architecture; data mining; data security; numerical algorithm; image processing; economic computing; networked robot systems; and clouds computing.
A new data stream outlier detection algorithm SODRNN is proposed based on reverse nearest neighbors. this paper researches data stream outlier detection algorithm which is based on Reverse k nearest neighbours. When we analyze the known algorithms, we find that the algorithm cannot deal with the concept drifting problem and they need multi-scan of the dataset. So, this paper introduces the SODRNN...
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