RC4 is a stream cipher algorithm operating on each byte of data; like the RC2, it supports key lengths of 40 bits, 64 bits, and 128 bits.
RC 4是一个流密码算法，它对数据的每个字节进行操作；和RC 2一样，它支持长度为40位、64位和128位的密钥。
A large amount of memories are consumed during dense data querying. A query processing algorithm based on XML stream is designed.
针对密集型数据查询要消耗大量内存的缺陷，设计了一种基于流的XM L文档查询算法。
This paper introduced a density grid-based data stream clustering algorithm.
提出了一种基于密度网格的数据流聚类算法。
Experimental results show that the algorithm is very effective to solve data stream clustering.
实验表明，该算法对于解决数据流聚类问题非常有效。
Data stream is characterized by infinite data and quick stream speed, so traditional clustering algorithm cannot be applied to data stream clustering directly.
数据流具有数据量无限且流速快等特点，使得传统的聚类算法不能直接应用于数据流聚类问题。
Aiming at synopsis computation of approximate query in data stream, a novel wavelet transformation algorithm, Minimum Error based Dimension Compression (MEDC) algorithm, is proposed in this paper.
针对数据流上近似查询中的梗概计算，提出了一种新的基于最小误差的维压缩小波变换算法(MEDC)。
First, the piecewise fractal model on data stream is introduced, and then based on this model the algorithm for detecting bursts is presented.
首先给出了数据流上的分段分形模型，进而基于该模型设计了突变检测算法。
In order to reduce the data transmission traffic, filtering the data stream that will be transmitted can be adopted besides taking DR algorithm and improving communication method.
为了减少传输的数据量，除了采用DR算法和改进通信方式外，还可以对将要发送的数据流进行过滤。
In addition, the data stream parsing, extraction protocol characteristics, the establishment of ATM, IP protocol type algorithm model for rapid identification.
另外，对数据流进行解析，提取协议特征，建立A TM、IP协议类型快速识别算法模型。
Meanwhile, the research of the stream data clustering algorithm would be useful references to the similar researches.
同时，本文对流数据聚类算法的研究，对于促进同类问题的研究具有一定的理论价值和借鉴意义。
The traditional algorithm of mining outliers cannot mine outliers in data stream effectively.
传统的离群点挖掘算法无法有效挖掘数据流中的离群点。
A frequent items mining algorithm of stream data (SW-COUNT) was proposed, which used data sampling technique to mine frequent items of data flow under sliding Windows.
提出了一种流数据上的频繁项挖掘算法(SW - COUNT)。该算法通过数据采样技术挖掘滑动窗口下的数据流频繁项。
This paper describes the relevant concepts and presents a model of CBR based on dynamic data stream mining, and gives an improved clustering algorithm of data stream.
首先阐述了相关概念，接着提出了一种基于动态数据流挖掘的案例推理模型，其中动态数据流挖掘算法采用改进的数据流聚类算法。
In order to improve the efficiency of filtering algorithms for time series data stream, this paper proposes a new more efficient streaming time series query filtering algorithm for DTW.
目的设计基于DTW的高效过滤算法，提高时间序列数据流的过滤查询的效率。
Concerning the infinite input and dynamic change in data stream environment, a new algorithm for detecting data stream outliers based on distance was proposed.
针对数据流的无限输入和动态变化等特点，提出一种新的基于距离的数据流离群点挖掘算法。
Secondly, the algorithm of multi-stream integrated and the data structure of the integrated file are described in detail.
然后详细介绍了多流合一的实现原理、合一后文件的数据结构；
Experimental results show the algorithm can capture the evolving behaviors of the data stream in real time with enough accuracy.
实验结果表明，该方法在保持足够计算精度的同时能够精确捕获数据流的实时演化行为。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
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