物联网环境下的差异网络数据库异常数据检测

当前的物联网环境下,各个智能网络的数据库的使用没有统一标准,不同生产商的数据库中的异常数据标准也不同,这就使得传统的以模式识别为基础的网络数据库异常检测方法在进行异常阀值设置时,无法形成统一标准,数据库数据量庞大且存在无序性,无法保证检测的准确性和检测效率。提出基于混沌特征分析算法的物联网环境下的差异网络数据库异常数据检测方法。依据混沌特征分析相关理论构建物联网环境下的差异网络数据库模型,构建一种异常数据的偏差函数,对不同数据库下的异常数据进行偏差统计,通过对偏差函数的统计结果进行最小值求解,根据求解描述最小化的阀值请求,实现物联网环境下的差异网络数据库异常数据的检测。实验结果表明,利用改进算法进行异常数据检测,能够提高检测的有效性与准确性。

Under the environment of Internet of things the difference of network database abnormal data detection

The current Internet environment, the use of the intelligent network database is not unified standard, different manufacturers have different standard of abnormal data in the database, which makes the traditional pattern recognition based database of network anomaly detection method for anomaly threshold Settings, unable to form a unified standard, database data quantity is huge and exists disorder, can"t guarantee the detection accuracy and efficiency. Based on chaotic characteristic analysis algorithm is put forward under the environment of Internet of things of the difference of network database abnormal data detection method. Based on chaotic characteristic analysis of related theory to build the Internet of things environment difference of network database model, build a kind of abnormal data deviation function, abnormal data under different database for deviation statistics, based on the minimum value of the statistical results of solving the deviation function, minimize according to describe the threshold of the request, to realize the Internet of things environment difference detection of abnormal data of network database. Experimental results show that the improved algorithm is abnormal data detection, can improve the effectiveness and accuracy of detection.