舰船网络入侵目标下检测效率与准确性的平衡问题解决

Ships under the network invasion target detection efficiency and accuracy of the balance problem is solved

针对舰船网络入侵目标下入侵关键目标较多,当前方法无法兼顾效率与准确性的问题。从模糊关联规则的观点对入侵目标进行分类。降低检测数据维度,最大程度对不同检测部门分类,使其约简化,放弃推导入侵数据集属性的支持度与置信度,建立频繁项目集等步骤,而是结合舰船网络入侵目标在特征上差异较大这一条件,通过制定模糊关联规则,获得网内入侵数据的相似度,进行多次检测,降低检测过程中的开销成本。实验结果表明,该方法可以兼顾舰船网络入侵目标的检测效率与准确性分体,具备应用性。

For ships invasion of key objectives under the network invasion target is more,the current method cannot both efficiency and accuracy. From the point of view of fuzzy association rules for invading target classification. Reduce the detecting data dimensions,maximum classification of different detection department,make its about to simplify,abandon intrusion dataset derived properties of the support and confidence,establish steps,such as frequent itemsets instead of the target ship network intrusion differences on the characteristics of this condition,by setting the fuzzy association rules,access to the network intrusion data similarity, multiple detection, to reduce the overhead costs in the process of detection. The experimental results show that the method can be to achieve the goal of ship network intrusion detection efficiency and accuracy of the body,have applied.