Research of Dynamic Forensics Analysis Technology Based on Genetic-Fuzzy Clustering Algorithm

The key to the implementation of dynamic forensics is how to mine in real-time and effectively criminal invasion information from voluminous data. Towards the disadvantages of Fuzzy C-means clustering (referred to as FCM) forensics analysis that it is very sensitive to initial data and impacted greatly by noise, a dynamic forensics analysis technology based on genetic-fuzzy clustering algorithm is proposed. The genetic-fuzzy clustering algorithm not only plays fully global optimization ability of genetic algorithm and local optimization capacity of FCM algorithm but also balances effectively algorithm to clustering space exploration. The experimental results by using KDD CUP99 Data, show that this method could better improve the efficiency and lower the false rate, at the same time, further improve the comprehensive performance of dynamic forensics analysis system.