Network intrusion forensics is an important extension to present security infrastructure, and is becoming the focus of forensics research field. However, comparison with sophisticated multi-stage attacks and volume of sensor data, current practices in network forensic analysis are to manually examine, an error prone, labor-intensive and time consuming process. To solve these problems, in this paper we propose a digital evidence fusion method for network forensics with Dempster-Shafer theory that can detect efficiently computer crime in networked environments, and fuse digital evidence from different sources such as hosts and sub-networks automatically. In the end, we evaluate the method on well-known KDD Cup 1999 dataset. The results prove our method is very effective for real-time network forensics, and can provide comprehensible messages for a forensic investigators.
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Tian et al. (2014) studied this question.
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