An intelligent embedded system for malicious email filtering

Disaster from computer viruses has been ranked at the top of computer crime incidents by CSI/FBI. However, many anti-virus systems have high latency and consume a lot in the available CPU resources for malicious code filtering. Nevertheless, switching or updating anti-virus software within different operating systems is costly, tedious, and annoying. Therefore, we have proposed a standalone intelligent Embedded Email Virus Filter system to overcome these drawbacks. The associative Petri net model that integrates malicious behavior reasoning is adopted to detect the malicious executable. The experimental results show that our proposed system has great potential in email virus filtering.