SII Model for Self-Start Detection on the Propagation Dynamics of Modern Email Malware

In recent years, email is the basic service for person to person communication, and email facilitates by its high speed, and process ability. The email malware exhibits two new propagation features, reinfection and self-start. Reinfection is the process by which an infected user sends out malware copies, whenever the infected user opens the malicious hyperlink or attachment. Self-Start is the process by which the infected user spreads the malware copies, whenever certain events are triggered. To solve this problem, derive a new analytical model by introducing a concept of virtual nodes. The malware detector serves as an empirical means of evaluating malware detection techniques detection capabilities. The new analytical model can efficiently predict the reinfection detection and effectively overcome the associated computational challenges.