Dynamics of malware spread in decentralized peer-to-peer network

Malware is the software developed with malicious intentions. The detection of such malware can be done by writing program which can understand the dynamics of malware. This paper presents an analytical model which can effectively characterize the true nature of malware and how it spreads in peer-to-peer networks such as Gnutella. The proposed model is compartmental model which involves derivation of network conditions and system parameters in such a way that under those parameters and conditions the underlying P2P network reaches a malware free equilibrium. The proposed model can also perform evaluation of strategies such as quarantine used to control malware spread. Afterwards the model has been enhanced and tested with networks of smart cell phones.