Epidemic Models of Malicious-Code Propagation and Control in Wireless Sensor Networks: An Indepth Review

Besides anti-malware usage for the eradication of malicious attacks, researchers have developed epidemic models in order to gain more insights into the spread patterns of malware. For wireless sensor networks (WSN), these epidemic models, which are equation-based, have been seen to characterize both salient features of the network as well as the dynamics of malware distribution. In this study, an in-depth review aimed at generating the strengths and weaknesses of Susceptible-Infected (SI)-based compartmental models of malware spread in WSN was performed. Emphasis is placed on models resulting from the biological SI model developed by Kermack and Mckendrick, and its subsequent adaptation for malware spread in communication networks. Specifically, lessons and open areas were presented in accordance with the following factors: communication graph/topology, multigroup modeling, horizontal/vertical transmission (VT), communication range and density, patching, protocols, sensor mobility, energy consumption, optimal control/cost, stability, delay analysis, and numerical simulation. Amongst several findings, it was discovered that epidemic WSN models are yet to sufficiently represent medium access control, VT, alongside limited battery power, memory, authentication (using key schemes), survivability and availability etc. Additionally, only a few epidemic models have been developed to represent botnet propagation, concurrent multiple malware infection types, and sensor mobility in WSN.