Using Signal Processing Techniques to Model Worm Propagation over Wireless Sensor Networks

Another neat paper that looks at worm propagation in a non-traditional network medium. The constraints found in such networks is offset by the opportunities they provide for long distance travel. This is increasingly important with PDA-based malware.

In this article, we define worm propagation characteristics that are specific to sensor networks. We parameterize the effects of physical channel conditions, medium access control (MAC) layer contention, network layer routing, and transport layer protocol on worm propagation in sensor networks. These parameters are incorporated in the TWPM, which borrows its basic formulation from models of epidemic diseases. The advanced model parameters and the mathematical treatment following the formulation are then developed specifically for sensor networks. The basic model formulation results in a partial differential equation, which is solved in the frequency domain to yield a closed-form solution for the TWPM. It is shown that in the spatial domain the TWPM spread function is low-pass filtered by a two-dimensional (2-D) isotropic Gaussian filter, thereby providing an intuitive feel for the dependence of the model on its underlying (physical, MAC, and network layer) parameters. For performance evaluation, we simulate the spread of a worm over a sensor network. The simulated and TWPM-predicted worm propagation dynamics are then compared to evaluate the accuracy of the model. We show that the TWPM predicts the worm propagation dynamics very accurately.

Source: "Using Signal Processing Techniques to Model Worm Propagation over Wireless Sensor Networks," Syed A. Khayam and Hayder Radha, IEEE Signal Processing Magazine, vol. 23, no. 2, pp. 164-169, March 2006.