Mitchell, J., O'Neill, E., Zyba, G., Voelker, G. M., Liljenstam, M., Mehes, A. and Johansson, P., 2012. Limitations of scanned human copresence encounters for modelling proximity-borne malware. IEEE.
Patterns of human encounters, which are difficult to observe directly, are fundamental to the propagation of mobile malware aimed at infecting devices in spatial proximity. We investigate errors introduced by using scanners that detect the presence of devices on the assumption that device copresence at a scanner corresponds to a device encounter. We show in an ideal static model that only 59% of inferred encounters correspond to actual device copresence. To investigate the effects of mobility, we use a simulator to compare encounters between devices with those inferred by scanners. We show that the statistical properties of scanned encounters differ from actual device encounters in ways which impact malware propagation dynamics, a form of aggressive data dissemination. In addition to helping us understand the limitations of encounter data gathered by scanners in the field, our use of virtual scanners suggests a practical method for using these empirical datasets to better inform simulations of proximity malware outbreaks and similar data dissemination applications.
|Item Type ||Conference or Workshop Items (UNSPECIFIED)|
|Creators||Mitchell, J., O'Neill, E., Zyba, G., Voelker, G. M., Liljenstam, M., Mehes, A. and Johansson, P.|
|Departments||Faculty of Science > Computer Science|
|Publisher Statement||O'Neill_COMSNETS_2012.pdf: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
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