EpiNet: a simulation framework to study the spread of malware in wireless networks

We describe a modeling framework to study the spread of malware over realistic wireless networks. We develop (i) methods for generating synthetic, yet realistic wireless networks using activity-based models of urban population mobility, and (ii) an interaction-based simulation framework to study the dynamics of worm propagation over wireless networks. We use the prototype framework to study how Bluetooth worms spread over realistic wireless networks. This required developing an abstract model of the Bluetooth worm and its within-host behavior. As an illustration of the applicability of our framework, and the utility of activity-based models, we compare the dynamics of Bluetooth worm epidemics over realistic wireless networks and networks generated using random waypoint mobility models. We show that realistic wireless networks exhibit very different structural properties. Importantly, these differences have significant qualitative effect on spatial as well as temporal dynamics of worm propagation. Our results also demonstrate the importance of early detection to control the epidemic.

[1]  Christian Bettstetter,et al.  Smooth is better than sharp: a random mobility model for simulation of wireless networks , 2001, MSWIM '01.

[2]  Guanhua Yan,et al.  Bluetooth worm propagation: mobility pattern matters! , 2007, ASIACCS '07.

[3]  Steve R. White,et al.  Computers and epidemiology , 1993, IEEE Spectrum.

[4]  Moshe Ben-Akiva,et al.  PII: S0965-8564(99)00043-9 , 2000 .

[5]  Jeffrey O. Kephart,et al.  Directed-graph epidemiological models of computer viruses , 1991, Proceedings. 1991 IEEE Computer Society Symposium on Research in Security and Privacy.

[6]  Stefan Saroiu,et al.  A preliminary investigation of worm infections in a bluetooth environment , 2006, WORM '06.

[7]  Guanhua Yan,et al.  Modeling Propagation Dynamics of Bluetooth Worms , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).

[8]  Donald F. Towsley,et al.  Code red worm propagation modeling and analysis , 2002, CCS '02.

[9]  M. D. McKay,et al.  Creating synthetic baseline populations , 1996 .

[10]  Brian D. Noble,et al.  Modeling epidemic spreading in mobile environments , 2005, WiSe '05.

[11]  Aravind Srinivasan,et al.  Modelling disease outbreaks in realistic urban social networks , 2004, Nature.

[12]  Geoffrey M. Voelker,et al.  Can you infect me now?: malware propagation in mobile phone networks , 2007, WORM '07.

[13]  Guanhua Yan,et al.  Bluetooth Worms: Models, Dynamics, and Defense Implications , 2006, 2006 22nd Annual Computer Security Applications Conference (ACSAC'06).

[14]  Madhav V. Marathe,et al.  EpiSimdemics: An efficient algorithm for simulating the spread of infectious disease over large realistic social networks , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[15]  Aravind Srinivasan,et al.  Structural and algorithmic aspects of massive social networks , 2004, SODA '04.