The application of epidemiology to computer viruses
Computers and Security
Code red worm propagation modeling and analysis
Proceedings of the 9th ACM conference on Computer and communications security
How to Own the Internet in Your Spare Time
Proceedings of the 11th USENIX Security Symposium
IEEE Security and Privacy
A preliminary investigation of worm infections in a bluetooth environment
Proceedings of the 4th ACM workshop on Recurring malcode
Bluetooth worm propagation: mobility pattern matters!
ASIACCS '07 Proceedings of the 2nd ACM symposium on Information, computer and communications security
Studying Bluetooth Malware Propagation: The BlueBag Project
IEEE Security and Privacy
Realistic mobility simulation of urban mesh networks
Ad Hoc Networks
Modeling Propagation Dynamics of Bluetooth Worms (Extended Version)
IEEE Transactions on Mobile Computing
EpiNet: a simulation framework to study the spread of malware in wireless networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Propagation, detection and containment of mobile malware
Propagation, detection and containment of mobile malware
Mobile location tracking in metro areas: malnets and others
Proceedings of the 17th ACM conference on Computer and communications security
Hi-index | 0.00 |
The enhanced capabilities of smartphones are creating the opportunity for new forms of malware to spread directly between mobile devices over short-range radio. This has been observed already in Bluetooth radios, and WiFi capabilities of smartphones provide an opportune new spreading vector. The increasing complexity of phone operating systems coupled with disclosed vulnerabilities suggest it is simply a matter of time before WiFi based worms are possible. Works that have considered this problem for Bluetooth suggest outbreaks would result in epidemics [11,28,32]. We use traditional epidemiological modeling tools and high-fidelity realistic human mobility data to study the spreading speed of this emergent threat. As opposed to other works, we take in to account the effects of exposure times, wireless propagation radii, and limited population susceptibility. Importantly, we find that lowering the susceptibility of the population to infection gives significant herd immunity as with biological infections, but unlike traditional Internet worms, making such threats unlikely in the near to medium term. Specifically, with susceptibility rates below 10% the result is near total immunity of the population. We find exposure times, and wireless transmission radii have no significant effect on outbreaks.