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
Modeling epidemic spreading in mobile environments
Proceedings of the 4th ACM workshop on Wireless security
A preliminary investigation of worm infections in a bluetooth environment
Proceedings of the 4th ACM workshop on Recurring malcode
Quantifying the Effectiveness of Mobile Phone Virus Response Mechanisms
DSN '07 Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
Can you infect me now?: malware propagation in mobile phone networks
Proceedings of the 2007 ACM workshop on Recurring malcode
Modeling Propagation Dynamics of Bluetooth Worms (Extended Version)
IEEE Transactions on Mobile Computing
An Investigation of Bluetooth Security Threats
ICISA '11 Proceedings of the 2011 International Conference on Information Science and Applications
Worm Propagation Modeling Using 2D Cellular Automata in Bluetooth Networks
TRUSTCOM '11 Proceedings of the 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications
Modeling and predicting the dynamics of mobile virus spread affected by human behavior
WOWMOM '11 Proceedings of the 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks
Foreword: Special issue of JCSS on UbiSafe computing and communications
Journal of Computer and System Sciences
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Smartphones combine the communication capabilities of cellphones and the functions of PDA (personal digital assistant), which enable us to access a large variety of ubiquitous services, such as surfing the web, sending/receiving emails, MMS, and online shopping. However, the availability of these services provided by smartphones increases the vulnerability to worm attacks. In addition, modeling on worm propagation in smartphones is particularly challenging because it is difficult to piece together dynamics from pair-wise device interactions. To characterize the propagation dynamics of worms in smartphones, we propose an efficient worm propagation modeling scheme using a two-dimensional cellular automata based on the epidemic theory. A set of suitable local transition rules is designed for the two-dimensional cellular automata in this scheme. Moreover, this scheme integrates an infection factor to evaluate the spread degree of infected nodes, and a resistance factor to evaluate the degree that susceptible nodes resist. Five classes of epidemic states are considered: susceptible, exposed, infected, diagnosed, and recovered. We explore a strategy for simulating the dynamics of worm propagation process from a single node to the entire network. The effectiveness and rationality of the proposed model have been validated through extensive simulations.