A performance comparison of multi-hop wireless ad hoc network routing protocols
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
An epidemic model for information diffusion in MANETs
MSWiM '02 Proceedings of the 5th ACM international workshop on Modeling analysis and simulation of wireless and mobile systems
The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Stochastic properties of the random waypoint mobility model
Wireless Networks
Analysis and implications of student contact patterns derived from campus schedules
Proceedings of the 12th annual international conference on Mobile computing and networking
Bluetooth worm propagation: mobility pattern matters!
ASIACCS '07 Proceedings of the 2nd ACM symposium on Information, computer and communications security
Performance modeling of epidemic routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
SmartSiren: virus detection and alert for smartphones
Proceedings of the 5th international conference on Mobile systems, applications and services
Can you infect me now?: malware propagation in mobile phone networks
Proceedings of the 2007 ACM workshop on Recurring malcode
Proximity breeds danger: emerging threats in metro-area wireless networks
SS'07 Proceedings of 16th USENIX Security Symposium on USENIX Security Symposium
Behavioral detection of malware on mobile handsets
Proceedings of the 6th international conference on Mobile systems, applications, and services
Detecting energy-greedy anomalies and mobile malware variants
Proceedings of the 6th international conference on Mobile systems, applications, and services
On capturing malware dynamics in mobile power-law networks
Proceedings of the 4th international conference on Security and privacy in communication netowrks
EpiNet: a simulation framework to study the spread of malware in wireless networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
VirusMeter: Preventing Your Cellphone from Spies
RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
A random walk model for infection on graphs
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Modeling and analysis malware spread in short-range wireless networks
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
A taxonomy of biologically inspired research in computer networking
Computer Networks: The International Journal of Computer and Telecommunications Networking
An empirical analysis of serendipitous media sharing among campus-wide wireless users
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A random walk model for infection on graphs: spread of epidemics & rumours with mobile agents
Discrete Event Dynamic Systems
Epidemic spread in mobile Ad Hoc networks: determining the tipping point
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
An epidemic model with adaptive virus spread control for Wireless Sensor Networks
International Journal of Security and Networks
What you see predicts what you get—lightweight agent-based malware detection
Security and Communication Networks
Modeling the dynamics of worm propagation using two-dimensional cellular automata in smartphones
Journal of Computer and System Sciences
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The growing popularity of mobile networks makes them increasingly attractive to virus writers, and malicious code targeting mobile devices has already begun to appear. Unfortunately, standard techniques for modeling computer virus propagation cannot be applied to mobile settings. We describe why these models fail and introduce a new framework called probabilistic queuing which treats node mobility as a first-order concern. A network is modeled by multiple queues which emulate the skewed connectivity levels common in mobile environments. Each queue represents a separate epidemiological population, and as nodes shuttle between queues, they bring their infections with them. Simulations show that for realistic mobility parameters, our model is more accurate than the standard Kephart-White framework.