Modeling Node Compromise Spread in Wireless Sensor Networks Using Epidemic Theory
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
IEEE/ACM Transactions on Networking (TON)
Honeypots: concepts, approaches, and challenges
ACM-SE 45 Proceedings of the 45th annual southeast regional conference
An adaptive automatically tuning intrusion detection system
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
| Hi-index | 0.01 |
Modern networks are very complex. It is highly desirable to reduce management complexity in next generation network design. Researchers have been seeking inspiration in natural observations to help better manage the ever increasing complexity of modern networks. Bio-inspired and cognitive networks have shown tremendous promise towards better adapting networks to local stimuli intelligently, and to some extent without human intervention. In this paper, we discuss why the human brain is an excellent model for designing next generation smart networks. Insights gained into macro-behavior of the human brain and its structural organization in the last decade are discussed. We identify features that can be adapted for network modeling. We then propose a network design model based on our understanding of the mind, how cognition is achieved, how memory is formed, etc. We end this paper with a real life network design problem we address using the proposed general model.