Efficient Security Adaptation Framework for Internet of Things
Security of Internet of Things has become a hot research topic due to their wide deployment, their huge generated information and the increasing new runtime attacks they are facing. Thereby, applications are unaware of what security mechanisms to apply, as well as how to overcome dynamic changing attacks. Accordingly, the concept that must cope with this new security challenge has to satisfy an overall performance such as power consumption, being actually a key issue for internet of things. This research investigates methods mainly based on autonomic computing and adaption security to build a Framework capable of determining appropriate security means for a highly dynamic wireless network with respect to context aware, self optimization and self protection paradigms of autonomic system. Trust computing was the means used to mitigate the influence of attackers. We have carried out a deep comparison of our Framework with many other Frameworks, mainly with autonomic system. The results clearly show that our Framework is efficient in terms of survivability, overall network utilization and power consumption.
2016 International Conference on Computational Science and Computational Intelligence (CSCI)