Abujarad F.,Yale University |
Lin Y.,115 Engineering Building |
Bonakdarpour B.,McMaster University |
Kulkarni S.S.,115 Engineering Building
Distributed Computing | Year: 2015
Existing algorithms for automated model repair for adding fault-tolerance to fault-intolerant models incur an impediment that designers have to identify the set of legitimate states of the original model. This set determines states from where the original model meets its specification in the absence of faults. Experience suggests that of the inputs required for model repair, identifying such legitimate states is the most difficult. In this paper, we consider the problem of automated model repair for adding fault-tolerance where legitimate states are not explicitly given as input. We show that without this input, in some instances, the complexity of model repair increases substantially (from polynomial-time to NP-complete). In spite of this increase, we find that this formulation is relatively complete; i.e., if it was possible to perform model repair with explicit legitimate states, then it is also possible to do so without the explicit identification of the legitimate states. Finally, we show that if the problem of model repair can be solved with explicit legitimate states, then the increased cost of solving it without explicit legitimate states is very small. In summary, the results in this paper identify instances of automated addition of fault-tolerance, where the explicit knowledge of legitimate state is beneficial and where it is not very crucial. © 2014, Springer-Verlag Berlin Heidelberg.
Pongaliur K.,115 Engineering Building |
Xiao L.,115 Engineering Building |
Liu A.X.,115 Engineering Building
Journal of Supercomputing | Year: 2013
Compromised sensor nodes may collude to segregate a specific region of the sensor network preventing event reporting packets in this region from reaching the basestation. Additionally, they can cause skepticism over all data collected. Identifying and segregating such compromised nodes while identifying the type of attack with a certain confidence level is critical to the smooth functioning of a sensor network. Existing work specializes in preventing or identifying a specific type of attack and lacks a unified architecture to identify multiple attack types. Dynamic Camouflage Event-Based Malicious Node Detection Architecture (D-CENDA) is a proactive architecture that uses camouflage events generated by mobile-nodes to detect malicious nodes while identifying the type of attack. We exploit the spatial and temporal information of camouflage event while analyzing the packets to identify malicious activity. We have simulated D-CENDA to compare its performance with other techniques that provide protection against individual attack types and the results show marked improvement in malicious node detection while having significantly less false positive rate. Moreover, D-CENDA can identify the type of attack and is flexible to be configured to include other attack types in future. © 2010 Springer Science+Business Media, LLC.