title,doi,url,abstract,journal,publication_year,pmid,arxiv
Temperature analysis with respect to time maintenance in a WSN, https://doi.org/10.32628/IJSRCSEIT, https://ijsrcseit.com/CSEIT172272, We address the problem of preventing the inference of contextual information in event-driven wireless sensor networks (WSNs). The problem is considered under a global eavesdropper who analyzes low-level RF transmission attributes such as the number of transmitted packets inter-packet times and traffic directionality to infer event location its occurrence time and the sink location. We devise a general traffic analysis method for inferring contextual information by correlating transmission times with eavesdropping locations. Our analysis shows that most existing countermeasures either fail to provide adequate protection or incur high communication and delay overheads. To mitigate the impact of eavesdropping we propose resource-efficient traffic normalization schemes. In comparison to the state-of-the-art our methods reduce the communication overhead by more than 50%; and the end-to-end delay by more than 30%. To do so we partition the WSN to minimum connected dominating sets that operate in a round-robin fashion. This allows us to reduce the number of traffic sources active at a given time while providing routing paths to any node in the WSN. We further reduce packet delay by loosely coordinating packet relaying without revealing the traffic directionality, International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2017, CSEIT172272