Search-Based Physical Attacks in Sensor Networks
Proceedings of IEEE International Conference on Computer Communication and Networks (ICCCN)
2005
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Conference Paper Description
The small form factor of the sensors, coupled with the unattended and distributed nature of their deployment expose sensors to Physical Attacks that physically destroy sensors in the network. In this paper, we study the modeling and analysis of Search-based Physical Attacks in sensor networks. We define a search-based physical attack model, where the attacker walks through the sensor network using signal detecting equipment to locate active sensors, and then destroys them. We consider both flat and hierarchical sensor networks. The attacker in our model uses a weighted random selection based approach to discriminate multiple target choices (normal sensors and clusterheads) to enhance sensor network performance degradation. Our performance metric in this paper is Accumulative Coverage (AC), which effectively captures coverage and lifetime of the sensor network. We then conduct detailed evaluations on the impacts of search-based physic attacks on sensor network performance. Our performance data clearly show that search-based physical attacks significantly reduce sensor network performance. We observe that attack related parameters, namely attacker movement speed, detection range and accuracy have significant impacts on the attack effectiveness. We also observe that the attack effectiveness is significantly impacted by sensor network parameters, namely the frequency of communication and frequency of cluster-head rotation. We believe that our work in this paper on modeling and analyzing search-based physical attacks is an important first step in understanding their overall impacts, and effectively defending against them in the future.
Bibliographic Details
Institute of Electrical and Electronics Engineers (IEEE)
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