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Issue No.01 - Jan.-Feb. (2015 vol.12)
pp: 98-110
Mohsen Rezvani , Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
Aleksandar Ignjatovic , Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
Elisa Bertino , Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
Sanjay Jha , Sch. of Comput. Sci. & Eng., Univ. of New South Wales, Sydney, NSW, Australia
Due to limited computational power and energy resources, aggregation of data from multiple sensor nodes done at the aggregating node is usually accomplished by simple methods such as averaging. However such aggregation is known to be highly vulnerable to node compromising attacks. Since WSN are usually unattended and without tamper resistant hardware, they are highly susceptible to such attacks. Thus, ascertaining trustworthiness of data and reputation of sensor nodes is crucial for WSN. As the performance of very low power processors dramatically improves, future aggregator nodes will be capable of performing more sophisticated data aggregation algorithms, thus making WSN less vulnerable. Iterative filtering algorithms hold great promise for such a purpose. Such algorithms simultaneously aggregate data from multiple sources and provide trust assessment of these sources, usually in a form of corresponding weight factors assigned to data provided by each source. In this paper we demonstrate that several existing iterative filtering algorithms, while significantly more robust against collusion attacks than the simple averaging methods, are nevertheless susceptive to a novel sophisticated collusion attack we introduce. To address this security issue, we propose an improvement for iterative filtering techniques by providing an initial approximation for such algorithms which makes them not only collusion robust, but also more accurate and faster converging.
wireless sensor networks, iterative methods, telecommunication security,iterative filtering algorithms, secure data aggregation technique, wireless sensor networks, collusion attacks, computational power, energy resources, multiple-sensor nodes, aggregating node, node compromising attacks, data trustworthiness, sensor node reputation, very-low-power processors, simple averaging method, weight factors, trust assessment,Energy efficiency, Resource management, Wireless sensor networks, Filtering theory, Data aggregation,collusion attacks, Wireless sensor networks, robust data aggregation
Mohsen Rezvani, Aleksandar Ignjatovic, Elisa Bertino, Sanjay Jha, "Secure Data Aggregation Technique for Wireless Sensor Networks in the Presence of Collusion Attacks", IEEE Transactions on Dependable and Secure Computing, vol.12, no. 1, pp. 98-110, Jan.-Feb. 2015, doi:10.1109/TDSC.2014.2316816
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