Paper Details

Due to restricted procedure power resources and energy resources, aggregation of data from multiplesensing element nodes done at the aggregating node is sometimes accomplished by easy strategies like averaging. butsuch aggregation is thought to be extremely liable to node compromising attacks. Since WSN are typically unattendedand while not tamper resistant hardware, they're extremely prone to such attacks. Thus, ascertaining trait of knowledgeand name of sensing element nodes is crucial for WSN. Because the performance of terribly low power processorsdramatically improves, future individual nodes are going to be capable of playing additional refined informationaggregation algorithms, therefore creating WSN less vulnerable. Repetitive filtering algorithms hold nice promise forsuch a purpose. Such algorithms at the same time mixture information from multiple sources and supply trust assessmentof those sources, typically in a very type of corresponding weight factors allotted to information provided by everysupply. During this paper we tend to demonstrate that many existing repetitive filtering algorithms, whereas considerablyadditional strong against collusion attacks than the easy averaging strategies, are nonetheless susceptive to a uniquerefined collusion attack we tend to introduce. To deal with this security issue, we tend to propose AN improvement forrepetitive filtering techniques by providing AN initial approximation for such algorithms that makes them not solelycollusion strong, however conjointly additional correct and quicker joining.

Siddharth C Sawai, Prof. S. N. Shelke, “Secure Data Aggregation Technique For Wireless Networks”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 1, pp. 1-5, January 2017.