Secure Data Aggregation for Sensor Networks in the Presence of Collusion Attack using Local Outlier Factor

Aggregation of data from multiple sensor nodes is usually done by simple methods such as averaging or, more sophisticated, iterative filtering methods. However, such aggregation methods are highly vulnerable to malicious attacks. In this work, algorithms that remove false readings before estimating of true values are developed and evaluated. For detection of false readings local outlier factor (LOF) technique is used.