Diagnosis of malaria must be rapid, accurate, simple to use, portable and low cost, as suggested by the World Health Organization (WHO). Despite recent efforts, the gold standard remains the light microscopy of a stained blood film. This method can detect low parasitemia and identify different species of Plasmodium. However, it is time consuming, it requires well trained microscopist and good instrumentation to minimize misinterpretation, thus the costs are considerable. Moreover, the equipment cannot be easily transported and installed. In this paper we propose a new technique named "secondary speckle sensing microscopy" (S3M) based upon extraction of correlation based statistics of speckle patterns generated while illuminating red blood cells with a laser and inspecting them under a microscope. Then, using fuzzy logic ruling and principle component analysis, good quality of separation between healthy and infected red blood cells was demonstrated in preliminary experiments. The proposed technique can be used for automated high rate detection of malaria infected red blood cells.