Ransomware is becoming an increasing concern in both the private sector and the public sector, because it can cause immediate financial damages or the loss of important data. The severity of ransomware attacks continues to grow from year to year, along with the associated costs, which have now reached the billions of dollars range. Ransomware attacks have become increasingly common, it is now more important than ever to develop anti-ransomware solutions that can protect users from ransomware. A new ransomware defense system, which is presented in this article is named as FCNNRD (Firefly Convolutional Neural Network based Ransomware Detection). In this FCNNRD firefly genetic algorithm was used to filter good set of features that increase learning of machine. Selected features ere further process for the deep feature extraction by applying convolutional and maxpooling operation. Experiment was done on real malware dataset. Results were compared with existing model on different evaluation parameters.

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