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Nowadays, Internet of Things (IoT) is considered as part our lives and it includes different aspects-from wearable devices to smart devices used in military applications. IoT connects a variety of devices and as such, the generated data is considered as ‘Big Data'. There has however been an increase in attacks in this era of IoT since IoT carries crucial information regarding banking, environmental, geographical, medical, and other aspects of the daily lives of humans. In this paper, a Distributed Attack Detection Model (DADEM) that combines two techniques-Deep Learning and Big Data analytics-is proposed. Sequential Deep Learning model is chosen as a classification engine for the distributed processing model after testing its classification accuracy against other classification algorithms like logistic regression, KNN, ID3 decision tree, CART, and SVM. Results showed that Sequential Deep Learning model …