Abstract
The technological advancement in internet and communication systems of a smart city makes the cyber security a big gainsay. Eventually, securing the smart city objects is of prime importance. An intrusion detection system is one of the approaches to ameliorate cyber security in smart city. Regardless of elaborate research, IDS encounters many difficulties in finding breaches. So, deep learning is applied in developing IDS in recent years. This paper provides organized survey of the latest DL methods in constructing an efficient IDS. At first, IDS techniques with it types are explained. Later, various DL approaches, performance measures, datasets and implementation tools were introduced. Finally, findings and discussion and conclusion have been provided.
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