Approaches to Detecting Threats in Wireless Sensor Networks for Data Transmission Security

A wireless sensor network (WSN) has a large number of sensor nodes and is utilized to gather data and transfer it via the shortest way to the base station. A transceiver was built into each sensor node so that it could send and receive data to nearby base stations. Secured data transmission in WSN is a significant one for efficient attack detection. Attack detection identified and categorized the attacks in wireless networks through matching the predefined patterns. Attack detection is an essential one to identify the attacks and to avoid the threat immediately for minimizing the attack impacts. Sinkhole, black hole, grey hole, wormhole and sybil attacks are various types of attacks. Different researchers carried out their research on attack detection in WSN. But, the attack detection accuracy was not increased and time consumption was not minimized. Machine learning and deep learning strategies are described for effective attack detection in WSN to overcome the issues.