Authors - Chanuka Dinuwan, Hiruni Amandakoon, Iroshan Aberathne, Tharindu Wimalarathna, Rashmi Ratnayake Abstract - The Application Programming Interface (API) has become the primary method for integrating different software systems. Malicious bots have recently become the main cyber security threat and have been used as an infra-structure to carry out almost any form of cyberattack. The existing methods, however, have been insufficient for solving this issue, specifically in APIs. This study introduces an automated malicious bot attack detection tool for APIs based on artificial intelligence and machine learning. The time series forecasting, and neural network were used to develop a model on the API log data. Without human interaction, the trained model recognizes malicious bot attempts in APIs and prevents them in real time. Moreover, the performance measures of the model are a key indicator to using this application as a real time bot detector and preventer in API.
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