Abstract: A computing platform may train a machine learning model to detect and analyze threat actor activities. The computing platform may generate dynamic honeypotted files and deploy the generated dynamic honeypotted files as adaptive defenses to threat actors in a computing environment. The computing platform may adapt to threat actor activities based on analyzed behavior of the threat actor and any identified tools used by the threat actor to gain access to the computing system. Threat actor activities may be written to a blockchain to publicly record all transactions related to a threat actor's activities for analysis and generation of adaptive defenses to threat actor attacks. The computing platform may cause redirection of the threat actor into a specific computing environment through generation and deployment of dynamic honeypotted files.

Abstract: A computing platform may train a machine learning model to detect and analyze threat actor activities. The computing platform may generate dynamic honeypots and deploy the generated dynamic honeypots as adaptive defenses to threat actors in a computing environment. The computing platform may adapt to threat actor activities based on analyzed behavior of the threat actor and any identified tools used to by the threat actor to gain access to the computing system. The computing platform may cause redirection of the threat actor into a specific computing environment through generation and deployment of dynamic honeypots.