Abstract: A teaching server computer system employs a teaching strategy developed through deep reinforcement learning to teach humans one or more academic languages to fluency. Teaching machine logic is trained in two phases. In a first phase, the teaching machine logic and corresponding student machine logic are trained with supervised training using available recorded lessons of human teachers and human students to provide initial generative models of the teaching logic and the student logic. In the second phase, the initial generative models of the teaching and student logic are combined in virtual lessons in which the teaching logic teaches the student logic in the academic language. The performance of the student logic in learning the academic language is scored and the scores are used to generate rewards in the environment of the deep reinforcement training.

Abstract: System and method for detecting a domain generation algorithm (DGA), comprising: performing processing associated with clustering, utilizing a name-based features clustering module accessing information from an electronic database of NX domain information, the randomly generated domain names based on the similarity in the make-up of the randomly generated domain names; performing processing associated with clustering, utilizing a graph clustering module, the randomly generated domain names based on the groups of assets that queried the randomly generated domain names; performing processing associated with determining, utilizing a daily clustering correlation module and a temporal clustering correlation module, which clustered randomly generated domain names are highly correlated in daily use and in time; and performing processing associated with determining the DGA that generated the clustered randomly generated domain names.

Abstract: A method and system for detecting a malicious domain name, comprising: collecting domain name statistical information from a non-recursive domain name system name server (RDNS NS); and utilizing the collected domain name statistical information to determine if a domain name is malicious or benign.

Abstract: A method and system for detecting a malicious domain name, comprising: collecting domain name statistical information from a non-recursive domain name system name server (RDNS NS); and utilizing the collected domain name statistical information to determine if a domain name is malicious or benign.