Abstract: The present invention discloses system and method to perform automated red teaming in organizational network replacing conventional orchestration and playbooks. The method includes obtaining input data and exit criterion for an organization from data sources. Further, the method includes determining attack surface associated with the organization based on the obtained input data and the exit criterion. The method includes identifying attack frontiers for the attack surfaces. Further, the method includes prioritizing the attack frontiers. Additionally, the method includes simulating the attack frontiers at the attack surfaces based on the prioritization. Moreover, the method includes determining attack paths associated with the attack surface based on results of simulation. Also, the method includes learning attack patterns associated with the attack paths based on the results of execution.

Abstract: The present invention discloses system and method to perform automated red teaming in organizational network replacing conventional orchestration and playbooks. The method includes obtaining input data and exit criterion for an organization from data sources. Further, the method includes determining attack surface associated with the organization based on the obtained input data and the exit criterion. The method includes identifying attack frontiers for the attack surfaces. Further, the method includes prioritizing the attack frontiers. Additionally, the method includes simulating the attack frontiers at the attack surfaces based on the prioritization. Moreover, the method includes determining attack paths associated with the attack surface based on results of simulation. Also, the method includes learning attack patterns associated with the attack paths based on the results of execution.

Abstract: A method for classifying a text fragment by applying one or more rule functions is provided. The method includes (i) obtaining a set of words from one or more sentences of the text fragment obtained from a multimedia content, (ii) mapping each word from the set of words with one or more category map tables to obtain a set of candidate vector, each candidate vector includes at least one category associated with each word, (iii) generating one or more category vectors based on the at least one category, (iv) applying rule functions on the one or more category vectors, (v) generating a candidate classification decision matrix based on the rule functions, and (vi) classifying the text fragment based on the candidate classification decision matrix. The candidate classification matrix includes results of each rule function applied on each of the category vector.

Abstract: A method for classifying a text fragment by applying one or more rule functions is provided. The method includes (i) obtaining a set of words from one or more sentences of the text fragment obtained from a multimedia content, (ii) mapping each word from the set of words with one or more category map tables to obtain a set of candidate vector, each candidate vector includes at least one category associated with each word, (iii) generating one or more category vectors based on the at least one category, (iv) applying rule functions on the one or more category vectors, (v) generating a candidate classification decision matrix based on the rule functions, and (vi) classifying the text fragment based on the candidate classification decision matrix. The candidate classification matrix includes results of each rule function applied on each of the category vector.