Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A decision engine includes: a genetic algorithm framework including a knowledge base of standard configurations, a candidate selector generator and a selector to select a candidate configuration from a plurality of preferred standard configurations in response to the candidate selector generator; a parallelized reasoning framework including an attack surface reasoning algorithm module to compute the security and cost tradeoffs of an attack surface associated with each candidate configuration; and a user interface framework including a web service engine where users can interact and provide feedback on direction of an evolution used in a genetic algorithm search for evolving defenses.

Abstract: A method for visually depicting complex events. Software agents are preferably employed to assist the human operator by collecting, enriching, selecting, aggregating, and analyzing data so that patterns of interest can be visually flagged or otherwise emphasized in the visual display. Events are depicted as an “event flow” from a source surface to a destination surface. Intervening surfaces may also be defined. The point of origin on the source surface reveals some information about the event flow, as does the point of impact on the destination surface. The event flow may be mapped to one or more intervening surfaces in order to visually depict other characteristics of the event. The entire depiction is rendered in a simulated three-dimensional view. The user is preferably given the ability to pan, zoom, and reorient the vantage point from which the user “views” the depiction on the computer display.

Abstract: A method for visually depicting complex events. Software agents are preferably employed to assist the human operator by collecting, enriching, selecting, aggregating, and analyzing data so that patterns of interest can be visually flagged or otherwise emphasized in the visual display. Events are depicted as an “event flow” from a source surface to a destination surface. Intervening surfaces may also be defined. The point of origin on the source surface reveals some information about the event flow, as does the point of impact on the destination surface. The event flow may be mapped to one or more intervening surfaces in order to visually depict other characteristics of the event. The entire depiction is rendered in a simulated three-dimensional view. The user is preferably given the ability to pan, zoom, and reorient the vantage point from which the user “views” the depiction on the computer display.