Abstract:
This disclosure generally relates to automated execution and evaluation of computer network training exercises, such as in a virtual machine environment. An example environment includes a control and monitoring system, an attack system, and a target system. The control and monitoring system initiates a training scenario to cause the attack system to engage in an attack against the target system. The target system then performs an action in response to the attack. Monitor information associated with the attack against the target system is collected by continuously monitoring the training scenario. The attack system is then capable of sending dynamic response data to the target system, wherein the dynamic response data is generated according to the collected monitor information to adapt the training scenario to the action performed by the target system. The control and monitoring system then generates an automated evaluation based upon the collected monitor information.
Abstract:
A server system receives messages from client computing devices. Each of the messages corresponds to a transaction. The server system assigns each respective transaction to a respective fresh virtual machine. Furthermore, the server system performs, as part of a respective virtual machine processing a respective transaction, a modification associated with the respective transaction to a shared database. The shared database is persisted independently of the plurality of virtual machines. In response to determining that processing of the respective transaction is complete, the server system discards the respective virtual machine. In response to determining that the respective transaction is associated with a cyber-attack, the server system uses checkpoint data associated with the respective transaction to roll back the modifications associated with the respective transaction to the shared database.
Abstract:
An example method includes outputting a graphical dashboard that includes one or more learning objective nodes and one or more skill nodes, selecting one or more software agents that are associated with the one or more skill nodes, providing, to at least one host computing system, an indication of the one or more software agents that are configured to collect parameter data from the at least one host computing system while a trainee performs actions, receiving the parameter data collected by the one or more software agents during execution, determining, based on the parameter data, that the one or more skills represented by the one or more skill nodes have been demonstrated by the trainee, and updating the one or more skill nodes to graphically indicate that one or more represented skills have been demonstrated.
Abstract:
A server system receives messages from client computing devices. Each of the messages corresponds to a transaction. The server system assigns each respective transaction to a respective fresh virtual machine. Furthermore, the server system performs, as part of a respective virtual machine processing a respective transaction, a modification associated with the respective transaction to a shared database. The shared database is persisted independently of the plurality of virtual machines. In response to determining that processing of the respective transaction is complete, the server system discards the respective virtual machine. In response to determining that the respective transaction is associated with a cyber-attack, the server system uses checkpoint data associated with the respective transaction to roll back the modifications associated with the respective transaction to the shared database.
Abstract:
An example method includes outputting a graphical dashboard that includes one or more learning objective nodes and one or more skill nodes, selecting one or more software agents that are associated with the one or more skill nodes, providing, to at least one host computing system, an indication of the one or more software agents that are configured to collect parameter data from the at least one host computing system while a trainee performs actions, receiving the parameter data collected by the one or more software agents during execution, determining, based on the parameter data, that the one or more skills represented by the one or more skill nodes have been demonstrated by the trainee, and updating the one or more skill nodes to graphically indicate that one or more represented skills have been demonstrated.
Abstract:
This disclosure generally relates to automated execution and evaluation of computer network training exercises, such as in a virtual machine environment. An example environment includes a control and monitoring system, an attack system, and a target system. The control and monitoring system initiates a training scenario to cause the attack system to engage in an attack against the target system. The target system then performs an action in response to the attack. Monitor information associated with the attack against the target system is collected by continuously monitoring the training scenario. The attack system is then capable of sending dynamic response data to the target system, wherein the dynamic response data is generated according to the collected monitor information to adapt the training scenario to the action performed by the target system. The control and monitoring system then generates an automated evaluation based upon the collected monitor information.
Abstract:
This disclosure generally relates to automated execution and evaluation of computer network training exercises, such as in a virtual machine environment. An example environment includes a control and monitoring system, an attack system, and a target system. The control and monitoring system initiates a training scenario to cause the attack system to engage in an attack against the target system. The target system then performs an action in response to the attack. Monitor information associated with the attack against the target system is collected by continuously monitoring the training scenario. The attack system is then capable of sending dynamic response data to the target system, wherein the dynamic response data is generated according to the collected monitor information to adapt the training scenario to the action performed by the target system. The control and monitoring system then generates an automated evaluation based upon the collected monitor information.
Abstract:
A server system receives messages from client computing devices. Each of the messages corresponds to a transaction. The server system assigns each respective transaction to a respective fresh virtual machine. Furthermore, the server system performs, as part of a respective virtual machine processing a respective transaction, a modification associated with the respective transaction to a shared database. The shared database is persisted independently of the plurality of virtual machines. In response to determining that processing of the respective transaction is complete, the server system discards the respective virtual machine. In response to a trigger, such as determining that the respective transaction is associated with a cyber-attack, the server system uses checkpoint data associated with the respective transaction to roll back the modifications associated with the respective transaction to the shared database.
Abstract:
A survivable network is described in which one or more network device includes enhanced functionality to fight through cyber attacks. A Fight-Through Node (FTN) is described, which may be a combined hardware/software system that enhances existing networks with survivability properties. A network node comprises a hardware-based processing system having a set of one or more processing units, a hypervisor executing on each one of the processing units, and a plurality of virtual machines executing on each of the hypervisor. The network node includes an application-level dispatcher to receive a plurality of transaction requests from a plurality of network communication session with a plurality of clients and distribute a copy of each of the transaction requests to the plurality of virtual machines executing on the network node over a plurality of time steps to form a processing pipeline of the virtual machines.
Abstract:
This disclosure generally relates to automated execution and evaluation of computer network training exercises, such as in a virtual machine environment. An example environment includes a control and monitoring system, an attack system, and a target system. The control and monitoring system initiates a training scenario to cause the attack system to engage in an attack against the target system. The target system then performs an action in response to the attack. Monitor information associated with the attack against the target system is collected by continuously monitoring the training scenario. The attack system is then capable of sending dynamic response data to the target system, wherein the dynamic response data is generated according to the collected monitor information to adapt the training scenario to the action performed by the target system. The control and monitoring system then generates an automated evaluation based upon the collected monitor information.