Accenture Global Solutions Limited

Avraham Dayan

Eitan Hadar

Moshe Hadad

Amin Hassanzadeh

Dani Grabois

Alexander Basovskiy

Gil Fidel

Dmitry Kravchenko

Gal Engelberg

Implementations include evaluating a first sub-set of rules based on a first sub-set of facts to provide a first set of impacts, evaluating including applying the first sub-set of facts to each rule using a hash join operation to determine whether a rule results in an impact, indexes of arguments of facts being used in a probe phase of the hash join operation, evaluating a second sub-set of rules using impacts of the first set of impacts to provide a second set of impacts, determining whether each goal in a set of goals has been achieved using the first set of impacts and the second set of impacts, each goal being provided as an impact, in response to determining that each goal in the set of goals has been achieved, removing paths of the AAG, each of the paths resulting in an impact that is not a goal.

Resource-efficient generation of analytical attack graphs

Implementations of the present disclosure include providing, by a security platform, graph data defining a graph that is representative of an enterprise network, the graph including nodes and edges between nodes, a set of nodes representing respective assets within the enterprise network, and a node representing a process executed within a system of the enterprise, each edge representing at least a portion of one or more lateral paths between assets in the enterprise network, determining, for each asset, a contribution value indicating a contribution of a respective asset to operation of the process, determining, for each asset, an impact value based on a total value of the process and a respective contribution value of the asset, and implementing one or more remediations based on a set of impact values determined for the assets, each remediation mitigating a cyber-security risk within the enterprise network.

Generating attack graphs in agile security platforms

Implementations of the present disclosure include executing, within a computer network, multiple instances of a process, each instance including a simulation of execution of the process within the computer network, receiving session datasets representative of sessions performed during execution of each instance of the process, generating a set of session traces, each session trace representing a sequence of sessions performed during an instance of the process within the computer network, processing the set of session traces using a clustering algorithm to cluster sessions of each session trace into two or more clusters, each cluster having an associated label, and providing a process model that generically represents multiple executions of the process within the computer network, the process model comprising a sequence of labels of the two or more clusters corresponding to session traces in the set of session traces.

Enterprise process discovery through network traffic patterns

Growing community of inventors

Bnei Brak, Israel

Avraham Dayan