Abstract: A computer system automatically generates a proposal for network application security policies to be applied on a telecommunications network. The system provides output representing the proposed network application security policies to a user. The user provides input either approving or disapproving of the network application security policies. If the user approves, then the system applies the of the proposed microsegmentation. This process may be repeated for a plurality of hosts and subsets thereof within the same network, and may be repeated over time to modify one or more existing network application security policies. The network application security policies govern inbound and outbound connections to the hosts in the network.

Abstract: A computer system automatically tests a network communication model by predicting whether particular traffic (whether actual or simulated) should be allowed on the network, and then estimating the accuracy of the network communication model based on the prediction. Such an estimate may be generated even before the model has been applied to traffic on the network. For example, the model may be generated based on a first set of network traffic. The accuracy of the model may then be estimated based on a second set of network traffic. This allows the accuracy of the model to be estimated without first waiting to apply the model to actual network traffic, thereby reducing the risk associated with applying the model before its accuracy is known.

Abstract: A system validates the establishment and/or continuation of a connection between two applications over a network. The system uses network application security rules to allow or disallow connections between the two applications. Those rules include definitions of the source and destination applications to which the rules apply. The system automatically updates the application definitions over time to encompass new versions of the applications covered by the security rules, but without encompassing other applications. The system is then capable of applying the updated rules both to the original applications and to the updated versions of those applications. This process enables the security rules to maintain security over time in a way that is consistent with the original intent of the rules even as applications on the network evolve.

Abstract: A computer system automatically generates a proposal for performing microsegmentation on a network. The system provides output representing the proposed microsegmentation to a user. The user provides input either approving or disapproving of the proposed microsegmentation. If the user approves of the proposed microsegmentation, then the system implements the microsegmentation. Otherwise, the system does not implement the proposed microsegmentation. This process may be repeated for a plurality of proposed microsegmentations within the same network, and may be repeated over time to modify one or more existing microsegmentations. The system advantageously performs the vast majority of the work required to microsegment the network automatically, leaving only the task of review and approval to the user. This both saves a significant amount of time and increases the quality of the microsegmentation in comparison to microsegmentation solely performed manually by one or more humans.

Abstract: Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Abstract: A computer system automatically learns which application behavior constitutes “multi-use” behavior by observing the behavior of applications on a network. The system uses this learned knowledge to automatically identify multi-use behavior in new applications that appear on the network. When the system enforces security policies against applications on the network, it identifies whether particular behavior of such applications violates any of the security policies. In this way, the system adapts automatically to new behavior of applications on the network over time in order to increase network security.

Abstract: Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.

Abstract: Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Abstract: Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.

Abstract: Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Abstract: Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.

Abstract: Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.

Abstract: Embodiments of the present invention generate network communication policies by applying machine learning to existing network communications, and without using information that labels such communications as healthy or unhealthy. The resulting policies may be used to validate communication between applications (or services) over a network.

Abstract: A computer system processes a plurality of unrelated database tables to create a join graph where each node in the join graph represents a table. The nodes in the join graph are connected by weighted, directed edges, where each directed edge represents a join from a first column in a first table to a second column in a second table and where the weight of the directed edge represents a predicted level of success in performing the join. The edge weights can be based on a likelihood of finding a value from the first column in the second column. A user selects a subset of the tables, and the system creates a join tree with recommended joins between the tables selected by the user. The recommended joins are used to create a structured query language statement which is executed to return a result to the user.

Abstract: A computer system processes a plurality of unrelated database tables to create a join graph where each node in the join graph represents a table. The nodes in the join graph are connected by weighted, directed edges, where each directed edge represents a join from a first column in a first table to a second column in a second table and where the weight of the directed edge represents a predicted level of success in performing the join. The edge weights can be based on a likelihood of finding a value from the first column in the second column. A user selects a subset of the tables, and the system creates a join tree with recommended joins between the tables selected by the user. The recommended joins are used to create a structured query language statement which is executed to return a result to the user.

Abstract: A computer system processes a plurality of unrelated database tables to create a join graph where each node in the join graph represents a table. The nodes in the join graph are connected by weighted, directed edges, where each directed edge represents a join from a first column in a first table to a second column in a second table and where the weight of the directed edge represents a predicted level of success in performing the join. The edge weights can be based on a likelihood of finding a value from the first column in the second column. A user selects a subset of the tables, and the system creates a join tree with recommended joins between the tables selected by the user. The recommended joins are used to create a structured query language statement which is executed to return a result to the user.

Abstract: The invention relates to pharmaceutically active compounds having improved pharmacokinetic properties and being useful for the treatment or prevention of a range of conditions including migraine, epilepsy, non-epileptic seizures, brain injury (including stroke, intracranial haemorrhage and trauma induced) or cardiovascular diseases including myocardial infarction, coronary revascularization or angina. The compounds of the invention form a novel group of related prodrugs of formula (II), where Ar is a 3-chloro-4-fluorophenyl ring, a 3-chlorophenyl ring or a 4-fluorophenyl ring; and R is a hydrolysable group comprising an amino group or an acidic group.

Abstract: A document can be processed to provide sentiment values for phrases in the document. The sequence of sentiment values associated with the sequence of phrases in a document can be handled as if they were a sampled discrete time signal. For phrases which have been identified as entities, a filtering operation can be applied to the sequence of sentiment values around each entity to determine a sentiment value for the entity.

Abstract: A computer system processes a plurality of unrelated database tables to create a join graph where each node in the join graph represents a table. The nodes in the join graph are connected by weighted, directed edges, where each directed edge represents a join from a first column in a first table to a second column in a second table and where the weight of the directed edge represents a predicted level of success in performing the join. The edge weights can be based on a likelihood of finding a value from the first column in the second column. A user selects a subset of the tables, and the system creates a join tree with recommended joins between the tables selected by the user. The recommended joins are used to create a structured query language statement which is executed to return a result to the user.

Abstract: A computer system processes arbitrary data sets to identify fields of data that can be the basis of a join operation. Each data set has a plurality of entries, with each entry having a plurality of fields. For each pair of data sets, the computer system compares the values of fields in a first data set in the pair of data sets to the values of fields in a second data set in the pair of data sets, to identify fields having substantially similar sets of values. Given pairs of fields that have similar sets of values, the computer system measures entropy with respect to an intersection of the sets of values of the pair of fields. The computer system can recommend fields for a join operation between any pair of data sets in the plurality of data sets based on such statistical measures.