Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to implement trusted transfer learning on transformer-based phishing detection. In some examples, an apparatus includes processor circuitry to perform instructions to instantiate circuitry. The instantiated circuitry provides a uniform resource locator (URL) matrix corresponding to at least a portion of a URL address to a first transformer model and provide a web content data matrix corresponding to web content data on a web page at the URL address to a second transformer model. The instantiated circuitry performs data fusion on a first output from the first transformer model and a second output from the second transformer model to create a combined result. The instantiated circuitry determines at least whether phishing is detected at the URL address based at least in part on the combined result.

Abstract: An industrial process field device includes a pressure sensor, and a housing containing the pressure sensor. The housing includes a base having a base interface and a first base process opening. A flange is attached to the base and includes a flange interface having a first flange process opening. A first gasket process opening of a gasket is aligned with the first base process opening and the first flange process opening. A first surface of the gasket engages the base interface, and a second surface of the gasket engages the flange interface. A dielectric insulation system includes at least one dielectric layer that insulates the housing from electrical currents conducted through the flange. Each dielectric layer includes a layer of ceramic material, an anodized layer, or a plastic overmold, which improve a maximum working pressure of the field device.

Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to analyze network traffic for malicious activity. An example apparatus includes a graph generator to, in response to obtaining one or more internet protocol addresses included within input data, generate a graph data structure based on one or more features of the one or more internet protocol addresses in the input data, a file generator to generate a first matrix using the graph data structure, the first matrix to represent nodes in the graph data structure and generate a second matrix using the graph data structure, the second matrix to represent edges in the graph data structure, and a classifier to, using the first matrix and the second matrix, classify at least one of the one or more internet protocol addresses to identify a reputation of the at least one of the one or more internet protocol addresses.

Abstract: There is disclosed herein a computing apparatus having a hardware platform, including a processor circuit and a memory; a web-enabled application; and stored instructions within the memory to instruct the processor circuit to: determine that an input field of the web-enabled application has requested a password or personal data from a user; receive an input value; apply a deterministic function to the input value to create an obfuscated value; and provide the obfuscated value as an input to the input field.

Abstract: A computing apparatus includes a hardware platform comprising a processor and a memory; and instructions encoded within the memory to receive a user-generated comment related to a uniform resource locator (URL); analyze the comment with a trained machine learning (ML) model to determine a user sentiment for the comment; assign a predicted reputation to the URL according to the user sentiment; and use the predicted reputation as an input to an analysis of the URL.

Abstract: An industrial process field device includes a pressure sensor, and a housing containing the pressure sensor. The housing includes a base having a base interface and a first base process opening. A flange is attached to the base and includes a flange interface having a first flange process opening. A pressure at the first flange process opening is communicated to the pressure sensor through the first base process opening. A first gasket process opening of a gasket is aligned with the first base process opening and the first flange process opening. A first surface of the gasket engages the base interface, and a second surface of the gasket engages the flange interface. A dielectric insulation system includes at least one dielectric layer that insulates the housing from electrical currents conducted through the flange. Each dielectric layer includes a layer of ceramic material, an anodized layer, or a plastic overmold.

Abstract: There is disclosed an example of one or more tangible, non-transitory computer-readable storage media, including instructions to: enumerate domain names newly registered in a time window; build a dictionary from the newly registered domain names; cluster the domain names, including performing a spell check with the dictionary to identify similar domain names; for a selected cluster, identify one or more domain names with an assigned reputation; and if a portion of assigned reputations exceeds a threshold of bad reputations, assign cluster-based bad reputations to domains in the cluster with unknown reputations.

Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to analyze network traffic for malicious activity. An example apparatus includes a graph generator to, in response to obtaining one or more internet protocol addresses included within input data, generate a graph data structure based on one or more features of the one or more internet protocol addresses in the input data, a file generator to generate a first matrix using the graph data structure, the first matrix to represent nodes in the graph data structure and generate a second matrix using the graph data structure, the second matrix to represent edges in the graph data structure, and a classifier to, using the first matrix and the second matrix, classify at least one of the one or more internet protocol addresses to identify a reputation of the at least one of the one or more internet protocol addresses.

Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.

Abstract: Methods, apparatus, systems and articles of manufacture for producing generic Internet Protocol (IP) reputation through cross-protocol analysis are disclosed. An example apparatus includes a data collector to gather a first data set representing IP telemetry data for a first protocol, the data collector to gather a second data set representing IP telemetry data for a second protocol different from the first protocol. A label generator is to generate a training data set based on records in the first data set and the second data set having matching IP addresses, the training data set to include combined label indicating whether each of the respective matching IP addresses is malicious. A model trainer is to train a machine learning model using the training data set. A model executor is to, responsive to a request from a client device, execute the machine learning model to determine whether a requested IP address is malicious.

Abstract: A field device assembly includes an industrial process field device, a flange and a sealing and electrically insulating system. The field device includes a pressure sensor and a housing containing the active component. The housing includes a base having a base interface, which includes a first base process opening. The flange is attached to the base of the housing and includes a coplanar interface having a first flange process opening. The sealing and electrically insulating system includes a gasket that includes a dielectric material. A first process opening in the gasket is aligned with the first base process opening and the first flange process opening. A first surface of the gasket engages the base interface, and a second surface of the gasket that is opposite the first surface engages the coplanar interface. The gasket electrically insulates the housing of the field device from the flange.

Abstract: A field device assembly includes an industrial process field device, a flange and a sealing and electrically insulating system. The field device includes a pressure sensor and a housing containing the active component. The housing includes a base having a base interface, which includes a first base process opening. The flange is attached to the base of the housing and includes a coplanar interface having a first flange process opening. The sealing and electrically insulating system includes a gasket that includes a dielectric material. A first process opening in the gasket is aligned with the first base process opening and the first flange process opening. A first surface of the gasket engages the base interface, and a second surface of the gasket that is opposite the first surface engages the coplanar interface. The gasket electrically insulates the housing of the field device from the flange.

Abstract: A system for link analysis, having records of plural record types, and having links of plural link types, the links linking pairs of the records. Some of the pairs may be of different record types. The system may also have an index indexing the records of plural record types. The record types may have respectively different sets of fields. The index may index one or more of the fields of each of the records. The records may correspond to real world entities or information, and the fields and their names may correspond to attributes of the entities. Metadata or the like may map the fields to the field names, and may be used to sensibly display related information, such set of the records, etc. All entities or records may be searched, which may be combined with link search and analysis. Point-to-point searches and repeated search refinement may also be provided.