Abstract: A processor-implemented method for detecting an information operations campaign includes retrieving a first neural network language model including a natural language model trained on a first dataset. The first neural network language model is modified, via transfer learning and based on a second dataset, to produce a second neural network language model. Social media post data associated with a social media post is received, and features are extracted from the social media post data. The features are tokenized to produce at least one token including a value. A prediction score for the at least one token is generated using the trained neural network language model. If the prediction score exceeds a threshold value, a threat warning including a representation associated with at least one of the social media post or an account associated with the social media post is generated.

Abstract: A processor-implemented method for detecting an information operations campaign includes retrieving a first neural network language model including a natural language model trained on a first dataset. The first neural network language model is modified, via transfer learning and based on a second dataset, to produce a second neural network language model. Social media post data associated with a social media post is received, and features are extracted from the social media post data. The features are tokenized to produce at least one token including a value. A prediction score for the at least one token is generated using the trained neural network language model. If the prediction score exceeds a threshold value, a threat warning including a representation associated with at least one of the social media post or an account associated with the social media post is generated.

Abstract: A processor-implemented method for detecting an information operations campaign includes retrieving a first neural network language model including a natural language model trained on a first dataset. The first neural network language model is modified, via transfer learning and based on a second dataset, to produce a second neural network language model. Social media post data associated with a social media post is received, and features are extracted from the social media post data. The features are tokenized to produce at least one token including a value. A prediction score for the at least one token is generated using the trained neural network language model. If the prediction score exceeds a threshold value, a threat warning including a representation associated with at least one of the social media post or an account associated with the social media post is generated.

Abstract: An automated system and method for analyzing a set of extracted strings from a binary is disclosed including processing the binary with a string-extraction logic that can locate strings within the binary and output an extracted string set for use in cybersecurity analysis. The logic retrieves a set of training data comprising a plurality of previously analyzed extracted string sets where each element of the previously analyzed extracted string set comprises at least one extracted string and a corresponding previously determined threat prediction score. A prediction model based upon the training data is generated and the extracted string set is processed by the prediction model to determine a threat prediction score for each string. Ranking of the located strings is based upon the determined threat prediction score, and an output of a ranked string list is generated.

Abstract: A computer-implemented method includes scanning, by one or more processors, data that is maintained on one or more social networks, analyzing the scanned data using one or more machine learning techniques, generating custom content associated with a target social entity, initiating interaction with the target social entity, where initiating interaction with the target social entity includes, posting, by the one or more processors, a form of the generated custom content associated with the target social entity to one or more of the target social entity's social networks.

Abstract: An electrosurgical system preferably used for denervation procedures of nerve tissue has a control unit and a pluggable electrode assembly. The electrode assembly has a preferably disposable cannula and a preservable supply electrode assembly. The cannula has a tubular body that projects axially from a preferably pointed distal end for piercing tissue to a proximal end engaged to a first coupling assembly of the cannula. The body carries a first contact exposed directly to the nerve tissue and connected electrically to a terminal of the first coupling assembly. The supply electrode assembly has a second coupling assembly and a supply electrode that projects axially and removably into a through-bore of the body when the tool is in an operating state. The second coupling assembly carries a terminal that abuts the first coupling assembly when the coupling assemblies are mated.