Techniques for searching an inverted index associating byte sequences of a fixed length and files that contain those byte sequences are described herein. Byte sequences comprising a search query are determined and searched in the inverted index. In some examples, training data for training machine learning model(s) may be created using pre-featured data from the inverted index. In various examples, training data may be used to retrain a ML model until the ML model meets a criterion. In some examples, the trained ML model may be used to perform searches on the inverted index and classify files.

Techniques for searching an inverted index associating byte sequences of a fixed length and files that contain those byte sequences are described herein. Byte sequences comprising a search query are determined and searched in the inverted index. In some examples, training data for training machine learning model(s) may be created using pre-featured data from the inverted index. In various examples, training data may be used to retrain a ML model until the ML model meets a criterion. In some examples, the trained ML model may be used to perform searches on the inverted index and classify files.

An intelligent-adversary simulator can construct a graph of a virtualized instance of a network including devices connecting to the virtualized instance of the network as well as connections and pathways through the virtualized instance of the network. Running a simulated cyber-attack scenario on the virtualized instance of the network in order to identify one or more critical devices connecting to the virtualized instance of the network from a security standpoint, and then put this information into a generated report to help prioritize which devices should have a priority. During a simulation, the intelligent-adversary simulator calculates paths of least resistance for a cyber threat in the cyber-attack scenario to compromise a source device through to other components until reaching an end goal of the cyber-attack scenario in the virtualized network, all based on historic knowledge of connectivity and behaviour patterns of users and devices within the actual network under analysis.

An intelligent-adversary simulator can construct a graph of a virtualized instance of a network including devices connecting to the virtualized instance of the network as well as connections and pathways through the virtualized instance of the network. Running a simulated cyber-attack scenario on the virtualized instance of the network in order to identify one or more critical devices connecting to the virtualized instance of the network from a security standpoint, and then put this information into a generated report to help prioritize which devices should have a priority. During a simulation, the intelligent-adversary simulator calculates paths of least resistance for a cyber threat in the cyber-attack scenario to compromise a source device through to other components until reaching an end goal of the cyber-attack scenario in the virtualized network, all based on historic knowledge of connectivity and behaviour patterns of users and devices within the actual network under analysis.

This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

A system and method for automatic generation of a data tree structure are disclosed. A database stores contract metadata associated with a plurality of contracts. The metadata includes relationship information data regarding parentage and/or child relationship between a particular contract and other contracts among the plurality of contracts. A processor operatively connects to the database via a communication network and accesses the database via the communication network to retrieve the contract metadata including the relationship information data. The processor also implements a search engine; stores the retrieved contract metadata including the relationship information data onto the search engine for creating a linkage between data points; and automatically generates, based on the created linkage between the data points, both an application programming interface (API) and a data tree structure that displays inter-dependency between two or more sets of contracts among the plurality of contracts.

A system and method for automatic generation of a data tree structure are disclosed. A database stores contract metadata associated with a plurality of contracts. The metadata includes relationship information data regarding parentage and/or child relationship between a particular contract and other contracts among the plurality of contracts. A processor operatively connects to the database via a communication network and accesses the database via the communication network to retrieve the contract metadata including the relationship information data. The processor also implements a search engine; stores the retrieved contract metadata including the relationship information data onto the search engine for creating a linkage between data points; and automatically generates, based on the created linkage between the data points, both an application programming interface (API) and a data tree structure that displays inter-dependency between two or more sets of contracts among the plurality of contracts.

Systems and methods for a media guidance application that generates results in multiple languages for search queries. In particular, the media guidance application resolves multiple language barriers by taking automatic and manual user language settings and applying those settings to a variety of potential search results.

Systems and methods for a media guidance application that generates results in multiple languages for search queries. In particular, the media guidance application resolves multiple language barriers by taking automatic and manual user language settings and applying those settings to a variety of potential search results.