Abstract: A system and method for crowdsourced innovation and automated process implementation, wherein individuals and businesses use a distributed computational graph module with crowdsourcing-technology to develop ideas and create process workflows for implementing those ideas. The developed process workflows are implemented through a system which automatically integrates heterogenous Internet resources such as electronic commerce, recruiting, and management platforms into a single portal. Businesses and other collaboration initiatives are supported via crowdsourced labor that are automatically orchestrated by the distributed computational graph workflows and user interface that provide a comprehensive and convergent solution for process management.

Abstract: A system and method for universalization and contextualization of computing assets that utilizes structure, organization, and ontologically-related metadata to unify computing assets into a common data model combined with provenance-related metadata to contextualize the assets for suitability in a given situation. The system and method include an asset registry that contains provenance information and ontological information about available computing assets, a provenance manager which tracks the provenance of each asset for data validation and contextual analysis purposes, an ontology manager that uses ontological relationships among assets to determine other domains in which an asset may be useful, and an interoperability manager which combines the provenance and ontology outputs to suggest computing assets that may be useful in a given context.

Abstract: A system for compensable crowdsourced data extraction and collection. Users and other entities crowdsource telemetric, analytic, and other types of data from owned devices which is secured, anonymized, and subsequently stored with other user's data. The crowdsourced data is offered to clients who then release payments to the system for compensable crowdsourced data extraction and collection that in turn compensates the users. Clients and other entities request existing data or present offers to gather new data while also being able to be offer its own data sources for compensation. Entities may also allocate computing power from owned devices for distributed computing requests by clients or as an architecture model for the system for compensable crowdsourced data extraction and collection. Application programming interfaces allow the connectivity between the vast number of Internet-connected devices and the system for compensable crowdsourced data extraction and collection.

Abstract: A system and method for providing access and agency to individual entities and people over their data for the purpose of data set validation to facilitate data set and algorithm bias certification and scoring. A first data set is filtered to extract its core information content and to create a certified data set. A certified model is created by training a machine learning algorithm on the certified data set, which certified model is then used to evaluate the bias of subsequent data sets. The data set may be given a value score which represents the overall validity of the data set and its bias characterization. A bias characterization audit can help identify the root causes of bias outcomes from predictive software and algorithms that perform third party tasks and services. The score can be used as a metric to further facilitate market transactions.

Abstract: A system for contextual data collection and extraction is provided, comprising an extraction engine configured to receive context from a user for desired information to extract, connect to a data source providing a richly formatted dataset, retrieve the richly formatted dataset, process the richly formatted dataset and extract information from a plurality of linguistic modalities within the richly formatted, and transform the extracted data into a extracted dataset; and a knowledge base construction service configured to retrieve the extracted dataset, create a knowledge base for storing the extracted dataset, and store the knowledge base in a data store.

Abstract: A system and methods for sandboxed malware analysis and automated patch development, deployment and validation, comprising a business operating system, vulnerability scoring engine, binary translation engine, sandbox simulation engine, at least one network endpoint, at least one database, a network, and a combination of machine learning and vulnerability probing techniques, to analyze software, locate any vulnerabilities or malicious behavior, and attempt to patch and prevent undesired behavior from occurring, autonomously.

Abstract: A system for autonomous issuance and management of insurance policies for computer and information technology related risks, including but not limited to business losses due to system availability, cloud computing failures, current and past data breaches, and data integrity issues. The system will use a variety of current risk information to assess the likelihood of business interruption or loss due to both accidental issues and malicious activity. Based on these assessments, the system will be able to autonomously issue policies, adjust premium pricing, process claims, and seek re-insurance opportunities with a minimum of human input.

Abstract: A system for meta-indexing, search, compliance, and test framework for software development is provided, comprising an indexing service configured to create a dataset by processing and indexing source code of a project provided by a developer, perform a code audit on the indexed source code, store results from the code audit in the dataset, gather additional information relating to the provided project, store the additional information in the dataset, and store the dataset into memory; and a monitoring service configured to continuously monitor the project for at least source code changes and make changes to the dataset as needed.

Abstract: A system for regulated message routing and global policy enforcement. The transmission of data across a network is bound by policies administered by individuals, organizations, and governments. The system continuously tracks current world government regulations, is easily programmed to incorporate organization best practices and policies, and will automatically handle network traffic routing such that all regulations are fulfilled at all stages of transmission and compliance is recorded for possible later forensic or regulatory analysis.

Abstract: A system and method for the prevention, mitigation, and detection of cyberattack attacks on computer networks by identifying weaknesses in directory access object allowances and providing professionals with centralized graph-centric tools to maintain and observe key security and performance insights into their security posture. The system uses an interrogation agent to collect Active Directory configuration parameters and activity information about a forest and the devices operating within. Cyber-physical graphs and histograms using persisted time-series data provides critical information, patterns, and alerts about configurations, attack vectors, and vulnerabilities which enable information technology and cybersecurity professionals greater leverage and control over their infrastructure.

Abstract: A system and method for the secure and private demonstration of cloud-based cyber-security tools. Using an advanced sandboxing design patterns, isolated instances of virtual networks allow a potential client to compare their existing cyber defense tools against a set of cloud-based tools. Capitalizing on non-persistent and secure sandboxes allow the invention to demonstrate fully functional and devastating cyber-attacks while guaranteeing strict privacy and security to both existing customers and potential ones. Additionally, instantiating separate sandboxed observed systems in a single multi-tenant infrastructure provide each customer with the ability to rapidly create actual representations of their enterprise environment offering the most realistic and accurate demonstration and comparison between products.

Abstract: A system and method for the contextualization and management of collaborative databases in an adversarial information environment. The system and method feature the ability to scan for, ingest and process, and then use relational, wide column, and graph stores for capturing entity data, their relationships, and actions associated with them. Furthermore, meta-data is gathered and linked to the ingested data, which provides a broader contextual view of the environment leading up to and during an event of interest. The gathered data and meta-data is used to manage the reputation of the contributing data sources. The system links each successive data set, algorithm, or meta-data which might pertain to its unique identification and to its ultimate reputation, utility, or fitness for purpose.

Abstract: A system and method for creation and expansion of high quality data set collections for training of machine learning algorithms via crowdsourced curation that utilizes a data marketplace which incentivizes data gatherers, publishers, and users to contribute to the creation of a vast resource of reliable data set collections. Data is automatically ingested from disparate sources and autonomously checked for data quality, provenance, and cyber-risks and subsequently given a reputation score. Data stewards curate a queue of low scoring real data as well as synthetically generated data. All reputable data is stored for user consumption and further iterative data generation.

Abstract: A system for mitigation of cyberattacks employing an advanced cyber decision platform comprising a time series data store, a directed computational graph module, an action outcome simulation module, and observation and state estimation module, wherein the state of a network is monitored and used to produce a cyber-physical graph representing network resources, simulated network events are produced and monitored, and the network events and their effects are analyzed to produce security recommendations.

Abstract: A system and method for the prioritization and dynamic presentation of digital content. Application-specific and trained machine learning models recognize situational events via active and passive monitoring, triggering specialized load-balancing of critical network data as well as dynamically optimizing graphical user interfaces (GUI). GUI optimization comprises changing the layout composition; omitting non-critical information or changing the color, transparency, size, or other properties of the GUI elements. Furthermore, the system may activate electronic devices designed to alert users to recognize identified events.

Abstract: A system and method for the detection and mitigation of Kerberos golden ticket, silver ticket, and related identity-based cyberattacks by passively monitoring and analyzing Kerberos and authentication operations within the network. The system and method provide real-time detections of identity attacks using time-series data and data pipelines, and by transforming the stateless Kerberos protocol into stateful protocol. A packet capturing agent is deployed on the network where captured time-series Kerberos and related event and log information is processed in distributed computational graph (DCG) stages where declarative rules determine if an attack is being carried out and what type of attack it is.

Abstract: A system and method for event-based modeling and model refinement for natural catastrophe related risks, including but not limited to fires, floods, earthquakes, and hurricanes/tornados. The system and method feature simultaneous simulation of a plurality of industry models using a variety of risk information, including but not limited to real-time data, recent and historical event data, hypothetical data, and crowd-sourced data. The system and method use a variety of data sources in conjunction with machine learning to continuously and in real-time update and tune the simulated models performance and sensitivity to provide useful risk assessment and risk management data. Based on these model assessments, the system can produce notifications that can be made to enable automated and human actions.

Abstract: A system for cybersecurity rating using active and passive external reconnaissance, that uses a web crawler that sends message prompts to external hosts and receives responses from external hosts, a time-series data store that produces time-series data from the message responses, and a directed computational graph module that analyzes the time-series data to produce a weighted score representing the overall cybersecurity state of an organization.

Abstract: A highly scalable distributed connection interface for data capture from multiple network service sources, comprising a connector module wherein, the connector module retrieves a plurality of business related data from a plurality of network data sources; employs a plurality of application programming interface routines to communicate with the plurality of business related data sources; accepts a plurality of analysis parameters and control commands directly from human interface devices or from one or more command and control storage devices; and specifies the action or actions to be taken on the retrieved business data.

Abstract: A system for contextual data collection and extraction is provided, comprising an extraction engine configured to receive context from a user for desired information to extract, connect to a data source providing a richly formatted dataset, retrieve the richly formatted dataset, process the richly formatted dataset and extract information from a plurality of linguistic modalities within the richly formatted, and transform the extracted data into a extracted dataset; and a knowledge base construction service configured to retrieve the extracted dataset, create a knowledge base for storing the extracted dataset, and store the knowledge base in a data store.