Abstract: A system and method for movement and manipulation of secure data. The system and method combine the ability to restrict and control the transport and processing of data based on specified directives and provide rich auditable provenance to support evidentiary requirements. The system may additionally automatically optimize data routes and specify processing hardware based on data residency, sovereignty, or localization restrictions, constraints, or economic considerations, furthermore, protect sensitive data from compromise by generating and integrating digital tokens and employing observability sensors, processing flows, and analytics on devices in the data transport, storage and compute chain to provide a secure method of data transport and utilization within applications.

Abstract: The provided system and methods describe a Multi-factor Authentication (MFA) kiosk that utilizes various sensors to capture biometric, behavioral, and physiological data for authentication. The kiosk includes a user interface, a set of sensors, and services such as kiosk management, rules configuration, sensor management, and an authentication service. The sensors, both integrated and external, gather diverse data, including facial recognition, fingerprint scans, voice recognition, gait analysis, and more, constructing a physical profile for authentication. The system incorporates a rules service for configuring authentication policies and a sensor management service to optimize sensor performance. Authentication service uses a scoring model, potentially a deep learning algorithm like an autoencoder, to generate an authentication score based on inputs from sensors, rules, and previous attempts. Security measures include encryption, isolation of components, and compliance with data protection regulations.

Abstract: A system and method for gathering and analyzing the value chain relationships between legal entities, people, systems, and real and intangible assets using a temporospatial knowledge graph of the integrated value chain. The system provides the ability to layer private data from paid vendors with end-user owned and public records data to enable more comprehensive, contextualized and complete representations of the underlying value chain. Data analysis techniques, such as deep learning and machine learning, are performed on the knowledge graph and its underlying data set, in conjunction with simulation and modeling, to analyze the value chain, including generation of a risk profile for an entity's value chain and potential optimization options to remediate the identified risks.

Abstract: A system and method for self-adjusting cybersecurity analysis with network mapping, wherein a reconnaissance engine gathers data about a client's computer network from the client, from devices and systems on the client's network, and from the Internet regarding various aspects of cybersecurity. Each of these aspects is evaluated independently, weighted, and cross-referenced to generate a cybersecurity score by aggregating individual vulnerability and risk factors together to provide a comprehensive characterization of cybersecurity risk using a transparent and traceable methodology. The scoring system itself can be used as a state machine with the cybersecurity score acting as a feedback mechanism, in which a cybersecurity score can be set at a level appropriate for a given organization, and data from clients or groups of clients with more extensive reporting can be used to supplement data for clients or groups of clients with less extensive reporting to enhance cybersecurity analysis and scoring.

Abstract: A system and method for analyzing integrated operational technology and information technology systems with sufficient granularity to predict key elements of their composite behavior. The system and method involve creating high-fidelity models of the operational technology and information technology systems using one or more cyber-physical graphs, performing parametric analyses of the models to identify key components, scaling the parametric analyses of the models to analyze the key components at a greater level of granularity, and iteratively improving the models via ongoing search and testing against observed data from the real-world systems.

Abstract: A system and method for comprehensive cybersecurity threat assessment of software applications based on the totality of vulnerabilities from all levels of the software supply chain. The system and method comprising analyzing the code and/or operation of a software application to determine components comprising the software, identifying the source of such components, determining vulnerabilities associated with those components, compiling a list of such components, creating a directed graph of relationships between the components and their sources, and evaluating the overall threat associated with the software application based its software supply chain vulnerabilities.

Abstract: A system and method for trigger-based scanning of cyber-physical assets, including a distributed operating system, parameter evaluation engine, at least one cyber-physical asset, at least one crypt-ledger, a network, and a scanner that detects trigger conditions and events and performs scans of cyber-physical assets based on the trigger and any relevant stored scan rules before storing scan results as time-series data.

Abstract: A system and method for fingerprint-based network mapping of cyber-physical assets, including a distributed operating system, parameter evaluation engine, at least one cyber-physical asset, at least one crypt-ledger, a network, and a scanner that retrieves stored fingerprint records and performs scans of cyber-physical assets to compare against corresponding fingerprints and update a cyber-physical graph based on the success or failure of fingerprint matching.

Abstract: Management and tracking of collaborative projects using a logging service configured to track contributions of a plurality of participants of a monitored project and log the contributions in a graph and timeseries-based contributions dataset. A knowledge graph generator generates a timeseries-based knowledge graph from gathered information. An automated planning service determines an associated value of the monitored project and a remuneration service analyzes the contributions dataset to determine appropriate apportionment of remuneration.

Abstract: A system for detecting and mitigating attacks using forged authentication objects within a domain is provided, comprising an authentication object inspector configured to observe a new authentication object generated by an identity provider, and retrieve the new authentication object; and a hashing engine configured to retrieve the new authentication object from the authentication object inspector, calculate a cryptographic hash for the new authentication object, and store the cryptographic hash for the new authentication object in a data store; wherein subsequent access requests accompanied by authentication objects are validated by comparing hashes for each authentication object to previous generated hashes.

Abstract: Improving a distributed model with distributed data receives an instance of the distributed model from the network-connected computing system, create a cleansed dataset from data stored in the memory with at least biases within the data stored in memory corrected, train the instance of the distributed model with the cleansed dataset, and generate an update report based at least in part by updates to the instance of the distributed model.

Abstract: A system for repeatable and flexible predictive analysis of very large data sets using a distributed computational graph using a domain specific language for pipeline and resource declaration has been developed. Data receipt software receives data from one or more sources. In a declared data pathway, data formalization software formats input data for storage, enrichment, or continued processing. An event analysis server inspects stored data for trends, situations, or knowledge. Aggregated data is passed to event message store and data stream handler software. Transformation pipeline software stores, triggers, executes and monitors declared transformation steps and pipelines to manipulate and act on bulk data and data streams, provides results and enables dynamic model and routine re-training and learning.

Abstract: Detection and mitigation of data source compromises in an adversarial information environment, featuring 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. Metadata 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. Data quality analysis is conducted as data is ingested in order to identify if a data source may be compromised. The results are used to manage the reputation of the contributing data sources.

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 holistic network cybersecurity evaluation and risk rating that takes into account the operation of the entire target network environment comprising hardware, software, operating systems, and network connections. Not only are the hardware, software, operating system, and network evaluated separately for cybersecurity concerns, their interaction and operation as a whole are also evaluated and scored. The results of such analyses may be used, for example, by underwriters of cybersecurity insurance policies to determine policy terms and rates.

Abstract: A system and methods for authentication attack detection with embedded authentication and delegation is provided, comprising an authentication object inspector configured to observe a new authentication object generated by an identity provider, and retrieve the new authentication object, wherein subsequent access requests accompanied by authentication objects are validated by comparing identifiers for each authentication object to previous identifiers.

Abstract: Automated analysis of legal documents within and across different fields is disclosed. An extraction processor identifies and extracts knowledge from data contained in documents and transforms it into a common data form. An analysis processor develops local and global knowledge graphs containing the key entities, relationships and concepts encoded in the text.

Abstract: A semantic search system integrates with an AI platform to provide advanced search capabilities by leveraging automatically generated ontologies and knowledge graphs. The system employs natural language processing, machine learning, and large language models to create, update, and align ontologies from diverse data sources. It supports context-aware query interpretation, personalized results, and complex reasoning by incorporating user context, feedback, and domain knowledge. The system optimizes search performance and efficiency through indexing techniques, distributed computing, and continuous learning. With a modular architecture and scalable infrastructure, the semantic search system enables users to retrieve relevant, meaningful, and context-specific information from vast amounts of structured and unstructured data.

Abstract: The Generative AI Content Verification Exchange systematically registers and stores content generated by AI and real people alike. Upon submission, the system categorizes content into distinct groups, then deconstructs it into multiple segments using various methods. Each segment is assigned a unique hash value, termed a “part identifier,” ensuring individualized identification. This registration process, combining grouping, segmentation, and hashing, enhances content traceability and retrieval. The resulting database not only organizes generated content by groups but also allows for efficient and secure referencing of specific content segments. A content similarity score may be generated by comparing hash values against a large corpus of registered content. The similarity score is indicative of the likelihood, or not, of an input content being in part registered content.

Abstract: A system and methods for detecting and mitigating authentication object forgery and manipulation attacks against services is provided, comprising a policy manager configured to observe a new authentication object generated by an identity provider, and retrieve the new authentication object; and a hashing engine configured to create a security cookie for each valid authentication session; wherein subsequent access requests accompanied by authentication objects are validated by checking for a valid security cookie.