Securboration, Inc.

Securboration Awarded an Air Force Contract to Provide the Private Assistant for Individual Relegation

Securboration has been awarded an Air Force contract to provide the Private Assistant for Individual Relegation (PAIR). It will facilitate proactive human-machine collaboration for intelligence analysis tasks such as intelligent data collection, content discovery, task recognition, analytical workflow and predictive analysis. Another objective is to research systematic approaches to credibility analyses that the agent can learn, developing a library of general credibility analysis models providing analysts a way to better manage the vast quantities of multi-sourced intelligence data.

Securboration Awarded Air Force Contract to Help Increase Operator Situational Awareness and Decision Speeds for Controlling Complex, Highly Dynamic Networks

Securboration has been awarded an Air Force contract to develop information technology which fuses distributed sensing and human perception to increase operator situational awareness and decision speeds for controlling complex, highly dynamic networks. Securboration will be developing the Joint Collaborative Augmentation for Sense-making Environment (JCAUSE). JCAUSE will combine advances in several fields of knowledge including sense making, cognitive science, machine learning, cyber security and visualization with expertise from the command and control realm.

Securboration Awarded Contract for Context-Driven Aeronautical Information Delivery Service

Securboration has been awarded an Air Force contract from the Air Force Research Lab to develop a Context-Driven Aeronautical Information Delivery (CAID) Service that can deliver relevant aeronautical information to pilot and air traffic controller workstations based on AIXM-based flight plans. This service will ingest aeronautical information from authoritative sources, prioritize the information using business rules, and deliver the information in a standard format suitable for a web portal or an electronic flight bag.

Securboration Awarded Air Force Contract for Mission Awareness for Mission Assurance

Securboration has been awarded an Air Force contract for a new consolidated program called “Mission Awareness for Mission Assurance” (MAMA). The goal of MAMA is to enhance cyber situational awareness by the automated assessment of mission execution through the analysis of network traffic flows. This resultant capability is an enabler to achieving mission assurance by allowing prioritization of mission essential functions, mapping of critical cyber assets, vulnerability assessment of mission essential functions and mitigation of vulnerabilities and risks. Securboration aims to accomplish the goals with the Semantic Templates for Assured Missions in a Proxy-Enabled Dissemination Environment (STAMPEDE) system.

Securboration Awarded Contract for Semantic Services for Enterprise Analytics

Securboration has been awarded an Air Froce contract from the Air Force Research Lab to develop Semantic Services for Enterprise Analytics (SSEA). This set of services will implement text analytics and develop knowledge graphs to link disparate data resulting in automated and expedited processing of both formal planning, programming, and acquisition information source, and informal artifacts to help identify and synchronize DoD R&E planning activities.

Securboration Awarded Air Force Contract for Risk Calculation System for Sensitive Data Disclosure

Securboration has been awarded a contract by the Air Force Research Laboratory (AFRL) to develop the RIsk QUantification and ESTimation (RIQUEST) system to extend the state-of-the art in automatic risk disclosure quantification by applying probabilistic inference to sets of sensitive information.  This effort follows a successful proof-of-concept where RIQUEST was applied to a novel use-case that highlighted the system’s potential. Similar to the previous work, this effort will focus on three areas that are essential for auto-risk disclosure: Text Analytics, Probabilistic Inference; and Causal Analysis. By making technological advancements in each, Securboration will create a unique and innovative system that performs auto-risk disclosure by ingesting data from multiple heterogeneous data streams, extracting information pertinent to the a piece of sensitive information from those streams, quantifying impacts that the discovered information have on the overall security posture of the sensitive information, and providing complete traceability and transparency into the disclosure risk causes for sensitive information. These capabilities will be developed as a robust, potent and modular set of auto-risk services that can seamlessly integrate with a variety of systems with the eventual goal of transitioning to operational systems.

Securboration Awarded Army Contract for Automatic Redacting Capability

Securboration has been awarded a US Army contract for automatic redaction of information based on each requestor’s allowed access level. Existing Army technologies as well as open source alternatives that are interchangeable will be used to provide a computing environment that allows Warfighters access to data that would normally be inaccessible due to the lack of identity and attribute awareness in these systems. Currently, analysts are unable to keep pace and products are incorrectly marked or over classified. The DOD needs the ability to accelerate intelligence dissemination across security enclaves to support the tempo of modern warfare. Dynamic data redaction and filtering of granular intelligence data based on user attributes is required. The objective is to develop a standards-based Identity and Access Management (IdAM) and Attribute-Based Access Control (ABAC) computing framework that is capable of fined-grained access control of metadata queries and product retrievals from the current system.

Securboration Wins Navy Contract for Course of Action Recommender

Securboration has been awarded a contract from the Navy to build a general framework for a course of action (COA) recommender. Securboration will develop COA Recommendation Services (COARS), which is a service-based implementation which fits well with the Navy’s modular approach to maturing leading edge research towards a deployable COA recommender. Securboration is teaming with Dartmouth College and their renowned computational modeling professor, Dr. Eugene Santos, to specifically address predictive capability for COA recommendations. We will extend Dr. Santos’ research in Bayesian Knowledge Bases (BKBs) by adding deep learning concepts to fuse knowledge fragments and derive complex emergent behavior that is missed with existing reasoning techniques and algorithms. This accounts for the intricacies and dynamics of the operational environment and overcomes the limitations of current COA recommender approaches that are based on simplistic assumptions regarding adversary objectives, limitations, and intent.

Securboration Wins Navy Contract for Electronic Warfare Scoring System

Securboration has been awarded a contract from the Navy to develop an automated information extraction and scoring system for Electronic Warfare (EW) systems. Securboration will develop the Maritime Electronic Warfare (MEW) Sustainment Information Card (MEWSIC) system to meet the requirements of this effort. Existing systems require manual research that is hampered by inaccurate information in inventory systems and/or by a partial or limited view of the inter-dependencies upon systems, components, and parts. Much of the necessary information is in textual resources and this effort aims to provide a cost effective and timely method to determine if the proper support solution is available to reduce repair time and maintain its equipment in an optimal operational readiness state. MEWSIC aims to provide this capability by exploiting both structured and unstructured data sources to gain a true picture of a system’s (e.g. ship) operational status and risk factors. The core technology behind MEWSIC is Securboration’s proven integration and text analytics pipeline, which includes distinct capabilities for Entity Extraction, Document Summarization, and Topic Identification and Ranking.

Air Force Awards Contract to Securboration to Enhance Analyst Capabilities

Securboration has been selected by the Air Force Research Laboratory (AFRL) to explore, systematically study and develop technology that enables computers to proactively support analyst activity. The goal is to provide a bidirectional human and information technology partnership where the computer learns, adapts and informs analysts based on their typical practices, situational context, and available data content. The system under development, referred to as the Adaptive Data Immersion Environment or ADIEN, combines machine learning, text analytics, and semantic search to learn and evolve user preferences based on individual usage patterns. Additionally, as new data products become available they will be automatically identified and seamlessly added into analyst’s workspace. ADIEN  is designed to act as a ‘buddy agent’ that not only stays one step ahead of the analyst but does so in an intelligent fashion.  In this capacity, ADIEN provides intelligent offloading to proactively provide assistance to the analyst while they are focused on another task; data immersion to provide the analyst with a wide view of the data landscape allowing them to navigate, test and evaluate hypothesis; continuity in order to maintain the analysis state, allowing analysts to take necessary breaks and seamlessly continue where they left off; and allows for collaboration across analyst networks. ADIEN combines machine learning, text analytics, and semantic search to not only learn and evolve preferences based on individual usage patterns, but also to identify related data relevant to what the analyst is working on and to proactively and seamlessly insert them into the analyst’s workspace. ADIEN’s capabilities include (1) letting the data speak for itself by guiding analysts to where the data convolves, but also highlighting ‘outliers’ of interest to the analyst; (2) continually adapting to and augmenting analyst’s workflow; (3) accommodating the analyst’s interrupt-driven environment and (4) subtly facilitating collaboration without mandating it.

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Securboration, Inc.