THE CHALLENGE: Creating an Efficient Security Clearance Process and Ending the Backlog
The security clearance backlog peaked at 725,000 open investigations in 2018, with some Americans waiting more than 500 days just to start their first day at work. In 2018, the Federal Government hired 2,500 additional investigators to address the backlog.
Proposed legislation calls for reducing this backlog to 200,000 by the end of 2020, andreducing the time required to issue a secret level to 30 days or fewer and top secret level to 90 days.
The legislation establishes the “clearance in person” concept, which enables clearances to follow employees who change agencies, within 2 weeks or fewer. Continuous evaluation is another key component, moving from the existing periodic reviews, to reviewing on a dynamic and ongoing basis.
Leveraging technology to assess these goals is critical. But with more than 2.5 quintillion bytes of data added to the web every day, analysts are challenged to access, evaluate, and prioritize the open-sourced and publicly available information on the Internet.
Open Source Intelligence (OS-INT)
is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk.
OS-INT scours publicly available data across the entire Internet, correlating names entered into the system with content related to 20 different risk factors, known as Behavioral Affinity Models (BAMs), and cross-referenced with more than 1 million queries into Lumina’s proprietary databases of risk.
Searches provide near-instant results, delivering meaningful, actionable intelligence to identify and prevent risk.
Internet Intelligence’s (NET-INT)
proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.
The system also searches known IP addresses, producing all URLs accessed by the address. Results are nearly instantaneous, and accessed with just three clicks on the computer’s mouse.
The platform collects and stores more than 1 million interactions every day and since its inception has recorded more than 623,000 IP addresses engaged with threat-related risk topics.
Human Intelligence’s (HUM-INT) is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time.
THE SOLUTION: Expediting Online and Unstructured Data Analysis through AI-Driven Intelligence
Radiance is designed to overcome the challenges of massive unstructured data ingestion, evaluation, and prioritization. This provides a rapidly deployable, scalable and user-friendly solution for the security clearance process.
OS-INT’s security clearance bundle is specifically configured against selectors for the Adjudicative Guidelines’ Security Executive Agent Directives (SEADs). This bundle includes more than 16,220 terms related to the guidelines. OS-INT performs nearly 325,000 searches across the entire web, correlating names with these terms and cross-referencing over 1 million queries into Lumina’s proprietary databases of risk.associated behavioral affinities related to risk. A manual web search of this magnitude would take more than 2 ½ years for one person to complete.
OS-INT pulls all applicable content into a comprehensive report. The results are prioritized, making it easy to further analyze the findings and determine potential risk. The system allows for continuous monitoring and evaluation, mapping previous results against results from more recent queries. Unlike social media monitoring, OS-INT is not reliant on a single platform or social media API, allowing for continuous ingestion of all open source data.
NET-INT’s massive system of data ingestion has the capability to catalog, index and redeploy Internet content related to risk dimensions associated with SEADs. The system captures an IP addresses’ pattern of life data, prioritizing anomalous behavior. NET-INT also screens IP addresses associated with an entity or person of interest against all IP addresses displaying anomalous behavior collected over the system’s lifespan. NET-INT’s continuous monitoring of a POI’s Internet research behavior helps predict emergent behavior indicative of a violation of the guidelines.
HUM-INT’s S4 app can be configured as a workplace tool, allowing employees to submit information related to potential risk behaviors exhibited by co-workers. A centralized management portal allows clients to access real-time threats to geo-fenced facility locations.
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Lumina was founded on the idea that technology is a force for good. We optimized our artificial intelligence capabilities to help keep people and places safe and secure. Protecting what matters most is more than what we do. It’s who we are.
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