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Lumina Secures $5 Million In Capital Raise

Tampa, Florida, July 10, 2019 – Lumina, a predictive analytics company whose AI-driven Radiance platform helps keep people and places safe and secure through active and early detection of potential risk-related behaviors, announced today that it has raised an additional $5 million in funding. This round, which included investment funds and individual investors, follows an earlier capital raise of approximately $8.5 million in August 2017.

“We are extremely pleased with our industry-leading Radiance platform, and the market’s positive response to it. We will use this funding to accelerate growth through further investment in sales and marketing,” said Allan Martin, the CEO and Co-Founder of Lumina. “Our confidence in Radiance and our growth trajectory is reflected in the fact that our latest round of funding came almost entirely from existing investors and team members.”

Lumina’s investment in sales and marketing efforts will focus on key industry verticals including education, government, finance and transportation industries.  As part of its education outreach efforts, the company plans to announce a major school initiative in the coming weeks, leveraging its Radiance platform to help keep students and campuses safe across the country. 

In addition to the sales and marketing efforts, the company is planning to expand office space at its Tampa headquarters and grow its team both there and in its Washington, DC office.  Lumina is currently recruiting for two positions, a customer success analyst and a research analyst, both based in Tampa.

About Lumina 

Lumina is a predictive analytics company founded on the idea that technology is a force for good.  The company’s optimized artificial intelligence capabilities help keep people and places safe and secure through active and early detection of high-risk behavior.  Lumina’s Radiance platform uses proprietary, deep web listening algorithms to uncover risk, provide timely, actionable information, and help prevent catastrophic loss.  Lumina is committed to protecting what matters most, and its Radiance platform is designed to help solve the world’s most challenging problems. 

For more information contact Jill Kermes at 202-957-0715 or jill.kermes@luminaanalytics.com

Waiting in Line at Airport Security This Summer?        AI Could Make Screening More Effective and Efficient.

Waiting in Line at Airport Security This Summer? AI Could Make Screening More Effective and Efficient.

With summer air travel expected to hit a new record between June 1 and August 31 this year, travelers should expect to see longer lines at security checkpoints.

To address these challenges, the Transportation Security Administration (TSA) is hiring an additional 2,000 employees and employing new technologies like automated screening lanes and computed tomography

360-degree Security View

As these changes move forward, implementing artificial intelligence and machine learning technologies can also help reduce wait times and increase the effectiveness of security screening.

In fact, experts suggest that AI and big data analytics can move the screening process from the current single point in time analysis to a 360-degree view of a person’s behavior over a broader time range by linking data sets to identify risky behavior even before a potential bad actor gets to the airport.

This thinking is in line with the recommendations from the White House’s 2018 National Strategy for Aviation Security (NSAS).  NSAS highlighted the importance of strengthening aviation domain awareness through integration of open-source data into existing air surveillance and law enforcement intelligence, collection and analysis of advanced and anticipatory information, and layered and risk-based security measures.

The International Air Transport Association is also working on a program to facilitate the exchange of critical security data.  According to the Director General and CEO Alexandre de Juniac, “This is similar to the way that our safety colleagues work with data to do predictive risk analysis. This tool will provide early detection of changes to security environments in different parts of the world, so we can effectively deal with emerging threats and the impacts of changes to security procedures.”

The Role of AI

AI-driven technologies, like Lumina’s Radiance platform are another facet to the solutions being implemented in the U.S. and globally.

Radiance has the ability to comprehensively mine unstructured data sources, whether across the open web, or among disparate, legacy data systems. It ingests, integrates and analyzes those data sets, searching against more than 6,500 terms related to aviation security.

The platform conducts nearly 135,000 searches across all publicly-available data on the web, correlating names with these associated risk behaviors and cross-referencing over 1 million queries into Lumina’s proprietary databases of risk. 

Then add to this open source search internal data sets such as passenger bookings and travel history – or in the case of insider-threats, employee-related data – and airline and airport security experts have an important tool to help predict and prevent threats.

Looking ahead

To be sure, integrating AI driven technologies like Radiance are not a thing of the far of future. Research shows that 66% of airlines and 79% of airports plan to implement these capabilities across a wide variety of use cases by 2021. In fact, AI in aviation was valued at $152 million in 2018 and expected to increase to $2.2 billion by 2025.  And, passengers are ready for these technologies to help expedite their time at  airport security and make their travel more seamless. An online poll of UK passengers found that 68 percent of respondents would welcome AI at airports, and another study found 65 percent would share additional personal information to speed up processing at the airport.

Learn more about Radiance’s capabilities for the airline industry here.

Lumina’s AI-Driven Radiance Technology Provides Solution for Modernizing Security Clearance Process

Lumina’s AI-Driven Radiance Technology Provides Solution for Modernizing Security Clearance Process

~~Artificial Intelligence, machine learning, and data analysis can speed the investigatory process, allow for continuous evaluation and reduce existing backlog~~

Lumina’s AI-driven Radiance platform, which uses proprietary, deep-web listening algorithms to uncover risk, provides one solution for modernizing the security clearance process and reducing the existing backlog.  The company has configured Radiance’s exclusive Behavioral Risk Profiles (BRPs) against the 13 adjudicative guidelines criteria, allowing for earlier risk determination and prioritization of investigatory resources.

“As many security experts have pointed out, our current system is not only time consuming and slow, it is also out of sync with how people live in the 21st century.  To be sure, 50 years ago, interviews with neighbors, colleagues and other associates could help provide meaningful insights into our lives and habits,” said Allan Martin, CEO of Lumina. “Today, we share these very same insights willingly, publicly and knowingly across a variety of online platforms.  But, with more than 2.5 quintillion bytes of data created on the Internet every day, only a platform with Radiance’s capabilities can quickly and thoroughly find and prioritize relevant and actionable content.”

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.  The technology is comprised of three modules, for edge-to-edge risk detection.

Radiance Open Source Intelligence (OS-INT)

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 its exclusive BRPs, and cross-referenced with more than one million queries into Lumina’s proprietary databases of risk.  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.

OS-INT’s security clearance bundle includes more than 16,220 terms related to the 13 adjudicative guidelines. OS-INT performs nearly 325,000 searches across the entire web, correlating names with associated risk behaviors. Similar results would take an individual running a manual web query more than 18 years to read and analyze.

OS-INT completes searches in an average of 4-5 minutes, providing prioritized, high resolution, and actionable results. The system allows for continuous monitoring and evaluation, mapping previous results against results from more recent queries.

The configuration of BRPs only collects publicly available information, within the scope of the investigation and does not use account creation or digital interaction with POIs. As a result, the collection of information adheres to Security Executive Agent Directive 5 guidelines.

Radiance Internet Intelligence’s (NET-INT) 

NET-INT’s proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.  Its massive system of data ingestion has the capability to catalogue, 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.

Radiance Human Intelligence (HUM-INT) 

HUM-INT is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. 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.

View Lumina’s blog and white paper on security clearance at www.luminaanalytics.com

About Lumina 
Lumina is a predictive analytics company founded on the idea that technology is a force for good.  The company’s optimized artificial intelligence capabilities help keep people and places safe and secure through active and early detection of high-risk behavior.  Lumina’s Radiance platform uses proprietary, deep web listening algorithms to uncover risk, provide timely, actionable information, and help prevent catastrophic loss.  Lumina is committed to protecting what matters most, and its Radiance platform is designed to help solve the world’s most challenging problems. 

For more information contact Jill Kermes at 202-957-0715 or jill.kermes@luminaanalytics.com

Modernizing the Security Clearance Process through Machine Learning and AI

Modernizing the Security Clearance Process through Machine Learning and AI

Late last month, President Donald Trump signed an Executive Order transferring responsibility for security clearance screening from the Office of Management and Budget to the Defense Department. 

The Administration had previously called the clearance process a target for government reform, noting in 2018 that “background investigations are critical to enabling national security missions and ensuring public trust in the workforce across the Government.”

The Administration’s efforts are part of an ongoing focus on reforming the clearance process, and reducing the existing backlog. 

That is because the current 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.  As part of these efforts, the Federal Government hired 2,500 additional investigators in 2018 to address the backlog.


Re-thinking Security Clearance

In addition to the Executive Order, in February, Senator Mark Warner (D-VA), reintroduced The Modernizing the Trusted Workforce for the 21st Century Act (S.314).

The legislation calls for a major overhaul of the system.

It also sets targets to reduce the backlog to 200,000 by the end of 2020, and shorten the time required to issue a secret level clearance to 30 days or fewer and top secret level clearance to 90 days. 

The legislation also establishes the “clearance in person” or “one-clearance” concept. This would enable – within two weeks or fewer – clearances to follow employees who change agencies.

Similarly, the legislation calls for continuous evaluation. It would move from the existing periodic reviews, to dynamic and ongoing reviews in the future.

In many ways, these recommendations represent a complete re-thinking of the security clearance process.

As Senator Warner notes in his legislation, technologies will play a critical role in preventing, detecting and monitoring threats. He also notes the role data integration and analytics can play in expediting or focusing
re-investigations through delta reporting and continuous evaluation. 


An Antiquated System

As many security experts have pointed out, the current system is not only time consuming and slow, it is also out of sync with how people live today.  For example, as it currently works, a field investigator is assigned to confirm information from the applicant’s form, and to make sure that individual does not represent a threat to national security.

These determinations are based on the 13 adjudicative guideline criteria, which among others include, financial considerations, foreign preference and influence, alcohol consumption, and drug involvement.

To be sure, 50 years ago, interviews with neighbors, colleagues and other associates could help provide meaningful insights into our lives and habits.  But today, we share these very same insights publicly, willingly and knowingly across a variety of online platforms, making the Internet a useful, but largely untapped resource.


Challenges to Reform

In fact, according to Gary Reid, Director of Defense Intelligence patterns of life, including scans of public-facing social media could one day be considered.

A significant challenge is the volume of data on the web. 

With more than 2.5 quintillion bytes of data created on the Internet every day, searching for relevant content can be like looking for the proverbial needle in a haystack.


The role of AI and Machine Learning

One way to solve for this is through machine learning and AI capabilities – a super-charged web search, allowing for all that publicly available, open-source data to be searched for risk behaviors – in this case, associated with the 13 established adjudicative guidelines.

But rather than having to weed through thousands of pages of search results, these technologies can quickly synthesize the data and cull out high priority risks associated with guideline selectors. 

As a result, analysts receive the most critical data first, helping streamline their search process and gather the most relevant information.


Call it the Radiance Solution
              

Lumina’s AI-powered Radiance technology is specifically 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. 

The technology is comprised of three modules, for edge-to-edge risk detection.


Radiance Open Source Intelligence (OS-INT)

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 its exclusive behavioral risk profiles (BRPS). It then cross-references that information with more than one million queries into Lumina’s proprietary databases of risk.  And, 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.

OS-INT’s security clearance bundle includes more than 16,220 terms related to the adjudicative guidelines. OS-INT performs nearly 325,000 searches across the entire web. It then correlates names with associated risk behaviors. Similar results would take an individual running a manual web query more than 18 years to read and analyze.

OS-INT completes searches in an average of 4-5 minutes, providing prioritized, high resolution, and actionable results. In addition, the system allows for continuous monitoring and evaluation, mapping previous results against results from more recent queries.

The configuration of BRPs only collects publicly available information, within the scope of the investigation. And, it does not use account creation or digital interaction with a person of interest. As a result, the collection of information adheres to Security Executive Agent Directive 5 guidelines.


Radiance Internet Intelligence (NET-INT)

NET-INT’s proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.  In addition, its massive system of data ingestion has the capability to catalogue, index and redeploy Internet content related associated with the adjudicative guidelines.

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 then helps predict emergent behavior indicative of a violation of the guidelines.


Radiance Human Intelligence (HUM-INT)

HUM-INT is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. The 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.


The Way Forward

As Washington continues its efforts to reduce the security backlog, and modernize the existing process, machine learning and artificial intelligence will play an important role.

Senator Warner recently said, “There is much more we can do to reform decades-old policies and processes to reflect today’s threat environment, adapt to the dynamic of a modern mobile workforce, and capitalize on opportunities offered by modern information technology.”

Lumina Expands its Predictive Analytics and Risk Sensing Capabilities with  Radiance Launch

Lumina Expands its Predictive Analytics and Risk Sensing Capabilities with Radiance Launch

~~AI-powered technology helps organizations anticipate, understand,
manage and mitigate risk~~

Lumina announced today the launch of its new Radiance platform, which uses proprietary, deep-web listening algorithms to uncover risk, provide timely and actionable information and help prevent catastrophic loss. The Radiance platform brings the power of Open-Source Intelligence (OS-INT), Internet Intelligence (NET-INT) and the See Something Say Something app (HUM-INT) for edge-to-edge risk detection.

“The power of Radiance is two-fold – its ability to ingest massive amounts of unstructured, open source data and its real-time ability to analyze that information to predict and prevent organizational risks and threats,” said Allan Martin, CEO of Lumina. “Radiance is designed to help keep people and places safe and secure, and this AI-driven solution will immediately transform how organizations think about risk management and risk mitigation.”

Radiance’s purpose-built, best-in-class algorithms overcome the challenges of massive unstructured data ingestion and prioritization.  Radiance scours the web, prioritizing current behaviors to predict future action. This is an advantage over other technologies, which focus only on historical behavior, which can lead to bias in the results. Additionally, clients can integrate their own structured and unstructured data into Radiance, allowing for correlation of internal databases against open source, publicly available data.

Radiance is a Software-as-a-Service (Saas) platform that includes managed service capabilities. It is rapidly deployable, scalable, highly configurable and user-friendly, and is comprised of the following components:

  • Radiance Open Source Intelligence (OS-INT) is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk. Names entered into OS-INT are correlated with content related to 20 different risk factors, known as Behavioral Risk Profiles (BRPs) and cross-referenced with more than 1 million queries into Lumina’s proprietary databases of risk, known as ecosystems. One search across all BRPs equates to more than 465,000 deep web searches.  OS-INT delivers prioritized results in about 5 minutes. A manual search of this magnitude would take a person more than 3 1/2 years to complete.
  • Radiance Internet Intelligence (NET-INT) detects means, motivation and target for attack planning. Its proprietary algorithms continuously identify, monitor, capture and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions. 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.
  • Radiance Human Intelligence (HUM-INT) is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. A centralized management portal allows clients to access real-time threats to geo-fenced locations.

“We constantly hear people say, ‘We have so much data, but what can we do with it?’  Radiance solves that problem by ingesting, integrating, correlating and analyzing disparate datasets.  It takes data never designed to identify risk, and prioritizes it – giving our clients an unbiased and fully auditable understanding of human behavior and associated threats,” said Dr. Morten Middelfart, Chief Data Scientist at Lumina.

He added that Radiance’s BRPs solve for the “data noise” obstacle associated with other OS-INT SaaS solutions.  In addition, Radiance drastically outperform existing Natural Language Processing (NLP) approaches to identify names of persons or entities in unstructured data. Radiance performed at a 93.1 percent accuracy level on unstructured, improperly cased documents such as HTML, JSON or computer code and other so-called messy documents compared to 0 percent for Stanford Named Entity Recognizer (NER) and other popular open-source NLP software. Additionally, the BRPs generated with Lumina’s machine learning are “human readable,” making them fully auditable as well.

About Lumina

Lumina is a predictive analytics company founded on the idea that technology is a force for good.  The company’s optimized artificial intelligence capabilities help keep people and places safe and secure through active and early detection of high-risk behavior.  Lumina’s Radiance platform uses proprietary, deep web listening algorithms to uncover risk, provide timely, actionable information, and help prevent catastrophic loss.  Lumina is committed to protecting what matters most, and its Radiance platform is designed to help solve the world’s most challenging problems.

For more information contact Jill Kermes at 202-957-0715 or jill.kermes@luminaanalytics.com