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The United States military could one day more quickly identify and assess the threat of objects in the sky, such as the Chinese balloon that was recently in the news or other unmanned aerial vehicles (UAVs), thanks to research being conducted at Missouri University of Science and Technology.
Dr. Sanjay Madria, Curators’ Distinguished Professor of computer science at Missouri S&T, has been awarded millions of dollars in federal grants in recent years to research this and other methods to keep members of the United States military safe and improve the country’s cybersecurity.
“I am working on a variety of cybersecurity projects to increase the security of different cloud and internet of things (IoT) applications in the battlefield, for transportation, and for the supply chain,” Madria says. “Some of the projects focus more on the U.S. armed forces, while others are broader projects with the federal government.”
Countering UAV swarms
With a $500,000 grant from the Army Research Office, Madria is looking for ways to counteract groups of unmanned aerial vehicles using machine learning.
“For this project, our goal is to have early detection of swarms of UAVs,” Madria says. “We are developing software that will use machine learning and other techniques to analyze different images of objects taken by aircraft, ground vehicles, or any other cameras.”
With this program, the military could more quickly determine the size and type of UAVs in the sky and distinguish them from similar objects, such as balloons, birds, or kites. The program will be tailored to detect potential swarms, or groups, of UAVs, that operate as one unit.
“Whatever the objects are, our machine learning will help distinguish UAVs from similar-looking distant objects so the military can then determine the appropriate course of action,” he says.
Madria is working with Dr. Maciej Zawodniok, an associate professor of electrical and computer engineering at S&T, to ensure the program can also be used to detect radio frequency and electromagnetic emissions, which could provide signs about what is lurking in the clouds above.
Concealing locations
Madria is also helping military groups maneuver on the battlefield without the aid of GPS with $215,000 from the U.S. Army Research Office. This project is expected to continue through March 2024.
Madria says the military has an urgent need to detect and track chemical, biological, radiological and nuclear defense (CBRN) materials being transported in combat zones without using GPS. Jamming of signals can make GPS unavailable, and those signals can be spoofed by the enemy to disorient forces. Other parties may also be able to track GPS signals using active sensors and radio communication between sensors.
“This adds another layer of security and is a big deal for the Army,” Madria says. “With the program, people will be able to take photos of landmarks and measure their exact locations. Other nodes can then approximate their locations with the new mobile anchor nodes and make secure connections.”
Securing information on the battlefield
In May 2022, Madria delivered software for a secure information-sharing platform to the Air Force Research Laboratory. The program, which was funded by a $500,000 grant, combined machine learning with a secure platform that allows members of the military to quickly share photos and highly accurate captions with authorized viewers.
The platform sets specific roles and missions for members of the military and can gauge who in the chain of command is most likely to need shared information. Photos can also be set by category based on what the machine learning platform determines they include.
“An important part of this program is that it allows users to quickly determine who they want to see the photos, as the photos are encrypted for specific users with their attribute-based keys,” Madria says. “Then, if their access needs to be revoked, specific photos can be re-encrypted with the touch of a button dynamically in the battlefield without affecting others.”
Madria says this technology will also help battlefield leaders more quickly understand events as they unfold and disseminate them to allow leaders to make more informed decisions securely. Its attribute-based security policy will also allow mission interests to be updated for personnel as battlefield situations change, ensuring the transmitted data is as up-to-date as possible.
Large, non-military projects
To go along with his projects for the U.S. military, Madria also has several grant projects in the works for other federal agencies.
A project that uses a blockchain as access control for information sharing has been funded at $125,000 annually for the past four years
“We are working to track the provenance of files as effectively as possible,” Madria says. “With the blockchain, we will see any time transmitted files are altered in any way. This could be for design and supply-chain purposes or for a variety of other documents in which one seemingly small change can make a significant difference for a project.”
With a $462,000 grant from the National Science Foundation, Madria is studying workforce development in the areas of cybersecurity, data analytics, and blockchains.
One aim of this project will be to increase the size and diversity of people in the computer science industry, as there is a special focus on working with underrepresented groups and women college students. The project will help undergraduate students build computer science skills while learning about future employment options in the field and in academics.
Madria is also directing a project for the Graduate Assistance in Areas of National Need (GAANN) program. Over the past five years, he has received about $800,000 in funding for a doctoral fellowship program that focuses on analytics, big data and machine learning for cybersecurity. This program involves multiple hands-on components for students to complete, such as internships, mentorships, supervised teaching, and international experiences.
“We appreciate how the federal government has sought Missouri S&T’s expertise on cybersecurity and machine learning on a variety of projects,” Madria says. “We have a strong partnership with several federal agencies, and the university has traditionally delivered strong products and programs that can often have world-changing implications.”
![Composite of (a) 300-hPa geopotential height anomalies [shading, shading interval (SI) = 10 gpm] and (b) 2-m air temperature anomalies (shading, SI = 0.5°C) during the extreme heat summers over Western North America (WNA) in ERA5 data set. (c, d) are the same as (a, b), but for the MME from 15 CMIP6 models. The blue rectangles represent the region over WNA (40°–60°N, 128°–110°W). The anomalies are relative to 1981–2010.](/images/ezgif.com-webp-to-jpg_f5ba0.jpg "Composite of (a) 300-hPa geopotential height anomalies [shading, shading interval (SI) = 10 gpm] and (b) 2-m air temperature anomalies (shading, SI = 0.5°C) during the extreme heat summers over Western North America (WNA) in ERA5 data set. (c, d) are the same as (a, b), but for the MME from 15 CMIP6 models. The blue rectangles represent the region over WNA (40°–60°N, 128°–110°W). The anomalies are relative to 1981–2010.")
From late June to early July 2021, an unprecedented heatwave swept across Western North America (WNA), causing considerable regional societal and economic hazards. Many new records on maximum temperatures were broken, including 46.7°C in Portland, Oregon, and 49.6°C in Lytton, British Columbia, the latter representing the highest temperature ever observed in Canada. In addition, more than 1,000 deaths were believed to have been linked to the extreme heatwave. Such an extreme event raises questions about how the likelihood of a similar heatwave will change under global warming.
Recently, in a paper published in Earth's Future, Prof. WANG Lin from the Center for Monsoon System Research, Institute of Atmospheric Physics (IAP) at the Chinese Academy of Sciences, in collaboration with scientists from Yunnan University, revealed that heatwaves similar to the unprecedented WNA one in summer 2021 are projected to become more frequent in a warmer world based on the multi-model simulations from the Coupled Model Intercomparison Project, which began in 1995 under the auspices of the World Climate Research Programme (WCRP) and is now in its sixth phase(CMIP6).
They found that the likelihood of a similar heatwave to the 2021 WNA one will increase in the future if the global warming level continues to rise. Such a heatwave is projected to occur more frequently with increased extreme temperature and shortened return period, making a rare event in the current climate a common event in warmer weather, especially under a high-emission scenario like the Shared Socioeconomic Pathways 585 (SSP5-8.5). They also found a significant expansion of areas over WNA that will break the 2021 record in the future with an increasing emission scenario. However, some heat records west of the Rocky Mountains are still difficult to break even at the end of the 21st century, highlighting the specific extremity of the observed 2021 WNA heatwave. ![Spatial-temporal evolutions of the 2021 Western North America (WNA) heatwave in the observation. (a) Temporal variations of the spatial extent (shading, SI = 100 × 103 km2) of land areas over WNA that experience record-breaking temperature anomalies at different time scales. The purple dot indicates the date and time scale with the maximum record-breaking areas (i.e., June 29 at the 5-day time scale). (b) 2-m air temperature anomalies (shading, unit: °C; relative to 1981–2010) at the 5-day time scale centered on 29 June 2021. Contour lines [contour interval (CI) = 1 SD] indicate the normalized 2-m temperature, defined as the anomalies divided by the corresponding standard deviation among all summer days in 1981–2010. The black points highlight the record-breaking grids. The blue rectangle represents the region over WNA (40°–60°N, 128°–110°W), and the purple lines represent the Canadian and U.S. states' boundaries. (c) The daily evolution of the area-mean 2-m temperature anomalies (orange line) over WNA at the 5-day time scale in the June-August of 2021. The pink shading indicates the historical maximum temperature anomalies at the 5-day time scale on each summer day from 1950 to 2020. The black dot represents the temperature anomaly on 29 June 2021.](/images/ezgif.com-webp-to-jpg_1_e10d9.jpg "Spatial-temporal evolutions of the 2021 Western North America (WNA) heatwave in the observation. (a) Temporal variations of the spatial extent (shading, SI = 100 × 103 km2) of land areas over WNA that experience record-breaking temperature anomalies at different time scales. The purple dot indicates the date and time scale with the maximum record-breaking areas (i.e., June 29 at the 5-day time scale). (b) 2-m air temperature anomalies (shading, unit: °C; relative to 1981–2010) at the 5-day time scale centered on 29 June 2021. Contour lines [contour interval (CI) = 1 SD] indicate the normalized 2-m temperature, defined as the anomalies divided by the corresponding standard deviation among all summer days in 1981–2010. The black points highlight the record-breaking grids. The blue rectangle represents the region over WNA (40°–60°N, 128°–110°W), and the purple lines represent the Canadian and U.S. states' boundaries. (c) The daily evolution of the area-mean 2-m temperature anomalies (orange line) over WNA at the 5-day time scale in the June-August of 2021. The pink shading indicates the historical maximum temperature anomalies at the 5-day time scale on each summer day from 1950 to 2020. The black dot represents the temperature anomaly on 29 June 2021.")
"Our study indicates that the unprecedented heatwave will become more common in most areas of Western North America if we do not take adequate climate mitigation measures", said Dr. DONG Zizhen, the first author of the paper.
"We use multiple climate models that participate in CMIP6 and consider different emission scenarios and warming levels for the future heatwave projections over WNA, which may provide more information for decision-makers to plan their development routes and adaptation measures", said Prof. WANG, the corresponding author of the paper.
