The tsunami of information that will hit with the full exploitation of 5G cellular will create a wealth of open source intelligence that will define the art in coming years. New sensor systems, artificial intelligence (AI) processing and expanded information delivery methods will produce new types of intelligence available in greater detail for a range of customers.
A research team at Sandia National Laboratories has successfully used machine learning—computer algorithms that improve themselves by learning patterns in data—to complete cumbersome materials science calculations more than 40,000 times faster than normal, according to a Sandia press release.
Their results, published in the January 4 issue of a journal called npj Computational Materials, could herald a dramatic acceleration in the creation of new technologies for optics, aerospace, energy storage and potentially medicine while simultaneously saving laboratories money on computing costs, according to the press release.
Pentagon officials are developing a strategy related to the joint all-domain command and control (JADC2) concept that should be delivered soon to the combatant commands, according to Lt. Gen. Dennis Crall, USMC, the Joint Staff's chief information officer and director of command, control, communications and computers, also known as the J-6.
Gen. Crall made the comments during the AFCEA TechNet Cyber conference, a virtual event held December 1-3.
In a project for the Defense Department’s Defense Innovation Unit (DIU), computer scientists have turned to artificial intelligence and aerial imagery to construct a detailed damage assessment solution. The tool can be used remotely and automatically to determine the amount of damage to buildings and structures from a natural disaster or catastrophe. The prototype, known as the xView II model, was tested this fall, with the goal of rolling out a more finalized operational version next year.
The recently completed Network Modernization Experiment (NetModX) included an army of autonomous agents unleashed in defense of the network and in some cases also protected other artificial intelligence (AI) technologies.
NetModX is a science and technology experiment held July 20-October 2 at Joint Base McGuire-Dix-Lakehurst, New Jersey. The science and technology experiment provides lessons learned for Army acquisition decisions, science and technology specifications, requirements and strategies necessary to modernize the force. Systems that performed well this year might ultimately end up in the Army’s arsenal as part of the capability sets to be fielded in 2023 and 2025.
The U.S. Army’s joint strategy document for countering small unmanned aerial systems should be headed soon to the Secretary of Defense for approval, Army officials say, and artificial intelligence and machine learning are crucial to the vision.
During a telephone discussion with reporters, Maj. Gen. Sean Gainey, USA, director of the Joint Counter-Unmanned Aircraft Systems Office and director of fires, G-3/5/7, described artificial intelligence (AI) and machine learning (ML) as “critical” to the military’s efforts to counter unmanned aerial systems (UAS).
Artificial intelligence technology tested during the Army’s Project Convergence exercise largely met expectations and will help transform the way the Army fights in the future, officials say.
Data in various forms supports a wide range of national security missions, and whichever country is best able to use that data will have a distinct advantage, according to intelligence agency experts speaking at the virtual 2020 Intelligence and National Security Summit.
The FBI’s pilot iris recognition program initiated in 2013 will likely be fully operational this fall, possibly by October 1. The agency also is developing tools to detect fingerprints that have been deliberately mutilated and a scanner large enough to get a print of the entire palm along with all five fingerprints.
A mushroom cloud explosion in the New Mexico desert on July 16, 1945 forever changed the nature of warfare. Science had given birth to weapons so powerful they could end humanity. To survive, the United States had to develop new strategies and policies that responsibly limited nuclear weapon proliferation and use. Warfare is again changing as modern militaries integrate autonomous and semiautonomous weapon systems into their arsenals. The United States must act swiftly to maximize the potential of these new technologies or risk losing its dominance.
“There’s a war out there, old friend. A world war. And it’s not about who’s got the most bullets. It’s about who controls the information. What we see and hear, how we work, what we think … it’s all about the information.” These lines are from the 1992 movie Sneakers, a film exploring the possibility of a decryption machine that could break any code, obliterating the ability to protect secrets. Nearly three decades later, the fictitious decoder still doesn’t exist, but the importance of data has grown exponentially.
A Marine Corps of the future with a “reinvigorated Fleet Marine Force” and a strong Marine Expeditionary Force requires robust command and control and other advanced communications technologies, says the service’s top leader. As such, the Marine Corps Systems Command’s Command Element Systems is pursuing advanced satellite communications, electronic warfare, biometrics and other solutions.
Cloud computing can quicken U.S. Department of Defense (DOD) efforts toward information dominance, but agencies must be measured and deliberate in the march toward the cloud.
Applying artificial intelligence/machine learning (AI/ML) cybersecurity is a “hard problem,” but one with significant and promising progress, according to intelligence experts. Achieving this will require a combination of top-down and bottom-up efforts that leverage both government and industry cooperation, as each can benefit from unique capabilities and contributions of the other.
If Hollywood were to create a movie about CIA human intelligence gathering, it would need to be more Mission Impossible than James Bond, more about teamwork and technical expertise than individual exploits, says Dawn Meyerriecks, who leads the agency’s Directorate of Science and Technology.
ECS Federal LLC, Fairfax, Virginia, was awarded a $78,725,114 modification (P00003) to contract W911QX-18-C-0037 for machine learning and computer vision engineering. Work will be performed in Fairfax, Virginia, with an estimated completion date of July 16, 2022. Fiscal year 2018 and 2019 research, development, test and evaluation funds in the amount of $35,847,000 were obligated at the time of the award. U.S. Army Contracting Command, Aberdeen Proving Ground, Maryland, is the contracting activity.
The U.S. Cyber Command has released a list of 39 challenge problems fitting under 12 categories: vulnerabilities, malware, analytics, implant, situational awareness, capability development, persona, hunt, mission management, attack, security and blockchain.
The Navy is seeking advanced cybersecurity solutions based on artificial intelligence and machine learning technologies, the Naval Information Warfare Systems Command announced in a recent statement.
The Command, known now as NAVWAR, and the Program Executive Office for Command, Control, Communications, Computers and Intelligence (PEO C4I) are co-sponsoring the so-called Artificial Intelligence Applications to Autonomous Cybersecurity Challenge (AI ATAC).
Hughes Network Systems LLC, Germantown, Maryland, was awarded an $11,823,659 cost-plus-fixed-fee contract for the research and development effort to research solutions, prototype products and demonstrate solutions that include machine learning to improve transport and network performance availability and reliability. One bid was solicited with one bid received. Work will be performed in Germantown, Maryland, with an estimated completion date of December 30, 2023. Fiscal year 2019 research, development, test and evaluation funds in the amount of $1,863,123 were obligated at the time of the award. U.S. Army Contracting Command, Aberdeen Proving Ground, Maryland, is the contracting activity (W56KGU-19-C-0016).
Artificial intelligence and machine learning techniques could help information and network defenders recognize patterns of potential attackers so their next moves can be proactively blocked. In addition, cyber tools enhanced with these capabilities could provide a much more detailed picture of the cyber battlefield and increase the potential of success in a cyber campaign. This knowledge would complement the kinetic battlefield and could permit war planners to choose the appropriate mix of cyber and kinetic operations.
Rekor Systems, Inc. has announced that it will provide automatic license plate recognition (ALPR) solutions to the U.S. Defense Department. The contract with the department is for the purchase of 200 licenses to use Rekor's machine learning-enabled vehicle recognition system powered by the company’s OpenALPR software.
The Defense Security Service (DSS) and Defense Information Systems Agency (DISA) have awarded nearly $75 million to Perspecta Enterprise Solutions LLC of Herndon, Virginia, to help reform and modernize the security clearance personnel vetting processes and develop the National Background Investigation Service (NBIS) information technology system.
Asked which technology will be most critical to artificial intelligence in the coming years, experts agree: artificial intelligence, hands down.
Two experts from academia and industry—Mathew Gaston, director of the Emerging Technology Center at the Carnegie Mellon University Software Engineering Institute, and Fletcher Previn, chief information officer at IBM Corporation—participated in a fireside chat at the AFCEA TechNet Cyber 2019 conference and predicted artificial intelligence will be the number one technology most critical to national security in the next several years.
The Defense Information Systems Agency (DISA) is acquiring an array of cutting-edge technologies using rapid development processes and could begin fielding some of those technologies within the next two years.
The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems. Scientists at the Army Research Laboratory, specializing in adversarial machine learning, are working to strengthen defenses and advance this aspect of artificial intelligence.
The National Science Foundation’s Directorate for Computer and Information Science and Engineering is working to create a big data ecosystem. As part of that effort, the NSF, as it is known, is expanding the National Network of Big Data Regional Innovation Hubs, first created three years ago. The hubs, with one location for each U.S. Census region—the Midwest, Northeast, South and West—grew out of the need to aid the development of big data research and to help solve complex societal problems. The hubs are having a positive impact on the growth of machine learning, increasing the access to data, methods, networks and expertise, experts say.
Burgeoning computer capabilities often are unreliable, or brittle, at first. Capabilities that work successfully in one instance may fail miserably when applied to another area. At the moment, machine learning is no different, experts say, and the government and private industry are endeavoring to get past the limitations to improve its use.
Artificial intelligence (AI) has come a long way in recent years, but the technology still has hurdles to overcome if machines are to become true partners and collaborators with humans. To help push the systems to that next level, the Defense Advanced Research Projects Agency (DARPA) is hosting a two-day conference aimed at spurring the next wave of AI advances.
The U.S. Navy is in the nascent stages of a plan to revolutionize readiness through the use of artificial intelligence, machine learning and data analytics. It also may include the establishment of two new offices: a chief readiness office and an analytics office.
The Intelligence Advanced Research Projects Activity (IARPA) is seeking information on research efforts in the area of machine learning with a particular focus on deep learning and in the area of cooling systems for small mobile devices.
Artificial intelligence and machine learning are two of the many technologies that will change the way the military operates, according to a panel of experts. However, despite the revolutionary innovations that lie ahead, humans always will need to be the controlling factor in any operation.
These experts offered their views of the future on the second day of AFCEA’s TechNet Asia-Pacific 2018, held November 14-16 in Honolulu. In a panel sponsored by the Young AFCEANs, the five experts presented a younger generation’s perspective on the advantages and pitfalls of a data-centric battlespace.
Applied Research Solutions, Beavercreek, Ohio, has been awarded a $38,788,878 cost-plus-fixed-fee contract, plus an option amount of $5,967,447, for sensing, learning, autonomy, and knowledge engineering research and development. This contract is to conduct research and develop multi-domain technologies and strategies to orchestrate closed-loop sensing that manages knowledge from environment understanding to mission effects, across multiple missions. Work will be performed at Wright-Patterson Air Force Base and in Dayton, Ohio, and is expected to be completed by March 4, 2024. Fiscal year 2019 research and development funds in the amount of $1,254,000 are being obligated at the time of award.
Russia’s ability to evolve its use of information operations to leverage social media and the cyber domain continues to shock and challenge the world community. The country’s actions, especially during the 2016 U.S. elections, have brought cyber information operations out of the shadows and into the limelight. Now, state and nonstate actors are frequently using similar techniques to influence the public and achieve political goals once only attainable through armed conflict.
It has become increasingly evident that artificial intelligence (AI) and machine learning (ML) are poised to impact government technology. Just last year, the General Services Administration launched programs to enable federal adoption of AI, and the White House encouraged federal agencies to explore all of the possibilities AI could offer. The benefits are substantial, but before the federal government can fully take advantage of advancements like AI, federal agencies must prepare their IT infrastructure to securely handle the additional bandwidth.
U.S. Army officials conducting the third annual Cyber Quest experiment, which ends today, will issue a report in about 30 days that will determine which of the systems involved will transfer to programs of record. The exercise consists of an array of systems, including artificial intelligence and machine learning, that help provide situational understanding of the cyber and electronic warfare realms.
With the arrival of June, we’re at the halfway point of an already busy year for the cybersecurity industry. With each passing year, our sector continues to demonstrate its evolving approach to fighting cyber threats, as cyber crime itself continues to evolve.
As both business and government move forward with digital transformation initiatives to improve processes and efficiency, the overall security attack surface continues to expand with more potential points of access for criminals to exploit. However, our industry is tackling these challenges head-on, with numerous innovative solutions continuing to come to market.
Two U.S. Army generals intimately involved in the modernization of the service’s network are considering a competition for industry and academia to come up with cutting-edge solutions, such as artificial intelligence, for the future network.
In an example of great minds thinking alike, Maj. Gen. Peter Gallagher, USA, who leads the network modernization cross-functional team (CFT), and Maj. Gen. David Bassett, USA, the program executive officer for command, control and communications-tactical (PEO C3T), recently realized during an interview with SIGNAL Magazine that both were thinking along the same lines.
BAE Systems Information and Electronic Technology Solutions, Burlington, Massachusetts, has been awarded a $9,286,398 cost-plus-fixed-fee contract for radio frequency (RF) emissions made unique and separable/dynamic adaptive neurally-inspired control for efficient RF surveillance software. This effort is focused on developing foundations for applying machine learning to the RF spectrum domain and developing practical applications in emerging spectrum problems to develop vastly improved discrimination performance over today’s hand-engineered RF systems. Work will be performed in Burlington, Massachusetts; Merrimack, Massachusetts; Raleigh/Durham, North Carolina; and Reston, Virginia. The work is expected to be complete by June 8, 2021.
Situational awareness is key to cybersecurity and using analytics can help create the situational awareness needed to defend the nation from adversaries. “Never before have we had the tools that we have today to understand the environment we’re in,” said Roberta “Bobbie” Stempfley, director, Carnegie Mellon University’s Software Engineering Institute, CERT Division, during her morning keynote at the AFCEA-GMU Critical Issues in C4I Symposium.
Machine learning has advanced to the point where more sophisticated methods can be more effective at cyber event detection than traditional methods, an expert says. Along with emerging methods, access to large amounts of “fresh” data is important for processing, determining trends and identifying malicious activity.
Teams looking at how to use machine learning need to consider different methods, suggested Mark Russinovich, chief technology officer, Microsoft Azure, at the AFCEA Defensive Cyber Operations Symposium (DCOS) in Baltimore on May 17.
With an onslaught of new technologies ever present on the horizon, the U.S. Marine Corps (USMC) is working to make sense of what technologies will work for them, not only in the traditional warfighting domains, but also in cyber—the new domain. Right now, they have a long list of priorities associated with modernizing the network, meeting standards and mandates, and fielding new capabilities.
Northrop Grumman Systems Corp., Bethpage, New York, is awarded a $7,255,294 cost-plus-fixed-fee contract for the development of machine learning algorithms (MLAs) for the Reactive Electronic Attack Measures (REAM) program. The REAM program is a future naval capabilities enabling capability with the objective of transitioning MLAs to the EA-18G airborne electronic attack suite to achieve capabilities against agile, adaptive, and unknown hostile radars or radar modes.
The generation that remembers “duck and cover” also recalls headlines that included the words Soviet Union and impending dangers. Today, a combination of global instability, rising authoritarianism and democracies in retreat may lead to similar yet more dangerous situations, and this time, the headlines also are likely to include the words “People's Republic of China.”
While stopping weapons of mass destruction and cyber attacks are high security priorities, the kinetic effects from cyber forces are a looming threat today. Malevolent uses for artificial intelligence combined with autonomous systems provide frightening new levels of capabilities to potential adversaries, and the U.S. Defense Department and the intelligence community are being called upon to address them with extraordinary vigor.
The U.S. Air Force is deploying a new open architecture for its primary intelligence, surveillance and reconnaissance system. At the same time, Air Force researchers are developing deep learning capabilities that will allow the decades-old system to sort through reams of data more easily, enabling faster decision making on the battlefield and enhancing multidomain command and control.
As businesses, governments and militaries wrestle with artificial intelligence (AI) technologies, managing machines that learn is a challenge common to all.
AI will not merely displace blue-collar tasks; it will affect every management level. Managers will outsource many mundane, time-consuming, attention-taxing and less rewarding tasks. The bigger challenge, however, is integrating AI systems into their teams and determining how teams will collaborate with AI systems to increase insights, improve decision making and enhance leadership.
In a constantly evolving cyberthreat landscape where firewalls and antiviruses have become old hat, organizations must adopt more technologically advanced ways to protect crucial data. Advanced machine learning algorithms can learn the routine patterns of life for every user and device in a network to detect anomalies and adapt accordingly. The most pressing need for this augmented intelligence is in security operations centers, where teams of analysts search for threats by poring over hundreds of thousands of security events every day.
Facing mounting threats, cyber hunt teams—aka security operations teams—are turning to machine learning technologies to sift through heaps of data and detect malicious activity faster than ever. People excel at making decisions with the right information, and machines excel at analyzing and retrieving actionable intelligence from large amounts of data. This duo is much more dynamic when working together than apart. Consider Tony Stark and his Iron Man suit versus the fictional character HAL 9000 from the Space Odyssey series.
Superman might have beaten bullets with his speed, but the U.S. Defense Department intends to do better. It has its sights set on developing cognitive technologies—computer vision, machine learning, natural language processing, for example—that are faster than the speed of human thought.
The military plans to tap machine learning and artificial intelligence (AI), in particular, to enhance decision making.
Geospatial imagery as well as facial recognition and other biometrics are driving the intelligence community’s research into artificial intelligence. Other intelligence activities, such as human language translation and event warning and forecasting, also stand to gain from advances being pursued in government, academic and industry research programs funded by the community’s research arm.
The Intelligence Advanced Research Projects Activity (IARPA) is working toward breakthroughs in artificial intelligence, or AI, through a number of research programs. All these AI programs tap expertise in government, industry or academia.