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.