Contracts for April 28, 2021

On the same subject

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  April 10, 2023 | International, Land

  Greece buys Rafael’s anti-tank Spike missiles from Israel

  The sale follows a recent purchase of another Israeli-made weapon by yet another NATO member.

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  February 7, 2019 | International, C4ISR

  DARPA: Defending Against Adversarial Artificial Intelligence

  Today, machine learning (ML) is coming into its own, ready to serve mankind in a diverse array of applications – from highly efficient manufacturing, medicine and massive information analysis to self-driving transportation, and beyond. However, if misapplied, misused or subverted, ML holds the potential for great harm – this is the double-edged sword of machine learning. “Over the last decade, researchers have focused on realizing practical ML capable of accomplishing real-world tasks and making them more efficient,” said Dr. Hava Siegelmann, program manager in DARPA's Information Innovation Office (I2O). “We're already benefitting from that work, and rapidly incorporating ML into a number of enterprises. But, in a very real way, we've rushed ahead, paying little attention to vulnerabilities inherent in ML platforms – particularly in terms of altering, corrupting or deceiving these systems.” In a commonly cited example, ML used by a self-driving car was tricked by visual alterations to a stop sign. While a human viewing the altered sign would have no difficulty interpreting its meaning, the ML erroneously interpreted the stop sign as a 45 mph speed limit posting. In a real-world attack like this, the self-driving car would accelerate through the stop sign, potentially causing a disastrous outcome. This is just one of many recently discovered attacks applicable to virtually any ML application. To get ahead of this acute safety challenge, DARPA created the Guaranteeing AI Robustness against Deception (GARD) program. GARD aims to develop a new generation of defenses against adversarial deception attacks on ML models. Current defense efforts were designed to protect against specific, pre-defined adversarial attacks and, remained vulnerable to attacks outside their design parameters when tested. GARD seeks to approach ML defense differently – by developing broad-based defenses that address the numerous possible attacks in a given scenario. “There is a critical need for ML defense as the technology is increasingly incorporated into some of our most critical infrastructure. The GARD program seeks to prevent the chaos that could ensue in the near future when attack methodologies, now in their infancy, have matured to a more destructive level. We must ensure ML is safe and incapable of being deceived,” stated Siegelmann. GARD's novel response to adversarial AI will focus on three main objectives: 1) the development of theoretical foundations for defensible ML and a lexicon of new defense mechanisms based on them; 2) the creation and testing of defensible systems in a diverse range of settings; and 3) the construction of a new testbed for characterizing ML defensibility relative to threat scenarios. Through these interdependent program elements, GARD aims to create deception-resistant ML technologies with stringent criteria for evaluating their robustness. GARD will explore many research directions for potential defenses, including biology. “The kind of broad scenario-based defense we're looking to generate can be seen, for example, in the immune system, which identifies attacks, wins and remembers the attack to create a more effective response during future engagements,” said Siegelmann. GARD will work on addressing present needs, but is keeping future challenges in mind as well. The program will initially concentrate on state-of-the-art image-based ML, then progress to video, audio and more complex systems – including multi-sensor and multi-modality variations. It will also seek to address ML capable of predictions, decisions and adapting during its lifetime. A Proposers Day will be held on February 6, 2019, from 9:00 AM to 2:00 PM (EST) at the DARPA Conference Center, located at 675 N. Randolph Street, Arlington, Virginia, 22203 to provide greater detail about the GARD program's technical goals and challenges. Additional information will be available in the forthcoming Broad Agency Announcement, which will be posted to www.fbo.gov. https://www.darpa.mil/news-events/2019-02-06

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  December 8, 2020 | International, Aerospace

  Taiwan F-16 upgrade aims for 2023 completion

  By Greg Waldron7 December 2020 Taiwan has upgraded 18 Lockheed Martin F-16A/Bs to the new F-16V standard, and hopes to complete all 141 planned upgrades by 2023. In addition, 66 new F-16Vs from a 2019 deal with the US government will be completed by 2026, according to a recent report by Taiwan's Central News Agency, quoting the Taiwanese military. The work is being undertaken by local airframer AIDC with support from Lockheed. Taipei hopes to complete the upgrade work by 2023, a year later than originally planned. The report adds that the Taiwan F-16V fleet will feature the Raytheon ALQ-184 electronic countermeasures pod, which is consistent with US Air Force equipment. The upgrade affects the mission computer, airframe, cockpit instruments, and electronic warfare system. The jets will also receive an active electronically scanned array radar in the form of Northrop Grumman's Scalable Agile Beam Radar. The project involves AIDC essentially installing a kit originally developed by Lockheed. Taipei has an urgent need to upgrade its defence capabilities owing to increasing military pressure from China, which views the democratic island as a province. Beijing, which has rapidly developed its military over the last decade, regularly mounts probing flights to test Taiwan's air defences. https://www.flightglobal.com/defence/taiwan-f-16-upgrade-aims-for-2023-completion/141502.article?referrer=RSS