ACM TechNews


Welcome to the January 22, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Illustration of a computer firewall. Booting Hackers a Complex Chore
Associated Press
Frank Bajak
January 19, 2021


Cybersecurity firm FireEye said an assessment of the effects of a seven-month-old cyberespionage campaign attributed to Russia, and removing participating hackers, is in the early stages. The company released a tool and a white paper to help potential targets screen cloud-based installations of Microsoft 365 for intrusions and continued hacker activity. FireEye's Matthew McWhirter said the goal is to prevent attackers from breaking in again, while the firm's Charles Carmakal suggested there are many more victims than those publicized so far. Carmakal said hackers tended to target users with access to high-value data and high-level network administrators, to determine which measures were being implemented to try to boot them off.

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Biden White House Website Hides Secret Invitation for Coders
Fox Business
Lucas Manfredi
January 20, 2021


The Biden administration is seeking skilled coders to apply for roles within the U.S. Digital Service (USDS). The Biden White House's newly updated website has a message hidden deep in its HTML source code: "If you're reading this, we need your help building back better. https://usds.gov/apply." USDS, created by President Barack Obama in 2014, aims to change the federal government's approach to technology and create better services by bringing together the best designers, engineers, product managers, and digital policy experts. Among other things, the agency has worked to improve HealthCare.gov, modernize the U.S. Department of Homeland Security's immigration system, help the U.S. Department of Education roll out the College Scorecard, and identify security vulnerabilities in the U.S. Department of Defense's website. USDS also aims to improve how the government buys technology and hires technical talent.

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An engineer observing flow physics of aircraft design on a computer display. Turbulence Model Could Help Design Aircraft Capable of Handling Extreme Scenarios
Purdue University News
Kayla Wiles
January 19, 2021


Purdue University researchers have developed a turbulence simulation technique to help design more resilient aircraft by modeling the vortex collision process at reduced computational time. The Coherent-vorticity-Preserving (CvP) Large-Eddy Simulation (LES) model requires a supercomputer to run, but can simulate a vortex collision much faster than previous large-scale calculations. Purdue's Carlo Scalo said, "The CvP-LES model is capable of capturing super-complex physics without having to wait a month on a supercomputer because it already incorporates knowledge of the physics that extreme-scale computations would have to meticulously reproduce." Purdue's Xinran Zhao verified the model's accuracy via large-scale computations.

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Pivotal Discovery in Quantum, Classical Information Processing
Argonne National Laboratory
January 13, 2021


Researchers at the U.S. Department of Energy's Argonne National Laboratory (ANL) and the University of Chicago have realized real-time control of interactions between microwave photons and magnons, potentially advancing electronic devices and both classical and quantum signal processing. ANL's Xufeng Zhang said such control, previously akin to firing an arrow into the air, is now "more like flying a drone, where we can guide and control its flight electronically." The team applied an electrical signal to periodically tweak the magnon vibrational frequency and cause magnon-photon interaction, creating on-demand tunability that can adjust interaction strength at any point during data transference.

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Blue arrows show the optical flow field of a drone in flight. Appreciating a Flower's Texture, Color, Shape Leads to Better Drone Landings
TU Delft (Netherlands)
January 19, 2021


An optical flow-based learning process developed by researchers at the Netherlands' Delft University of Technology (TU Delft) and Germany's Westphalian University of Applied Sciences lets robots calculate distances through the visual appearance of objects in view. This approach boosts the navigation skills of small aerial drones by mimicking flying insects' intelligence. TU Delft's Guido de Croon said enabling robots to interpret optical flow as well as the visual appearance of objects in their environment would eliminate certain limitations to optical flow. The solution involved the drones inducing optical flow oscillations to perceive distances to objects in the scene via visual cues. Westphalian's Tobias Seidl said, "The presented learning process forms a novel hypothesis on how flying insects improve their navigational skills, such as landing, over their lifetime."

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Mitsubishi Electric, Tokyo Tech Develop Blockchain Technology to Optimize P2P Energy Trading
Tokyo Institute of Technology
January 19, 2021


Blockchain technology developed by researchers at Japan's Tokyo Institute of Technology and electronics firm Mitsubishi Electric can optimize peer-to-peer (P2P) energy trading. The team designed a distributed-optimization algorithm that enables client computers to share trading goals and data, then optimally match buy and sell orders with a minimum of computation. The four-step method involves first sharing buy and sell order data with a common trading goal among computing servers during a predetermined timeframe, then having each server search for orders matching that goal. Each server shares its search results in the third step, after which they each generate a new block by choosing trades that best meet the shared goal. The decentralized search for a solution is conducted in parallel on multiple computers where equivalent matches are chosen at random, in order to ensure fair trading.

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An aerial view of a traffic intersection. Optimizing Traffic Signals to Reduce Intersection Wait Times
Texas A&M Today
Stephanie Jones
January 15, 2021


Researchers at Texas A&M University and the U.K.'s University of Edinburgh have developed a system that uses machine learning to optimize the timing of traffic signals to reduce wait times at intersections. Their approach can successfully train a deep neural network in real time and transfer what it has learned from real-world observations to a different control function that can be understood and regulated by traffic engineers. The researchers used a simulation of a real intersection and found that optimizing their interpretable controller reduced vehicle delays by as much as 19.4% compared to commonly deployed signal controllers, which are the "brains" of an intersection.

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How Did Lockdowns Affect Urban Mobility? Research Tracks Rio de Janeiro Cell Data
Binghamton University
Chris Kocher
January 13, 2021


Analysis of cellular data by researchers at Binghamton University and Brazil's Fluminense Federal University measured the impact of the coronavirus pandemic on travel in Rio de Janeiro. The team examined data from 2 million daily cellphone users and 120 million connections to antennas around the Rio metropolitan area, and pinpointed the locations of connections to generate a day-by-day perspective of how many people traveled in the city, their destinations, and how many residents remained home. Results indicated that although roughly 85% of residents showed low mobility, 15% still ventured significantly outside their neighborhoods despite lockdowns. The researchers designed an interactive tool to display mobility patterns, which could help health officials measure mobility of individuals and the number of Covid cases in specific locales.

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An illustration of a design features of a jellyfish-like robot. Jellyfish-Inspired Robot Could Be Used to Explore Coral Reefs, Archaeological Sites
Daily Mail (U.K.)
Ian Randall
January 20, 2021


A robot developed by researchers at the U.K.'s University of Edinburgh and University of Southampton mimics the efficient swimming movements of the moon jellyfish. The robot is 10 to 50 times more efficient than propeller-driven drones and could operate in sensitive underwater environments like coral reefs. The robot propels itself forward via resonance, the large vibrations that occur when a force is applied to an object at its ideal frequency, when a small piston in the front part of the robot's body taps the "propulsive bell"—a rubber membrane enclosing eight three-dimensionally (3D)-printed flexible ribs. This resonance allows the robot to move like the moon jellyfish at 10.5 inches per second. Said Southampton's Gabriel Weymouth, "This has allowed us to unlock the efficiency of propulsion used by sea creatures that use jets to swim."

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Videos Show RNA as It's Never Been Seen
Northwestern McCormick School of Engineering
Amanda Morris
January 15, 2021


Researchers at Northwestern University's McCormick School of Engineering used data generated by RNA-folding experiments to produce the first data-based videos showing RNA folding in action. Northwestern's Julius Lucks and colleagues developed a technology platform that records data about RNA folding during generation, then computationally mines and organizes the data, to expose points where the molecule folds and what happens afterward. Northwestern's Angela Yu fed this data into computer models to generate videos of the folding process. Lucks said, "The information that we give the algorithms helps the computer models correct themselves."

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Fake Collaboration Apps Steal Data as Staff Struggle with Home-Working Security
ZDNet
Danny Palmer
January 19, 2021


According to cybersecurity company Wandera's Cloud Security Report 2021, malware attacks increasingly targeted remote workers last year, with 52% of organizations suffering such hacks, versus 37% in 2019. Remote workers often are deceived into downloading malware from phishing emails. Wandera's Michael Covington said many such applications purport to offer collaboration functions, but really steal private data or fool users into granting access to a device’s camera and microphone for eavesdropping. More than a third of users of malware-compromised devices continued to access corporate emails, while 10% continued to access cloud services, both potentially providing attackers greater network access than they had initially obtained by compromising one remote device. Said Covington, "Continuously engaging with workers on the sign-in mechanisms they should use, the incident reporting they should follow, and the applications that are approved for work will help everyone do their part to protect the business and its assets."

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An image of a busy hospital setting amid the pandemic. Facebook AI Predicts Likelihood of Worsening Covid Symptoms
CNBC
Sam Shead
January 15, 2021


Artificial intelligence (AI) researchers at social media company Facebook claim to have developed software that can forecast the probability of a Covid-19 patient's symptoms escalating, based on their chest x-rays. The Facebook team worked with academics in New York University Langone Health's predictive analytics unit and radiology department. The researchers said the new software could help prevent doctors from sending at-risk patients home too early, as well as helping hospitals plan for oxygen demand. The collaborators said they devised three machine learning models: one predicts deterioration based on a single chest x-ray, the second performs the same task with a sequence of x-rays, and the third employs one x-ray to anticipate how much supplemental oxygen a patient might require. The team said the sequential chest x-ray-based model could predict a patient's needs up to 96 hours in advance.

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Photo of a redheaded, freckle-faced female. Advances in Facial Recognition Improve Accuracy, Bias of Algorithms in Regard to Gender, Skin Color
Universitat Oberta de Catalunya (Spain)
January 15, 2021


Researchers at Spain's Universitat Oberta de Catalunya (UOC) and the University of Barcelona tested facial recognition algorithms against confounding attributes for accuracy and bias regarding gender and skin tones, as part of a challenge within the European Conference of Computer Vision (ECCV) 2020. Challenge participants used an unbalanced image dataset containing 152,917 images portraying 6,139 identities that were annotated for gender and skin color, and for attributes including age, pose, and whether the person is wearing glasses. The best submissions achieved 0.999 accuracy and scored extremely low on proposed bias metrics. Assessment of the algorithms of the top 10 teams indicated more false positives for dark-skinned females and for samples where both individuals wore glasses, and for light-skinned males and for samples where both subjects were under 35. UOC's Julio C. S. Jacques Jr. said, "Overall accuracy is not enough when the goal is to build fair facial recognition methods, and ... future work on the topic must take into account both accuracy and bias mitigation."

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Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio Micali
 
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