Welcome to the March 20, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Location Data to Gauge Lockdowns Tests Europe's Love of Privacy
Bloomberg
Jonathan Tirone; Thomas Seal; Natalia Drozdiak
March 18, 2020
Officials in Austria and Italy are using location data transmitted by mobile phones to determine the effectiveness of their coronavirus lockdown policies. Telekom Austria AG is using tracking technology originally developed to analyze travel patterns to provide "anonymized data" to relevant authorities. Meanwhile, Vodafone Group Plc is providing Italian officials with anonymized customer data to track and analyze population movements in the Lombardi region of the country. European countries have some of the world's strictest rules regarding the use and sharing of mobile phone location data, and European companies must seek explicit consent from users in most cases before processing any personal data; the EU also mandates high standards for data anonymization.
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Detailed Audit of Voatz' Voting App Confirms Security Flaws
Government Technology
Andrew Westrope
March 18, 2020
Security consulting firm Trail of Bits confirmed issues raised by Massachusetts Institute of Technology researchers and others that the Voatz mobile voting app is riddled with flaws, with an audit identifying 79 bugs, with 33% of them designated high-severity. Trail of Bits cited technical flaws in Voatz ranging from a lack of test coverage and documentation to manually provisioned infrastructure without infrastructure-as-code tools, outdated features that have yet to be deleted, and nonstandard cryptographic protocols. Michael Fernandez with the Association for the Advancement of Science's Center for Scientific Evidence in Public Issues said the challenge of mobile voting is permitting audits of each ballot, without exposing how any specific person voted.
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Widely Used Machine Learning Method Doesn't Work as Claimed
UC Santa Cruz Newscenter
Tim Stephens
March 16, 2020
A study by researchers at the University of California, Santa Cruz (UCSC), Google, and Stanford University found fundamental flaws in a widely used machine learning (ML) technique for modeling complex networks. The researchers said low-dimensional embeddings have drawbacks, and mathematically showed that significant structural aspects of networks are lost in the embedding process. UCSC's C. Seshadhri warned that any embedding technique yielding a small list of numbers will basically fail because a low-dimensional geometry is insufficiently expressive for social networks and other complex networks. Seshadhri said the research shows the need to check the validity of underlying ML assumptions, because "in this day and age when machine learning is getting more and more complicated, it's important to have some understanding of what can and cannot be done."
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The Humble Tire Gets Kitted Out with Technology
The Wall Street Journal
Sara Castellanos
March 19, 2020
Tire manufacturers are designing intelligent tires to improve the braking of self-driving vehicles. Goodyear Tire & Rubber is developing tires equipped with a sensor and proprietary machine learning algorithms, in the hope they will help autonomous vehicles brake at a shorter distance and communicate with self-driving systems. Goodyear currently sells tires that measure temperature and pressure, but the new intelligent tire incorporates a sensor that monitors wear, inflation, and road surface conditions; data from the sensor is tracked continuously and analyzed in real time with machine learning algorithms. Said Goodyear CEO Rich Kramer, "With the onset of autonomous vehicles, the role of the tire in the performance and safety of the vehicle would increase if we can make that tire intelligent."
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Research Improves Drone Detection
Aalto University
March 18, 2020
Researchers at Aalto University in Finland, Universite Catholique de Louvain in Belgium, and New York University have compiled radar measurement data from different types of aerial drones, to enhance the detection and identification of unmanned aerial vehicles. The researchers measured the Radar Cross Section of commercially available and custom-built drones, which indicates how each reflects radio signals, as a way of identifying their size, shape, and structural materials. Aalto's Vasilii Semkin said the publicly available results are intended to form the basis of a uniform drone database. Said Semkin, “There is an urgent need to find better ways to monitor drone use. We aim to continue this work and extend the measurement campaign to other frequency bands, as well as for a larger variety of drones and different real-life environments.”
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Novel System Allows Untethered Multi-Player VR
Purdue University News
Chris Adam
March 18, 2020
Purdue University researchers have created a virtual reality (VR) system that allows untethered multi-player gameplay on smartphones. The Coterie system manages the rendering of high-resolution virtual scenes to fulfill the quality of experience of VR, facilitating 4K resolutions on commodity smartphones and accommodating up to 10 players to engage in the same VR application at once. Purdue's Y. Charlie Hu said Coterie "opens the door for enterprise applications such as employee training, collaboration and operations, healthcare applications such as surgical training, as well as education and military applications."
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Chip-Based Devices Improve Practicality of Quantum-Secured Communication
Optical Society of America
March 19, 2020
Researchers at the University of Bristol in the U.K. demonstrated chip-based devices containing all required optical components for quantum key distribution and boosting real-world security. The devices feature semiconductor technology found in all smartphones and computers, replacing the wires for conveying electricity with circuits that control photonic signals; nanoscale elements shrink the power requirements of quantum communication systems while maintaining high-speed performance for networks. The researchers developed the platform to support citywide networks and reduce the number of connections between users. Bristol's Harry Semenenko said the new chip-based platform “offers a level of precise control and complexity not achievable with alternatives. It will allow users to access a secure network with a cost-effective device the same size as the routers we use today to access the Internet.”
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Abel Prize in Mathematics Shared by Two Trailblazers of Probability, Dynamics
The New York Times
Kenneth Chang
March 18, 2020
Hillel Furstenberg of Israel's Hebrew University of Jerusalem and Yale University's Gregory Margulis share this year's Abel Prize in mathematics for trailblazing work in probability and dynamics. Both researchers' work demonstrated the application of probability for solving abstract problems. Furstenberg's doctoral thesis at Princeton University explored whether a full history of some measurements or a sequence of numbers could help indicate what would happen next, and he demonstrated that a dynamical system where snapshots reproduced the numerical sequence could achieve this. Margulis' work included devising a procedure for designing connected networks, known as expander graphs. The procedure also can be useful in creating error correction algorithms, random number generators, and cryptography.
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Stanford Engineers Create Shape-Changing, Free-Roaming Soft Robot
Stanford News
Taylor Kubota
March 18, 2020
Stanford University and University of California, Santa Barbara (UCSB) researchers have developed a human-scale soft robot that can reconfigure its shape to grasp and handle objects, as well as being able to roll in controllable directions. The most basic iteration of this "isoperimetric robot" is an inflated tube running through three small machines that pinch it into a triangle form; although its shape dramatically changes, the total length of the edges and the amount of internal air do not. The researchers can add complexity by attaching triangles together, and coordinating the movements of different motors enables different behaviors. Stanford's Allison Okamura said, "This research highlights the power of thinking about how to design and build robots in new ways."
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Researchers Expose Vulnerabilities of Password Managers
University of York
Shelley Hughes
March 16, 2020
Researchers at the University of York in the U.K. have demonstrated that some commercial password managers may not completely protect users. The team created a malicious app to impersonate a legitimate Google app and was able to fool two out of the five password managers it tested into revealing a password. Some of the password managers used weak criteria for identifying an app and which username and password to suggest for autofill; others did not have a limit on the number of times a master PIN or password could be entered. York's Siamak Shahandashti said the researchers suggest password managers “need to apply stricter matching criteria that is not merely based on an app's purported package name."
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AI Helps Prevent Disruptions in Fusion Devices
Princeton Plasma Physics Laboratory
John Greenwald
March 17, 2020
An international team of scientists led by researchers at the U.S. Department of Energy Princeton Plasma Physics Laboratory (PPPL) showed that artificial intelligence (AI) can predict and avoid the sudden, disruptive release of energy stored in the plasma that powers fusion reactions. The team trained a machine learning algorithm on thousands of previous experiments on the DIII-D National Fusion Facility, then applied the algorithm to ongoing experiments and found it could predict the likelihood of disruptions and initiate actions that avert them. Said PPPL's Raffi Nazikian, "However, a great deal of R&D is still required to improve the accuracy of the predictions and to develop fail-safe control methods to avoid disruptions in ITER (a large fusion device under construction in France) and future reactors.”
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WordPress, Apache Struts Account for 55% of Weaponized Vulnerabilities
ZDNet
Catalin Cimpanu
March 17, 2020
A study of all vulnerability disclosures between 2010 and 2019 by risk analysis firm RiskSense estimated that the WordPress and Apache Struts application frameworks were responsible for more than half (55%) of all weaponized and exploited security bugs. Vulnerabilities in PHP and Java apps were the most weaponized bugs in coding languages during that period. Although JavaScript and Python contained the fewest bugs, New Mexico-based RiskSense, which provides vulnerability and cybersecurity risk management services, expects this will change in the future as both languages' popularity and adoption ramp up. The three leading bugs by weaponization rate were command injection (60% weaponized), OS command injection (50% weaponized), and code injection (39% weaponized).
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Personality Key in Whether Developers Can Contribute to Open Source Projects
Waterloo News
March 16, 2020
The results of a study by researchers at the University of Waterloo in Canada suggest a software developer's personality could affect their ability to contribute to open source projects. Although social factors are the primary determinant of acceptance or rejection of online contributors' work, Waterloo's Meiyappan Nagappan said personality also is important to consider because it governs how contributors' behaviors manifest in their interactions with others. The researchers assessed data from the GitHub open source platform to analyze the personality traits of 16,935 active developers from 1,860 projects, and extracted the five leading developer personalities—openness, conscientiousness, extraversion, agreeableness, and neuroticism—with the IBM Watson Personality Insights service. Waterloo's Alex Yun said the analysis suggested that biases may be involved in the acceptance or rejection of contributions to work on open source platforms. Said Yun, "Managers are more likely to accept a contribution from someone they know, or someone more agreeable than others, even though the technical contribution might be similar."
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