Welcome to the November 13, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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WPI Researchers Discover Vulnerabilities Affecting Billions of Computer Chips
Worcester Polytechnic Institute
Sharon Gaudin
November 12, 2019
Researchers at Worcester Polytechnic Institute, the University of California, San Diego, and Germany's University of Lubeck found two flaws impacting Intel and STMicroelectronics central processing units (CPUs) which hackers could exploit to steal or doctor data on billions of devices. The TPM-Fail technique would enable bad actors to use timing side-channel attacks, exposing cryptographic keys to compromise a computer's operating system, forge digital signatures, and steal or alter encrypted information. The flaws are in trusted platform modules (TPMs), tamper-proof chips that computer makers have been incorporating into virtually all laptops, smartphones, and tablets for the past decade. One flaw is in Intel's TPM firmware, within a cryptographic library, that can recover the signature key in less than two minutes; the other flaw is within STMicroelectronics' TPM, which essentially leaks the signature key. The researchers disclosed the vulnerabilities to both companies, which worked with them to create fixes for the next generation of these chips.
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Building a World Where Data Privacy Exists Online
The New York Times
Craig S. Smith
November 10, 2019
University of California, Berkeley's Dawn Song, one of the world's foremost experts in computer security and trustworthy artificial intelligence, is developing an alternative online data-privacy model, a platform for people to control and audit their personal data while corporations compensate them for its use. Song believes combining specialized computer chips and blockchain can support a system offering greater scalability and privacy protection. Her team is working to increase the security of chips' trusted execution environments via the Keystone open source enclave, within which secure code bits, or smart contracts, give individuals control of access to their data. Said Song, "You can ... have the integrity that the blockchain ledger provides and also you can have privacy or confidentiality for the smart contract execution that's provided by the secure enclave."
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Brain-Like Computer Chips Could Address Privacy Concerns, Greenhouse Emissions
University of Canterbury (New Zealand)
November 6, 2019
Researchers at the University of Canterbury in New Zealand have developed computer chips with brain-like functionality, which could significantly reduce carbon emissions associated with computing. The researchers proved signals on the chips are remarkable similar to those that pass through the network of neurons in the brain. Such brain-like computing could enable "edge computing" and address the energy consumption of computers. The technology could also significantly reduce the amount of data shared with private companies like Google and Facebook. Said Canterbury researcher Simon Brown, "The key is that processing on-chip and with low power consumption opens up new applications that are not currently possible."
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Apple Card Algorithm Sparks Gender Bias Allegations Against Goldman Sachs
The Washington Post
Taylor Telford
November 11, 2019
Danish software developer David Heinemeier Hansson cited apparent gender discrimination in the Apple Card algorithm, spurring an investigation into Apple Card partner Goldman Sachs' credit card practices. Hansson tweeted that his wife was refused a credit line increase for the Apple Card, despite having a higher credit score than him, prompting the superintendent of New York's State Department of Financial Services (DFS) to launch a probe into the matter. DFS superintendent Linda Lacewell said, "DFS wants to work with the tech community to make sure consumers nationwide can have confidence that the algorithms that increasingly impact their ability to access financial services do not discriminate and instead treat all individuals equally and fairly."
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Meal-Detection Technology Brings Artificial Pancreas Closer to Reality
Stevens Institute of Technology
Katie Koch
November 11, 2019
Artificial intelligence researchers at Stevens Institute of Technology have created a system that detects when someone is eating and calculates their carbohydrate intake. Stevens' Samantha Kleinberg said, "This brings us a step closer to the holy grail — an 'artificial pancreas' that can quickly detect glucose changes, and correct them with an insulin pump, without the user having to do anything." The algorithm compares changes in glucose in the body to an archive of curves representing glucose changes resulting from eating many different foods, and identifying the curve resembling fluctuations and activity levels read over a certain period. The algorithm refers to the dietary information for what it concludes the person just consumed, calculates the carbohydrate number, and dispatches the appropriate dose of insulin. The algorithm can model carbohydrate intake to within 1.2 grams and identify meals within an average of 25 minutes.
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Spying on Cancer
ASCR Discovery
November 1, 2019
Northwestern University researchers monitored the structure and movement of macromolecules within cancer cells exposed to deadly ultraviolet light via partial-wave spectroscopic (PWS) microscopy. The technique spots extremely small intracellular structures without deadly or disruptive labels or dyes, and tracks entire molecular clusters. Northwestern's Allen Taflove and colleagues developed dynamic PWS through models on a supercomputer at the U.S. Department of Energy's Argonne Leadership Computing Facility (ALCF). Taflove said, "Using the ALCF Mira resource, we validated the dynamic PWS microscopy technique and successfully applied it to study the time-domain response of cancer cells subjected to a lethal stimulus." The researchers ran experiments alongside models using an open source finite-difference time-domain-based software suite, which modeled static and dynamic PWS. Dynamic PWS enhances the process with millisecond resolution, confirming its effectiveness in gaining new insights about macromolecular behavior in cancer cells.
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MIT Robot Can Grow Like a Plant When It Needs Extra Reach
TechCrunch
Darrell Etherington
November 7, 2019
Researchers at the Massachusetts Institute of Technology have developed a robotic system that can "grow" in a way similar to how a young plant grows upward. The robot is not a soft robot, so it can extend itself to reach up to a previously unreachable height, or through a gap in a hard-to-reach area, while maintaining the rigidity and strength required to support a gripper or other mechanism. The robot uses a chain-like apparatus similar to a bicycle chain. The links of the chain are interlocking blocks that can "lock" into one another to form a rigid column, then "unlock" to return to a flexible state.
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Stress Testing the Healthcare System
Complexity Science Hub Vienna
November 11, 2019
Researchers at Austria's Complexity Science Hub Vienna created a computer model of the Austrian healthcare system based on patient flows between primary care physicians in regional networks. The model can deduce a healthcare system's resilience from these networks in real time; the researchers found surprisingly close linkage and regional concentration of patient-flow networks. Knowing that more than 80% of all patients choose physicians for further healthcare with whom they have previously had contact allowed the researchers to calculate where patients of a specific doctor will go following their retirement. The model showed that the loss of too many doctors at one time, or of particularly critical physicians, can overtax the system.
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This Piece of Music Could Stop Your Amazon Alexa
New Scientist
Layal Liverpool
November 6, 2019
Carnegie Mellon University (CMU) researchers have developed a technique to inhibit the Amazon Alexa voice assistant's ability to respond to commands by playing an audio clip. The researchers used an artificial intelligence-generated clip on their own voice assistant, producing guitar sounds the assistant did not respond to—then tested the attack on Alexa. Alexa responded to the audio cue "Alexa" only 11% of the time, versus 80% when other music was playing, and 93% with no audio clip. CMU's Juncheng Li said this attack could be used to trick, confuse, or distract people, but it should be relatively easy for Amazon to tweak Alexa to identify and evade such exploits. Amazon said the attack presents little danger, as "it would require specific audio samples to be played at the same time as a user saying the wake word and would only increase times where the wake word is not detected."
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Putting Conservation Finger on Internet's Pulse
University of Helsinki
November 11, 2019
Scientists at the University of Helsinki in Finland have mined online reactions to endangered animals and plants in order to improve the odds endangered plants and animals can be saved. They developed an algorithm that continuously quantifies the volume of online discussions on species extinction, gauging users' sentiments to identify whenever the average sentiment exceeds the norm, specifying the occurrence of a major species event. Helsinki's Christoph Fink said, "Automatic sentiment analysis reveals the feelings people express in text, and other so-called natural language processing techniques have not been used much in conservation science." The researchers amassed for analysis about 5,000 Twitter posts and 1,000 online news articles in 20 languages every day for the last five years. The researchers think understanding public sentiment on species conservation, using social media as a starting point, can feed into the design of widely accepted policies, combat misinformation, and measure the efficacy of educational programs.
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Etalumis 'Reverses' Simulations to Reveal New Science
Berkeley Lab News Center
Keri Troutman
November 12, 2019
Multinational researchers tapped Lawrence Berkeley National Laboratory's National Energy Research Scientific Computing Center (NERSC) to create the first probabilistic programming framework for controlling existing simulators operating on high-performance computing platforms. The Etalumis system offers a way to reverse-engineer simulations to better interpret the experimental data fed into these models and gain scientific knowledge. Etalumis executes Bayesian inference, basically inverting the simulator to predict input parameters from observations. Atilim Gunes Baydin at the U.K.'s University of Oxford said, "This means the simulator is no longer used as a black box to generate synthetic training data, but as an interpretable probabilistic generative model that the simulator's code already specifies, in which we can perform inference." The researchers applied Etalumis to Switzerland's Large Hadron Collider at CERN, reducing the time it takes to train a complex dynamic neural network on NERSC's Cori supercomputer from months to minutes.
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How Do You Like Your Beef ... Old-Style Cow or 3D-Printed?
The Guardian
Gareth Rubin
November 10, 2019
Israeli and Spanish companies are offering three-dimensionally (3D)-printed meat products synthesized from plant protein. Israeli firm Redefine Meat will pilot its plant-based meat in European eateries early next year. Spain's Novameat aims to have its plant-based printers in Spanish, Italian, and U.K. restaurants in the next year, in supermarkets in 2021, and in residences a year or two later. Novameat's printers receive pea and rice proteins via capsules, which they combine with a red paste to create realistic steak or chicken. Said Emma Lake of U.K. food-industry publication The Caterer, "The potential market for 3D-printed meat could be substantial; we've already seen dramatic growth in vegan meat imitations in response to more consumers cutting down on their consumption of animal products for environmental and health reasons."
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