Welcome to the August 25, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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qBitcoin: a Way of Making Bitcoin Quantum-Computer Proof?
IEEE Spectrum
Mark Anderson
August 24, 2017


Kazuki Ikeda at Osaka University in Japan has proposed qBitcoin, a new quantum cryptography-based bitcoin standard that could make the cryptocurrency immune to decryption by quantum computers. Ikeda's proposal suggests the sending of quantum cryptographic keys between a qBitcoin remitter and a receiver, and the system would employ demonstrably secure protocols such as the BB84 quantum key distribution framework. The exchange of qBitcoin requires deploying a transmission network for sending and receiving qubits. Ikeda notes qBitcoin, like conventional bitcoin, would be a peer-to-peer system, while also offering comparable or augmented levels of privacy, anonymity, and security. However, the profession of bitcoin mining also could be transformed by the qBitcoin protocol. This is because although translation would still require verification and securing, qBitcoin's security would depend on a quantum digital signature that is reliant on the laws of quantum physics to make the qBitcoin ledger tamper- and hack-proof.

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A submarine underwater First Underwater Entanglement Could Lead to Unhackable Comms
New Scientist
Powell. Devin
August 23, 2017


Researchers at Shanghai Jiao Tong University in China say they have, for the first time, transmitted quantum entangled particles of light through water, marking the first step in using lasers to send underwater messages that are impossible to intercept. The fragile quantum state of entangled particles can easily be disturbed by the surrounding environment, and until now entanglement had only been maintained between particles separated by long distances after traveling through air, space, and optical fibers. To test entanglement in water, the researchers gathered saltwater from the Yellow Sea and placed it in a three-meter-long container, and found they were able to transmit entangled photons through the water without disturbing their quantum link. In addition, the team's calculations suggest it should be possible to communicate in this manner over nearly 900 meters in water. "Because ocean water absorbs light, extending this is going to difficult," notes the University of Missouri in Columbia's Jeffrey Uhlmann.

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Amazon Has Developed an AI Fashion Designer
Technology Review
Will Knight
August 24, 2017


Amazon researchers are working on machine-learning algorithms for analyzing, predicting, and leveraging trends in fashion design, with one Israel-based team having developed software that can infer how stylish a particular look is by analyzing only a few labels attached to images. Meanwhile, Amazon's Lab126 group has developed an algorithm that gleans a specific fashion style from example images so it can produce new items in similar styles from scratch, via a generative adversarial network. A recent Amazon-hosted workshop on machine learning and fashion highlighted research with broader applications to human behavior, including a project conducted by Cornell University professor Kavita Bala and colleagues. Bala says her team is using data collected from Instagram "to understand how people live their daily lives." In addition, a team from the University of Illinois in Urbana-Champaign developed an algorithm for identifying fashion-focused social-network accounts, and Myntra unveiled software for guessing a person's correct apparel size based on past purchases.

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3D molecular structures Major Leap Towards Storing Data at the Molecular Level
University of Manchester
Jordan Kenny
August 24, 2017


Researchers at the University of Manchester in the U.K. have proved that storing data in single-molecule magnets is more feasible than previously thought. Their research shows magnetic hysteresis, a memory effect that is required for data storage, is possible in individual molecules at -213 degrees Celsius, which is extremely close to the temperature of liquid nitrogen. The result means data storage within single molecules could become a reality because the data servers could be cooled using liquid nitrogen, which is much less expensive than commonly used liquid helium. The team thinks future molecular technologies could store more than 200 TB for every square inch. "Using single molecules for data storage could theoretically give 100 times higher data density than current technologies," says Manchester's Nicholas Chilton. In addition, Chilton says the research could lead to much smaller hard drives that require less energy, so data centers could become significantly more energy efficient.

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NSF Announces $17.7M in Awards for Cross-Disciplinary Data Sciences Projects
HPCwire
John Russell
August 24, 2017


The U.S. National Science Foundation (NSF) on Thursday announced it will allocate $17.7 million to fund 12 Transdisciplinary Research in Principles of Data Science (TRIPODS) projects, to "bring together the statistics, mathematics, and theoretical computer science communities to develop the foundations of data science." The initiatives will support research and training activities in data science that go beyond disciplinary boundaries, and NSF's Jim Kurose says the TRIPODS projects "will enable continued data-driven discovery and breakthroughs across all fields of science and engineering." NSF also released its first series of Convergence awards for nurturing cross-disciplinary collaboration to address grand challenge problems. "Convergence is a deeper, more intentional approach to the integration of knowledge, techniques, and expertise from multiple disciplines in order to address the most compelling scientific and societal challenges," says NSF director France Cordova. The awards will align with five grand challenges, including tapping the data revolution, quantum computing, and the human-technology frontier.

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'Nano-Hashtags' Could Provide Definitive Proof of Majorana Particles
Eindhoven University of Technology (Netherlands)
August 23, 2017


Researchers at the Eindhoven University of Technology and the Delft University of Technology in the Netherlands, and the University of California, Santa Barbara say they have created an advanced quantum chip designed to provide definitive evidence of the existence of Majorana particles. The chip is composed of ultrathin indium phosphide nanowire networks configured in the shape of hashtags, with sufficient properties to enable two Majorana particles to "braid," or switch places. The hashtag-like nanowire intersections support a closed circuit along which Majoranas can move. When exposed to a stream of aluminum particles, superconductive layers form on specific points on the wires, which are where the Majorana particles emerge. "The behavior we then see could be the most conclusive evidence yet of Majoranas," says Eindhoven's Erik Bakkers. The mysterious and robust particles are considered the ideal building block for future quantum computers, as two braided Majoranas could form the basis for a quantum bit.

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Doctor’s hand examining woman’s birthmark Artificial Intelligence Helps With Earlier Detection of Skin Cancer
University of Waterloo
Matthew Grant
August 23, 2017


Researchers at the University of Waterloo in Canada say they are developing artificial intelligence (AI) technology to help detect melanoma skin cancer earlier. The team says the technology uses machine-learning software to analyze images of skin lesions and provide doctors with objective data on biomarkers of melanoma. The AI systems, which were trained on tens of thousands of skin images and their corresponding eumelanin and hemoglobin levels, could reduce the number of unnecessary biopsies by giving doctors objective information on lesion characteristics. Waterloo professor Alexander Wong says the new system deciphers levels of biomarker substances in lesions, and adds consistent, quantitative information to assessments currently based on appearance alone. "There can be a huge lag time before doctors even figure out what is going on with the patient," Wong says. "Our goal is to shorten that process."

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Monitoring Network Traffic More Efficiently
MIT News
Larry Hardesty
August 23, 2017


Researchers at the Massachusetts Institute of Technology and their collaborators have developed Marple, a more efficient network traffic monitoring system designed to minimize the circuit complexity of the router and the number of external analytic servers. The system includes a programming language that lets network operators specify a broad spectrum of network-monitoring tasks and a small array of circuit elements that can carry out any task specified in the language. Simulations imply Marple should need only one traffic analysis server for every 40 or 50 application servers within a data center. Marple's underlying concept is to perform as much analysis on the router itself as possible without inducing network delays, and then sending external server summary statistics instead of raw packet data, therefore incurring major savings in bandwidth and processing time. The team unveiled their research this week at the ACM Special Interest Group on Data Communication (SIGCOMM 2017) conference in Los Angeles.

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Folder with the “confidential” label torn Journalists Successfully Used Secure Computing to Expose Panama Papers, Researchers Say
The Newsstand (SC)
August 17, 2017


Researchers at Clemson University, Columbia University, and the University of Washington (UW) say they have determined the journalists involved in the Panama Papers project have achieved their computer security goals. The Panama Papers project was a year-long collaborative investigation of leaked financial documents during which a large, diverse group of globally distributed journalists worked remotely via the Internet while maintaining the security of the project. "Success stories in computer security are rare," notes UW professor Franzi Roesner. Columbia University professor Susan McGregor says the researchers found the tools developed for the Panama Papers project were highly useful and usable, which motivated journalists to use the secure communication platforms provided by the International Consortium of Investigative Journalists. "This project is an example of the power of multi-disciplinary research," said Kelly Caine, director of Clemson's Humans and Technology Lab. "We couldn't have made these important discoveries without the expertise of everyone on the team."

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Secret Chips in Replacement Parts Can Completely Hijack Your Phone's Security
Ars Technica
Dan Goodin
August 18, 2017


Researchers at Ben-Gurion University of the Negev in Israel warn smartphone security can be compromised by repair shops that install replacement parts containing secret, malicious hardware. The research demonstrated that replacement touchscreens could be employed to secretly log passwords, install malware, and circumvent built-in security measures. In addition, the booby-trapped components could be indistinguishable from genuine hardware, facilitating undetectable installation and no signs of tampering. The team's proof of concept involved embedding a chip that manipulates the phone's communication bus in a touchscreen, to simulate a chip-in-the-middle attack. The chip has malware that surreptitiously executes tasks the end users never initiated, and it can deactivate the display panel to keep the user unaware. The researchers exploited Android smartphones for their demonstration, but they say tablets and phones running iOS also could be vulnerable to similar attacks. The researchers also offer hardware countermeasures manufacturers can deploy to shield devices from malicious screen-based hacks.

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Creating a Virtual Assistant for Software Engineers: It's All About a Common Language
Notre Dame News
Nina Welding
August 16, 2017


University of Notre Dame professor Collin McMillan's researchers are investigating source code summarization and the automatic generation of English descriptions of source code behavior, which they plan to apply to the development of a virtual assistant for software engineers. The goal of the three-year project is to produce a model of the dialogues between programmers, and from there devise expressions referring to software components in a human-like manner so they can program algorithms to extract the data to make similar references as part of a knowledge base, so the new virtual assistant could respond as quickly and precisely as commercially available assistants. The researchers also will assess their methods' effectiveness under laboratory and real-world conditions. They say the research will yield scientific knowledge of how coders ask and answer questions, new models for representing data in software projects, descriptions of software artifacts, and better comprehension of how persons with visual disabilities interact with software and its development.

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New Machine-Learning Program Shows Promise for Early Alzheimer's Diagnosis
The Daily (OH)
August 16, 2017


Researchers at Case Western Reserve University say they have developed a new machine-learning program that outperforms other methods in diagnosing Alzheimer's disease before symptoms become too severe. The researchers say the program integrates a range of Alzheimer's disease indicators, including mild cognitive impairment. In two successive stages, the algorithm selects the most relevant indicators to predict which patients have the disease. The researchers tested the algorithm using data from 149 patients collected via the Alzheimer's Disease Neuroimaging Initiative. The team says they developed a Cascaded Multi-view Canonical Correlation Algorithm, which integrates measurements from magnetic resonance imaging scans, features of the hippocampus, glucose metabolism rates in the brain, proteomics, genomics, mild cognitive impairment, and other parameters. The algorithm selects the parameters that best distinguish between healthy and unhealthy patients, and then it selects from the unhealthy variables those that best distinguish who has mild cognitive impairment and who has Alzheimer's disease.

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Why AI Visionary Andrew Ng Teaches Humans to Teach Computers
Associated Press
Ryan Nakashima
August 23, 2017


Stanford University professor Andrew Ng's current area of concentration is teaching next-generation artificial intelligence (AI) specialists to train computers. As a pioneer in such AI-training courses, Ng says he envisions AI as a tool to "free humanity from repetitive mental drudgery." He expects AI to have a transformative effect on virtually every industry, and eventually enable any job that takes less than a second of thought to become automated. Ng is an advocate of machine-learning neural networks, and his breakthrough in the field of AI was discovering a new way to give neural networks a significant performance boost by using chips typically found in video-game machines. Neural networks function much better if they can run thousands of calculations concurrently, an operation well suited to graphics-processing units. Ng and his Stanford team's research in this field was able to accelerate machine learning by as much as 70 times in 2008.

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