Physical abuse at home doesn’t just leave kids black and blue. It also bruises their ability to learn how to act at school and elsewhere, contributing to abused children’s well-documented behavior problems.

Derailment of a basic form of social learning has, for the first time, been linked to these children’s misbehavior years down the line, psychologist Jamie Hanson of the University of Pittsburgh and colleagues report February 3 in the Journal of Child Psychology and Psychiatry. Experiments indicate that physically abused kids lag behind their nonabused peers when it comes to learning to make choices that consistently lead to a reward, even after many trials.
“Physically abused kids fail to adjust flexibly to new behavioral rules in contexts outside their families,” says coauthor Seth Pollak, a psychologist at the University of Wisconsin–Madison. Youth who have endured hitting, choking and other bodily assaults by their parents view the world as a place where hugs and other gratifying responses to good behavior occur inconsistently, if at all. So these youngsters stick to what they learned early in life from volatile parents — rewards are rare and unpredictable, but punishment is always imminent. Kids armed with this expectation of futility end up fighting peers on the playground and antagonizing teachers, Pollak says.

If the new finding holds up, it could lead to new educational interventions for physically abused youth, such as training in how to distinguish safe from dangerous settings and in how to control impulses, Pollak says. Current treatments focus on helping abused children feel safe and less anxious.

More than 117,000 U.S. children were victims of documented physical abuse in 2015, the latest year for which data are available.

“Inflexible reward learning is one of many possible pathways from child maltreatment to later behavior problems,” says Stanford University psychologist Kathryn Humphreys, who did not participate in the new study. Other possible influences on physically abused kids’ disruptive acts include a heightened sensitivity to social stress and a conviction that others always have bad intentions, Humphreys suggests.

Hanson’s team studied 41 physically abused and 40 nonabused kids, ages 12 to 17. Participants came from various racial backgrounds and lived with their parents in poor or lower middle-class neighborhoods. All the youth displayed comparable intelligence and school achievement.
In one experiment, kids saw a picture of a bell or a bottle and were told to choose one to earn points to trade in for toys. Kids who accumulated enough points could select any of several desirable toys displayed in the lab, including a chemistry set and a glow-in-the-dark model of the solar system. Fewer points enabled kids to choose plainer toys, such as a Frisbee or colored pencils.

Over 100 trials, one picture chosen at random by the researchers at the start of the experiment resulted in points 80 percent of the time. The other picture yielded points 20 percent of the time. In a second round of 100 trials using pictures of a bolt and a button, one randomly chosen image resulted in points 70 percent of the time versus 30 percent for the other image.

Both groups chose higher-point images more often as trials progressed, indicating that all kids gradually learned images’ values. But physically abused kids lagged behind: They chose the more-rewarding image on an average of 131 out of 200 trials, compared with 154 out of 200 trials for nonabused youth. The abused kids were held back by what they had learned at home, Pollak suspects.

Welcome to the somewhat civilized jungle. Plant cultivation by native groups has shaped the landscape of at least part of South America’s Amazon forests for more than 8,000 years, researchers say.

Of dozens of tree species partly or fully domesticated by ancient peoples, 20 kinds of fruit and nut trees still cover large chunks of Amazonian forests, say ecologist Carolina Levis of the National Institute for Amazonian Research in Manaus, Brazil, and colleagues. Numbers and variety of domesticated tree species increase on and around previously discovered Amazonian archaeological sites, the scientists report in the March 3 Science.
Domesticated trees are “a surviving heritage of the Amazon’s past inhabitants,” Levis says.

The new report, says archaeologist Peter Stahl of the University of Victoria in Canada, adds to previous evidence that “resourceful and highly developed indigenous cultures” intentionally altered some Amazonian forests.

Southwestern and northwestern Amazonian forests contain the greatest numbers and diversity of domesticated tree species, Levis’ team found. Large stands of domesticated Brazil nut trees remain crucial resources for inhabitants of southwestern forests today.

Over the past 300 years, modern Amazonian groups may have helped spread some domesticated tree species, Levis’ group says. For instance, 17th century v­oyagers from Portugal and Spain established plantations of cacao trees in southwestern Amazonian forests that exploited cacao trees already cultivated by local communities, the scientists propose.

Their findings build on a 2013 survey of forest plots all across the Amazon led by ecologist and study coauthor Hans ter Steege of the Naturalis Biodiversity Center in Leiden, the Netherlands. Of approximately 16,000 Amazonian tree species, just 227 accounted for half of all trees, the 2013 study concluded.
Of that number, 85 species display physical features signaling partial or full domestication by native Amazonians before European contact, the new study finds. Studies of plant DNA and plant remains from the Amazon previously suggested that domestication started more than 8,000 years ago. Crucially, 20 domesticated tree species — five times more than the number expected by chance — dominate their respective Amazonian landscapes, especially near archaeological sites and rivers where ancient humans likely congregated, Levis’ team says.

Archaeologists, ecologists and crop geneticists have so far studied only a small slice of the Amazon, which covers an area equivalent to about 93 percent of the contiguous U.S. states.

Levis and her colleagues suspect ancient native groups domesticated trees and plants throughout much of the region. But some researchers, including ecologist Crystal McMichael of the University of Amsterdam, say it’s more likely that ancient South Americans domesticated trees just in certain parts of the Amazon. In the new study, only Brazil nut trees show clear evidence of expansion into surrounding forests from an area of ancient domestication, McMichael says. Other tree species may have mainly been domesticated by native groups or Europeans in the past few hundred years, she says.

Scientists have created an ultrasecure form of money using quantum mechanics — and immediately demonstrated a potential security loophole.

Under ideal conditions, quantum currency is impossible to counterfeit. But thanks to the messiness of reality, a forger with access to sophisticated equipment could skirt that quantum security if banks don’t take appropriate precautions, scientists report March 1 in npj Quantum Information. Quantum money as a concept has been around since the 1970s, but this is the first time anyone has created and counterfeited quantum cash, says study coauthor Karel Lemr, a quantum physicist at Palacký University Olomouc in the Czech Republic.
Instead of paper banknotes, the researchers’ quantum bills are minted in light. To transfer funds, a series of photons — particles of light — would be transmitted to a bank using the photons’ polarizations, the orientation of their electromagnetic waves, to encode information. (The digital currency Bitcoin is similar in that there’s no bill you can hold in your hand. But quantum money has an extra layer of security, backed by the power of quantum mechanics.)

To illustrate their technique in a fun way, the researchers transmitted a pixelated picture of a banknote — an old Austrian bill depicting famed quantum physicist Erwin Schrödinger — using photons’ polarizations to stand for grayscale shades. In a real quantum money system, each bill would be different and the photon polarizations would be distributed randomly, rather than forming a picture. The polarizations would create a serial number–like code the bank could check to verify that the funds are legit.

A criminal intercepting the photons couldn’t copy them accurately because quantum information can’t be perfectly duplicated. “This is actually the cornerstone of security of quantum money,” says Lemr.
But the realities of dealing with quantum particles complicate matters. Because single photons are easily lost or garbled during transmission, banks would have to accept partial quantum bills, analogous to a dollar with a corner torn off. That means a crook might be able to make forgeries that aren’t perfect, but are good enough to pass muster.
Lemr and colleagues used an optimal cloner, a device that comes as close as possible to copying quantum information, to attempt a fake. The researchers showed that a bank would accept a forged bill if the standard for accuracy wasn’t high enough — more than about 84 percent of the received photons’ polarizations must match the original.

Previously, this vulnerability “wasn’t explicitly pointed out, but it’s not surprising,” says theoretical computer scientist Thomas Vidick of Caltech, who was not involved in the research. The result, he says, indicates that banks must be stringent enough in their standards to prove the bills they receive are real.

Americans don’t hate science. Quite the contrary. In fact, 79 percent of Americans think science has made their lives easier, a 2014 Pew Research Center survey found. More than 60 percent of people also believe that government funding for science is essential to its success.

But should the United States spend more money on scientific research than it already does? A layperson’s answer to that question depends on how much that person thinks the government already spends on science, a new study shows. When people find out just how much — or rather, how little — of the federal budget goes to science, support for more funding suddenly jumps.

To see how people’s opinions of public science spending were influenced by accurate information, mechanical engineer Jillian Goldfarb and political scientist Douglas Kriner, both at Boston University, placed a small experiment into the 2014 Cooperative Congressional Election Study. The online survey was given to 1,000 Americans, carefully selected to represent the demographics of the United States. The questions were designed to be nonpartisan, and the survey itself was conducted in 2014, long before the 2016 election.

The survey was simple. First, participants were asked to estimate what percentage of the federal budget was spent on scientific research. Once they’d guessed, half of the participants were told the actual amount that the federal government allocates for nondefense spending on research and development. In 2014, that figure was 1.6 percent of the budget, or about $67 billion. Finally, all the participants were asked if federal spending on science should be increased, decreased or kept the same.

The majority of participants had no idea how much money the government spends on science, and wildly overestimated the actual amount. About half of the respondents estimated federal spending for research at somewhere between 5 and 20 percent of the budget. A quarter of participants estimated that figure was 20 percent of the budget — one very hefty chunk of change. The last 25 percent of respondents estimated that 1 to 2 percent of federal spending went to science.

When participants received no information about how much the United States spent on research, only about 40 percent of them supported more funding. But when they were confronted with the real numbers, support for more funding leapt from 40 to 60 percent.

Those two numbers hover on either side of 50 percent, but Kriner notes, “media coverage [would] go from ‘minority’ to ‘majority’” in favor of more funding — a potentially powerful message. What’s more, the support for science was present in Democrats and Republicans alike, Kriner and Goldfarb report February 1 in Science Communication.
“I think it contributes to our understanding of the aspects of federal spending that people don’t understand very well,” says Brendan Nyhan, a political scientist at Dartmouth University in Hanover, N.H. It’s not surprising that most people don’t know how much the government is spending on research. Nyhan points out that most people probably don’t know how much the government spends on education or foreign aid either.

When trying to gather more support for science funding, Goldfarb says, “tell people how little we spend, and how much they get in return.” Science as a whole isn’t that controversial. No one wants to stop exploring the universe or curing diseases, after all.

But when people — whether politicians or that guy in your Facebook feed — say they want to cut science funding, they won’t be speaking about science as a whole. “There’s a tendency to overgeneralize” and use a few controversial or perceived-to-be-wasteful projects to stand in for all of science, Nyhan warns.

When politicians want to cut funding, he notes, they focus on specific controversial studies or areas — such as climate change, stem cells or genetically modified organisms. They might highlight studies that seem silly, such as those that ended up in former Senator Tom Coburn’s “Wastebook,” (a mantle now taken up Senator Jeff Flake). Take those issues to the constituents, and funding might end up in jeopardy anyway.

Kriner hopes their study’s findings might prove useful even for controversial research areas. “One of the best safeguards against cuts is strong public support for a program,” he explains. “Building public support for science spending may help insulate it from budget cuts — and our research suggests a relatively simple way to increase public support for scientific research.”

But he worries that public support may not stay strong if science becomes too much of a political pawn. The study showed that both Republicans and Democrats supported more funding for science when they knew how little was spent. But “if the current administration increases its attacks on science spending writ large … it could potentially politicize federal support for all forms of scientific research,” Kriner says. And the stronger the politics, the more people on both sides of the aisle grow resistant to hearing arguments from the other side.

Politics aside, Goldfarb and Kriner’s data show that Americans really do like and support science. They want to pay for it. And they may even want to shell out some more money, when they know just how little they already spend.

The mystery of why birds’ eggs come in so many shapes has long been up in the air. Now new research suggests adaptations for flight may have helped shape the orbs.

Stronger fliers tend to lay more elongated eggs, researchers report in the June 23 Science. The finding comes from the first large analysis of the way egg shape varies across bird species, from the almost perfectly spherical egg of the brown hawk owl to the raindrop-shaped egg of the least sandpiper.
“Eggs fulfill such a specific role in birds — the egg is designed to protect and nourish the chick. Why there’s such diversity in form when there’s such a set function was a question that we found intriguing,” says study coauthor Mary Caswell Stoddard, an evolutionary biologist at Princeton University.

Previous studies have suggested many possible advantages for different shapes. Perhaps cone-shaped eggs are less likely to roll out of the nest of cliff-dwelling birds; spherical eggs might be more resilient to damage in the nest. But no one had tested such hypotheses across a wide spectrum of birds.

Stoddard and her team analyzed almost 50,000 eggs from 1,400 species, representing about 14 percent of known bird species. The researchers boiled each egg down to its two-dimensional silhouette and then used an algorithm to describe each egg using two variables: how elliptical versus spherical the egg is and how asymmetrical it is — whether it’s pointier on one end than the other.

Next, the researchers looked at the way these two traits vary across the bird family tree. One pattern jumped out: Species that are stronger fliers, as measured by wing shape, tend to lay more elliptical or asymmetrical eggs, says study coauthor L. Mahadevan, a mathematician and biologist at Harvard University.
Mahadevan cautions that the data show only an association, but the researchers propose one possible explanation for the link between flying and egg shape. Adapting to flight streamlined bird bodies, perhaps also narrowing the reproductive tract. That narrowing would have limited the width of an egg that a female could lay. But since eggs provide nutrition for the chick growing inside, shrinking eggs too much would deprive the developing bird. Elongated eggs might have been a compromise between keeping egg volume up without increasing girth, Stoddard suggests. Asymmetry can increase egg volume in a similar way.

Testing a causal connection between flight ability and egg shape is tough “because of course we can’t replay the whole tape of life again,” says Claire Spottiswoode, a zoologist at the University of Cambridge who wrote a commentary accompanying the study. Still, Spottiswoode says the evidence is compelling: “It’s a very plausible argument.”

Santiago Claramunt, associate curator of ornithology at the Royal Ontario Museum in Toronto, isn’t convinced that flight adaptations played a driving role in the evolution of egg shape. “Streamlining in birds is determined more by plumage than the shape of the body — high performing fliers can have rounded, bulky bodies” he says, which wouldn’t give elongated eggs the same advantage over other egg shapes. He cites frigate birds and swifts as examples, both of which make long-distance flights but have fairly broad bodies. “There’s certainly more going on there.”

Indeed, some orders of birds showed a much stronger link between flying and egg shape than others did. And while other factors — like where birds lay their eggs and how many they lay at once — weren’t significantly related to egg shape across birds as a whole, they could be important within certain branches of the bird family tree.

When my younger daughter was around 6 months old, we gave her mashed up prune. She grimaced and shivered a little, appearing to be absolutely disgusted. But then she grunted and reached for more.

Most babies are ready for solid food around 6 months of age, and feeding them can be fun. One of the more entertaining approaches does not involve a spoon. Called baby-led weaning, it involves allowing babies to feed themselves appropriate foods.

Proponents of the approach say that babies become more skilled eaters when allowed to explore on their own. They’re in charge of getting food into their own mouths, gumming it and swallowing it down — all skills that require muscle coordination. When the right foods are provided (yes to soft steamed broccoli; no to whole grapes), babies who feed themselves are no more likely to choke than their spoon-fed peers.

Some baby-led weaning proponents also suspected that the method might ward off obesity, and a small study suggested as much. The idea is that babies allowed to feed themselves might better learn how to regulate their food intake, letting hunger and fullness guide them to a reasonable calorie count. But a new study that looked at the BMIs of babies who fed themselves and those who didn’t found that babies grew similarly with either eating style.

A clinical trial of about 200 mother-baby pairs in New Zealand tracked two different approaches to eating and their impact on weight. Half of the moms were instructed to feed their babies as they normally would, which for most meant spoon-feeding their babies purees, at least early on. The other half was instructed that only breast milk or formula was best until 6 months of age, and after that, babies could be encouraged to feed themselves. These mothers also received breastfeeding support.

At the 1- and 2-year marks, the babies’ average BMI z-scores were similar, regardless of feeding method, researchers report July 10 in JAMA Pediatrics. (A BMI z-score takes age and sex into account.) And baby-led weaning actually produced slightly more overweight babies than the other approaches, but not enough to be meaningful. At age 2, 10.3 percent of baby-led weaning babies were considered overweight and 6.4 percent of traditionally-fed babies were overweight. The two groups of babies seemed to take in about the same energy from food, analyses of the nutritional value and amount of food eaten revealed.

The trial found a few other differences between the two groups. Babies who did baby-led weaning exclusively breastfed for longer, a median of about 22 weeks. Babies in the other group were exclusively breastfed for a median of about 17 weeks. Babies in the baby-led weaning group were also more likely to have held off on solid food until 6 months of age.

While baby-led weaning may not protect babies against being overweight, the study did uncover a few perks of the approach. Parents reported that babies who fed themselves seemed less fussy about foods. These babies also reportedly enjoyed eating more (though my daughter’s prune fake-out face is evidence that babies’ inner opinions can be hard to read). Even so, these data seem to point toward a more positive experience all around when using the baby-led weaning approach. That’s ideal for both experience-hungry babies and the parents who get to savor watching them eat.

Consider everything your smartphone has done for you today. Counted your steps? Deposited a check? Transcribed notes? Navigated you somewhere new?

Smartphones make for such versatile pocket assistants because they’re equipped with a suite of sensors, including some we may never think — or even know — about, sensing, for example, light, humidity, pressure and temperature.

Because smartphones have become essential companions, those sensors probably stayed close by throughout your day: the car cup holder, your desk, the dinner table and nightstand. If you’re like the vast majority of American smartphone users, the phone’s screen may have been black, but the device was probably on the whole time.

“Sensors are finding their ways into every corner of our lives,” says Maryam Mehrnezhad, a computer scientist at Newcastle University in England. That’s a good thing when phones are using their observational dexterity to do our bidding. But the plethora of highly personal information that smartphones are privy to also makes them powerful potential spies.
Online app store Google Play has already discovered apps abusing sensor access. Google recently booted 20 apps from Android phones and its app store because the apps could — without the user’s knowledge — record with the microphone, monitor a phone’s location, take photos, and then extract the data. Stolen photos and sound bites pose obvious privacy invasions. But even seemingly innocuous sensor data can potentially broadcast sensitive information. A smartphone’s movement may reveal what users are typing or disclose their whereabouts. Even barometer readings that subtly shift with increased altitude could give away which floor of a building you’re standing on, suggests Ahmed Al-Haiqi, a security researcher at the National Energy University in Kajang, Malaysia.

These sneaky intrusions may not be happening in real life yet, but concerned researchers in academia and industry are working to head off eventual invasions. Some scientists have designed invasive apps and tested them on volunteers to shine a light on what smartphones can reveal about their owners. Other researchers are building new smartphone security systems to help protect users from myriad real and hypothetical privacy invasions, from stolen PIN codes to stalking.

Message revealed
Motion detectors within smartphones, like the accelerometer and the rotation-sensing gyroscope, could be prime tools for surreptitious data collection. They’re not permission protected — the phone’s user doesn’t have to give a newly installed app permission to access those sensors. So motion detectors are fair game for any app downloaded onto a device, and “lots of vastly different aspects of the environment are imprinted on those signals,” says Mani Srivastava, an engineer at UCLA.

For instance, touching different regions of a screen makes the phone tilt and shift just a tiny bit, but in ways that the phone’s motion sensors pick up, Mehrnezhad and colleagues demonstrated in a study reported online April 2017 in the International Journal of Information Security. These sensors’ data may “look like nonsense” to the human eye, says Al-Haiqi, but sophisticated computer programs can discern patterns in the mess and match segments of motion data to taps on various areas of the screen.

For the most part, these computer programs are machine-learning algorithms, Al-Haiqi says. Researchers train them to recognize keystrokes by feeding the programs a bunch of motion sensor data labeled with the key tap that produces particular movement. A pair of researchers built TouchLogger, an app that collects orientation sensor data and uses the data to deduce taps on smartphones’ number keyboards. In a test on HTC phones, reported in 2011 in San Francisco at the USENIX Workshop on Hot Topics in Security, TouchLogger discerned more than 70 percent of key taps correctly.

Since then, a spate of similar studies have come out, with scientists writing code to infer keystrokes on number and letter keyboards on different kinds of phones. In 2016 in Pervasive and Mobile Computing, Al-Haiqi and colleagues reviewed these studies and concluded that only a snoop’s imagination limits the ways motion data could be translated into key taps. Those keystrokes could divulge everything from the password entered on a banking app to the contents of an e-mail or text message.

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A more recent application used a whole fleet of smartphone sensors — including the gyroscope, accelerometer, light sensor and magnetism-measuring magnetometer — to guess PINs. The app analyzed a phone’s movement and how, during typing, the user’s finger blocked the light sensor. When tested on a pool of 50 PIN numbers, the app could discern keystrokes with 99.5 percent accuracy, the researchers reported on the Cryptology ePrint Archive in December.

Other researchers have paired motion data with mic recordings, which can pick up the soft sound of a fingertip tapping a screen. One group designed a malicious app that could masquerade as a simple note-taking tool. When the user tapped on the app’s keyboard, the app covertly recorded both the key input and the simultaneous microphone and gyroscope readings to learn the sound and feel of each keystroke.

The app could even listen in the background when the user entered sensitive info on other apps. When tested on Samsung and HTC phones, the app, presented in the Proceedings of the 2014 ACM Conference on Security and Privacy in Wireless and Mobile Networks, inferred the keystrokes of 100 four-digit PINs with 94 percent accuracy.

Al-Haiqi points out, however, that success rates are mostly from tests of keystroke-deciphering techniques in controlled settings — assuming that users hold their phones a certain way or sit down while typing. How these info-extracting programs fare in a wider range of circumstances remains to be seen. But the answer to whether motion and other sensors would open the door for new privacy invasions is “an obvious yes,” he says.

Tagalong
Motion sensors can also help map a person’s travels, like a subway or bus ride. A trip produces an undercurrent of motion data that’s discernible from shorter-lived, jerkier movements like a phone being pulled from a pocket. Researchers designed an app, described in 2017 in IEEE Transactions on Information Forensics and Security, to extract the data signatures of various subway routes from accelerometer readings.

In experiments with Samsung smartphones on the subway in Nanjing, China, this tracking app picked out which segments of the subway system a user was riding with at least 59, 81 and 88 percent accuracy — improving as the stretches expanded from three to five to seven stations long. Someone who can trace a user’s subway movements might figure out where the traveler lives and works, what shops or bars the person frequents, a daily schedule, or even — if the app is tracking multiple people — who the user meets at various places.
Accelerometer data can also plot driving routes, as described at the 2012 IEEE International Conference on Communication Systems and Networks in Bangalore, India. Other sensors can be used to track people in more confined spaces: One team synced a smartphone mic and portable speaker to create an on-the-fly sonar system to map movements throughout a house. The team reported the work in the September 2017 Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.

“Fortunately there is not anything like [these sensor spying techniques] in real life that we’ve seen yet,” says Selcuk Uluagac, an electrical and computer engineer at Florida International University in Miami. “But this doesn’t mean there isn’t a clear danger out there that we should be protecting ourselves against.”

That’s because the kinds of algorithms that researchers have employed to comb sensor data are getting more advanced and user-friendly all the time, Mehrnezhad says. It’s not just people with Ph.D.s who can design the kinds of privacy invasions that researchers are trying to raise awareness about. Even app developers who don’t understand the inner workings of machine-learning algorithms can easily get this kind of code online to build sensor-sniffing programs.

What’s more, smartphone sensors don’t just provide snooping opportunities for individual cybercrooks who peddle info-stealing software. Legitimate apps often harvest info, such as search engine and app download history, to sell to advertising companies and other third parties. Those third parties could use the information to learn about aspects of a user’s life that the person doesn’t necessarily want to share.

Take a health insurance company. “You may not like them to know if you are a lazy person or you are an active person,” Mehrnezhad says. “Through these motion sensors, which are reporting the amount of activity you’re doing every day, they could easily identify what type of user you are.”

Sensor safeguards
Since it’s only getting easier for an untrusted third party to make private inferences from sensor data, researchers are devising ways to give people more control over what information apps can siphon off of their devices. Some safeguards could appear as standalone apps, whereas others are tools that could be built into future operating system updates.

Uluagac and colleagues proposed a system called 6thSense, which monitors a phone’s sensor activity and alerts its owner to unusual behavior, in Vancouver at the August 2017 USENIX Security Symposium. The user trains this system to recognize the phone’s normal sensor behavior during everyday tasks like calling, Web browsing and driving. Then, 6thSense continually checks the phone’s sensor activity against these learned behaviors.

If someday the program spots something unusual — like the motion sensors reaping data when a user is just sitting and texting — 6thSense alerts the user. Then the user can check if a recently downloaded app is responsible for this suspicious activity and delete the app from the phone.

Uluagac’s team recently tested a prototype of the system: Fifty users trained Samsung smartphones with 6thSense to recognize their typical sensor activity. When the researchers fed the 6thSense system examples of benign data from daily activities mixed in with segments of malicious sensor operations, 6thSense picked out the problematic bits with over 96 percent accuracy.
For people who want more active control over their data, Supriyo Chakraborty, a privacy and security researcher at IBM in Yorktown Heights, N.Y., and colleagues devised DEEProtect, a system that blunts apps’ abilities to draw conclusions about certain user activity from sensor data. People could use DEEProtect, described in a paper posted online at arXiv.org in February 2017, to specify preferences about what apps should be allowed to do with sensor data. For example, someone may want an app to transcribe speech but not identify the speaker.

DEEProtect intercepts whatever raw sensor data an app tries to access and strips that data down to only the features needed to make user-approved inferences. For speech-to-text translation, the phone typically needs sound frequencies and the probabilities of particular words following each other in a sentence.

But sound frequencies could also help a spying app deduce a speaker’s identity. So DEEProtect distorts the dataset before releasing it to the app, leaving information on word orders alone, since that has little or no bearing on speaker identity. Users can control how much DEEProtect changes the data; more distortion begets more privacy but also degrades app functions.

In another approach, Giuseppe Petracca, a computer scientist and engineer at Penn State, and colleagues are trying to protect users from accidentally granting sensor access to deceitful apps, with a security system called AWare.

Apps have to get user permission upon first installation or first use to access certain sensors like the mic and camera. But people can be cavalier about granting those blanket authorizations, Uluagac says. “People blindly give permission to say, ‘Hey, you can use the camera, you can use the microphone.’ But they don’t really know how the apps are using these sensors.”

Instead of asking permission when a new app is installed, AWare would request user permission for an app to access a certain sensor the first time a user provided a certain input, like pressing a camera button. On top of that, the AWare system memorizes the state of the phone when the user grants that initial permission — the exact appearance of the screen, sensors requested and other information. That way, AWare can tell users if the app later attempts to trick them into granting unintended permissions.

For instance, Petracca and colleagues imagine a crafty data-stealing app that asks for camera access when the user first pushes a camera button, but then also tries to access the mic when the user later pushes that same button. The AWare system, also presented at the 2017 USENIX Security Symposium, would realize the mic access wasn’t part of the initial deal, and would ask the user again if he or she would like to grant this additional permission.

Petracca and colleagues found that people using Nexus smartphones equipped with AWare avoided unwanted authorizations about 93 percent of the time, compared with 9 percent among people using smartphones with typical first-use or install-time permission policies.

The price of privacy
The Android security team at Google is also trying to mitigate the privacy risks posed by app sensor data collection. Android security engineer Rene Mayrhofer and colleagues are keeping tabs on the latest security studies coming out of academia, Mayrhofer says.

But just because someone has built and successfully tested a prototype of a new smartphone security system doesn’t mean it will show up in future operating system updates. Android hasn’t incorporated proposed sensor safeguards because the security team is still looking for a protocol that strikes the right balance between restricting access for nefarious apps and not stunting the functions of trustworthy programs, Mayrhofer explains.

“The whole [app] ecosystem is so big, and there are so many different apps out there that have a totally legitimate purpose,” he adds. Any kind of new security system that curbs apps’ sensor access presents “a real risk of breaking” legitimate apps.

Tech companies may also be reluctant to adopt additional security measures because these extra protections can come at the cost of user friendliness, like AWare’s additional permissions pop-ups. There’s an inherent trade-off between security and convenience, UCLA’s Srivastava says. “You’re never going to have this magical sensor shield [that] gives you this perfect balance of privacy and utility.”

But as sensors get more pervasive and powerful, and algorithms for analyzing the data become more astute, even smartphone vendors may eventually concede that the current sensor protections aren’t cutting it. “It’s like cat and mouse,” Al-Haiqi says. “Attacks will improve, solutions will improve. Attacks will improve, solutions will improve.”

The game will continue, Chakraborty agrees. “I don’t think we’ll get to a place where we can declare a winner and go home.”

Don’t expect to play a game of Marco Polo by shouting from beneath the pool’s surface. No one will hear you because, normally, only about 0.1 percent of sound is transmitted from water to the air. But a new type of device might one day help.

Researchers have designed a new metamaterial — a type of material that behaves in ways conventional materials can’t — that increases sound transmission to 30 percent. The metamaterial could have applications for more than poolside play. A future version might be used to detect noisy marine life or listen in on sonar use, say applied physicist Oliver Wright of Hokkaido University in Sapporo, Japan, and a team at Yonsei University in Seoul, South Korea, who describe the metamaterial in a paper accepted to Physical Review Letters.
Currently, detection of underwater sounds happens with hydrophones, which have to be underwater. But what if you wanted to listen in from the surface?

Enter the new device. It’s a small cylinder with a weighted rubber membrane stretched across a metal frame that floats atop the water surface. When underwater sound waves hit the device, its frame and membrane vibrate at finely tuned frequencies to help sound transmit into the air.

“A ‘hard’ surface like a table or water reflects almost 100 percent of sound,” says Wright. “We want to try to mitigate that by introducing an intermediary structure.”
Both water and air resist the flow of sound, a property known as acoustic impedance. Because of its density, water’s acoustic impedance is 3,600 times that of air. The greater the mismatch, the more sound is reflected at a boundary.
Adding a layer of material one-fourth the thickness of an incoming wave’s wavelength can reduce the amount of reflection. This is the principle at work behind anti-reflective coatings applied to lenses of cameras and glasses. While optical light has a wavelength in the hundreds of nanometers, necessitating a thin coating only a few atoms thick, audible sound waves can be meters long.

Even though it’s only one-hundredth the thickness of the sound’s wavelength, instead of the conventional one-fourth, the metamaterial still transmits sound.

“It’s a tour de force of experimental demonstration,” says Oleg Godin, a physicist at the Naval Postgraduate School in Monterey, Calif., who was not involved with the research. “But I’m less impressed by the suggestions and implications about its uses. It’s wishful thinking.”

One major problem that the researchers would have to overcome is the device’s inability to transmit sound that hits the surface an angle. In the lab, the device is tested in a tube — effectively a one-direction environment. But on the vast surface of a lake or ocean, the device would be limited to transmitting sounds from the small area directly below it. Additionally, the metamaterial is limited to transmitting a narrow band of frequencies. Noise outside that range reflects off the water’s surface as usual.

Still, the scientists are optimistic about the next steps, and even propose that a sheet of these devices could work in concert.