Posts Tagged ‘Data’

Simple Circuit Could Double Cell Phone Data Speeds

November 24th, 2014

A relatively simple circuit invented by researchers at the University of Texas could let smartphones and other wireless devices send and receive data twice as fast as they do now.

The circuit makes it possible for a radio to send and receive signals on the same channel simultaneously – something known as “full-duplex” communications. That should translate to a doubling of the rate at which information can be moved around wirelessly.

Today’s radios must send and receive at different times to avoid drowning out incoming signals with their own transmissions. As a smartphone accesses the Internet via a cell tower, for example, its radio flips back and forth between sending and receiving, similar way to the way two people having a conversation take turns to speak and listen.

The new circuit, known as a circulator, can isolate signals coming into a device from those it is sending out, acting as a kind of selective filter in between a device’s antenna and its radio circuitry. Circulators are already a crucial part of radar systems, but until now they have always been built using strong magnets made from rare earth metals, making them bulky and unsuited to the circuit boards inside devices such as laptops and smartphones.

The new circuit design avoids magnets, and uses only conventional circuit components. “It’s very cheap, compact, and light,” says Andrea Alù, the associate professor who led the work. “It’s ideal for a cell phone.”

The two-centimeter-wide device could easily be miniaturized and added to existing devices with little modification to the design. “This is just a standalone piece of hardware you put behind your antenna.”

Alù’s circulator design looks, and functions, like a traffic circle with three “roads,” in the form of wires, leading into it. Signals can travel into, or out of, the circle via any of those wires. But components called resonators spaced around that circle force signals to travel around it only in a clockwise direction.

When a wireless device’s antenna is connected to one of the wires leading into the circle, it isolates signals that have just been received from those the device has generated for transmission itself. The new design is described by Alù and colleagues in a paper in the journal Nature Physics.

“This is definitely a significant research development,” says Philip Levis, an associate professor at Stanford. “It’s a very new way to look at a very old problem, and has some very good results.” However Levis notes that work remains to be done to convert the lab-bench breakthrough into something practical for the crucial frequency bands used for Wi-Fi, cellular, and other communications.

Alù says that his circulator can easily be adjusted to work at a wide range of frequencies, and that he is exploring options for commercializing the design. The circuit could, for instance, help simplify and improve technology being tested by some U.S. and European cellular carriers that uses a combination of software and hardware to allow full-duplex radio links (see “The Clever Circuit That Doubles Bandwidth”).

Joel Brand, vice president for product management at startup Kumu Networks, which developed that technology, says the new device could indeed be useful. “We would be happy to take advantage of it,” he says.


Data-Toting Cops

November 18th, 2014

Mornings at 7:00, Wade Brabble has decisions to make. So in the last year, he has come to rely upon a computer-generated forecast of where crime will happen on his day shift as a police lieutenant in Fort Lauderdale, Florida. Depending on the report, which comes out of a system built in a year-old partnership with IBM, he’ll move his 15 patrol officers around, telling some to focus on hot spots while assigning routine calls to everyone else. “I base a lot of it on numbers,” he says.

Twenty years after the New York Police Department pioneered the idea with a program called CompStat, computerized crime analysis is moving to a new level. Back then, the innovation was a map tracking past crimes, which higher-ups used to hold district commanders accountable. Now the push is for widespread adoption of analytics that predict crime in close to real time, identifying target areas to within 250,000 square feet. Bigger data sets, commercially available analytics and forecasting software, and faster computers are driving the improvement, say the Rand Corporation’s John Hollywood and Walt Perry, authors of a 2013 report on the trend.

Critics like the Electronic Frontier Foundation, however, fear that such projects will promote racial profiling, and skeptics like Maria Haberfeld, a professor of criminal justice at John Jay College, think they are as likely to move crime a few blocks away as they are to prevent it.

Some big departments, like the Los Angeles Police Department, simply base predictions on data about past crime locations and time and type of crime, says UCLA anthropologist Jeff Brantingham, who is also cofounder of PredPol, the company that helped design the LAPD’s software. At the other extreme is Chicago, which has gone as far as using data to predict whether specific potential criminals may be involved in violence. Fort Lauderdale takes a middle path: it uses crime history but factors in details such as events that are expected to draw crowds, and even the likely impact of weather.

The analytics aren’t good enough to say a specific store will be hit on Tuesday, but they can predict a 70 percent chance of burglaries in one area, or a 40 percent chance of muggings somewhere else.

The approach seems to work—but as with any experiment in a living city, it’s hard to be certain why crime is down. In Fort Lauderdale, crimes like murder, robbery, larceny, and sexual assault fell 6 percent in the first eight months of 2014. Assistant police chief Michael Gregory says that in addition to the computer analytics, the department has implemented tactics such as distributing anti-theft kits in a burglary-prone neighborhood.

In Chicago, violent crime was down 13 percent year over year as of October, and the number of murders could be the lowest since 1965. Chicago’s “hot people” strategy was based on a list of the 400 Chicagoans, all with arrest records and connections to known criminals,that a computer model identified as most at risk of becoming either a perpetrator or a victim of violence, though it can’t predict which.

Since 2013, people on the list have been getting personal visits from local cops—usually the head of their precinct, according to Commander Jonathan Lewin, head of the department’s public-safety information technology unit. They’re handed a letter that explains the consequences of breaking the law and offers social services. The hot 400 are as much as 500 times more likely than average to be involved in a crime, Lewin says, and most of the data used to build the list has to do with the level of connectedness to criminals: “It does not—repeat, not—include gender or race.” There have been some problems, including reports that minor offenders were listed. Soon the list will be weighted by probation history, outstanding warrants, and record of narcotics and weapon possession.

Los Angeles eschews modeling aimed at identifying specific criminals, and Brantingham warns that nothing in predictive policing generates enough probable cause for a search warrant or justifies a stop-and-frisk. In the end, even the best systems can’t entirely replace human judgment.“It takes a little time for people to get out of the mind-set that it’s a cure-all,” Brabble says.

Video and social networks like Twitter are increasingly sources of data for analysis, and in time, systems with more decision support built in may be deployed as well, putting more data into the hands of officers using mobile devices and in-car computers in the field. One thing that won’t change: controversy over what kinds of data are relevant, and politically acceptable, to include in crime forecasting.


5 ways to protect yourself from data breaches

September 22nd, 2014

Data breaches at retailers aren’t going away but there are ways consumers can protect themselves from future heists of their payment card information.

Home Depot in the US said on Thursday that malicious software lurking in its check-out terminals between April and September affected 56 million debit and credit cards that customers swiped at its stores. Target, Michaels and Neiman Marcus have also been attacked by hackers in the past year.

More breaches are likely. The US Department of Homeland Security warned last month that more than 1,000 retailers could have malware in their cash-register computers.

Here are five ways to protect yourself:

1. Consider another way to pay

Try newer ways to pay, such as PayPal or Apple Pay.

“Any technology that avoids you having your credit card in your hand in a store is safer,” says Craig Young, security researcher for software maker Tripwire.

Those services store your credit card information and it’s not given to the retailer when you make a payment. Many big retailers, including Home Depot, accept PayPal at their stores, but many others don’t. Apple Pay, which was only introduced this month, has even more limitations: It is available in just a small number of stores so far and only people with an iPhone 6 can use it.

Stored-value cards or apps, such as the ones used at coffee chains Starbucks and Dunkin Donuts, are also a safer bet, says Gartner security analyst Avivah Litan. That’s because they don’t expose credit card information at the register.

2. Sign it, don’t pin it

If you’re planning on paying with a debit card, sign for your purchase instead of typing in your personal identification number at the cash register. You can do this by asking the cashier to process the card as a credit card or select credit card on the display. Not entering your PIN into a keypad will help reduce the chances of a hacker stealing that number too, Young says.

Crooks can do more damage with your PIN, possibly printing a copy of the card and taking money out of an ATM, he says. During Target’s breach last year, the discount retailer said hackers gained access to customers’ PINs. Home Depot, however, said there was no indication that PINs were compromised in the breach at its stores.

3. Beware of email scammers

After big data breaches are exposed, and get a lot of media attention, scammers come out of the woodwork looking to steal personal information. Some emails may mention Home Depot or offer free credit monitoring, but you should never click on the links. Many are for fake sites that try to steal bank information or passwords. “Avoid these entirely,” Young says. If an email looks credible, go to Home Depot’s site directly instead of clicking on links.

4. Keep up with statements

Scan credit card statements every month for any unauthorised charges. And keep an eye out for smaller charges. Thieves will charge smaller amounts to test to see if you notice and then charge a larger amount later, Litan says. They may also steal a small amount from millions of accounts, scoring a big payday, she says.

And check your credit report for any accounts that crooks may have opened in your name. Credit reports are available for free or for a reasonable charge if you want the information quickly. The following credit reporters operate in New Zealand – Veda Advantage, Dun and Bradstreet and Centrix. Home Depot in the United States is also offering free credit monitoring and identity protection services to customers. Customers can go to the company’s website for more information.

5. Go old school

Use cash. When possible, the safest bet is to not swipe a card at all. Even if security gets stronger at stores, hackers are likely to figure out a way around it. “It’s always a cat and mouse game,” Young says.


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