Ex-tech pleads guilty to smart meter network attack


Some beers, anger at former employer, and root access add up to a year in prison

Ex-tech pleads guilty to smart meter network attack; changed a password to “f***you.”

Millions of homeowners reject smart meters over hacking fear

Millions of homeowners reject smart meters over hacking fear

June 26 2017, 12:01am, The Times

The government has promised that smart meters will cut energy bills
The government has promised that smart meters will cut energy billsGETTY IMAGES

Concerns over cybersecurity are undermining the nationwide introduction of smart meters, with more than one in five people saying they do not want one.

Almost six million homes would reject the devices despite government promises that they would cut energy bills, according to a survey of attitudes to Britain’s biggest infrastructure project in a generation. More than half of those who oppose smart meters said that their principal concern was data protection.

The government has promised that every home in Britain would be offered a smart meter by 2020. The devices are connected to the internet and track energy usage in real time, allowing customers to better understand their consumption patterns. They would eventually cut the time it takes to switch supplier from six weeks…


What Does Your Smart Meter Know About You?

What Does Your Smart Meter Know About You?

a smart meter
Photo: iStockphoto

An ordinary smart meter gives your local utility useful information about how much energy you are using—every hour, or even as often as every minute. This helps utility planners efficiently adjust electricity generation to meet demand or encourage reductions in demand when necessary.

But machine learning systems, looking at that data, can tell something else about your home besides its energy use—they can tell if you are home, or if you are not. That’s what University of California at Berkeley researchers Ming Jin, Ruoxi Jia, and Costas Spanos found out. That information, Jin says, is also useful for utilities—they can call or show up to perform necessary maintenance when you are home, and not waste personnel time trying to reach you.

SEE ALSO: Want to Know What's Happening in a Building? Listen in at the Breaker Box

But they aren’t the only ones who can access this information, given the data is transmitted wirelessly, and isn’t necessarily encrypted at every stage of its journey.

“If you know a person is home, as an advertiser, you can make a phone call. If you know a person isn’t home, that information could be used for home intrusion or other bad activities,” Jin says.

In a recent paper, Jin and his colleagues demonstrated that machine learning systems can be trained to detect occupancy without any initial information from a home owner. “You just need a smart meter that listens over time,” he says, “as well as the basic assumption that different types of buildings have different occupancy patterns, for example, commercial buildings are typically occupied during the day and not the night and homes are the opposite.” Using this assumption, the machine learning algorithms were able to tease out more detailed characteristics about power consumption when a home is occupied; they then are able to tell when someone is home or not, even when that person’s patterns are outside the norm.

How to keep occupancy data private and still provide the information utilities need to manage their grids is the next area of research, Jin says. “Right now, meters are sending accurate information about energy consumption. To protect privacy, you could add some noise to that data. We are now looking to determine the optimal size of the added noise that would mask information about occupancy and still give the utility company an accurate enough reading for its needs.”


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