Some smartphone models more vulnerable to attack

New research from North Carolina State University shows that some smartphones specifically designed to support the Android mobile platform have incorporated additional features that can be used by hackers to bypass Android's security features, making them more vulnerable to attack. Android has the largest share of the smartphone market in the U.S.

"Some of these pre-loaded applications, or features, are designed to make the smartphones more user-friendly, such as features that notify you of missed calls or text messages," says Dr. Xuxian Jiang, an assistant professor of computer science at NC State and co-author of a paper describing the research. "The problem is that these pre-loaded apps are built on top of the existing Android architecture in such a way as to create potential 'backdoors' that can be used to give third-parties direct access to personal information or other phone features."

In essence, these pre-loaded apps can be easily tricked by hackers. For example, these "backdoors" can be used to record your phone calls, send text messages to premium numbers that will charge your account or even completely wipe out all of your settings.

The researchers have tested eight different smartphone models, including two "reference implementations" that were loaded only with Google's baseline Android software. "Google's reference implementations and the Motorola Droid were basically clean," Jiang says. "No real problems there."

However, five other models did not fare as well. HTC's Legend, EVO 4G and Wildfire S, Motorola's Droid X and Samsung's Epic 4G all had significant vulnerabilities -- with the EVO 4G displaying the most vulnerabilities.

The researchers notified manufacturers of the vulnerabilities as soon as they were discovered, earlier this year.

"If you have one of these phones, your best bet to protect yourself moving forward is to make sure you accept security updates from your vendor," Jiang says. "And avoid installing any apps that you don't trust completely."

Researchers now plan to test these vulnerabilities in other smartphone models and determine whether third-party firmware has similar vulnerabilities.

The paper, "Systematic Detection of Capability Leaks in Stock Android Smartphones," will be presented Feb. 7, 2012, at the 19th Network and Distributed System Security Symposium in San Diego, Calif. The paper was co-authored by Jiang and NC State Ph.D. students Michael Grace, Yajin Zhou and Zhi Wang. The research was supported by the National Science Foundation and the U.S. Army Research Office.

The full paper, with technical details, is available here.

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Samsung Galaxy S2 Sales Impressive And Set To Be Boosted By 2 New Models

There have been several superb mobile phones released over the past year but none have managed to eclipse the global success that has been achieved by the Samsung Galaxy S2. This high specification model has proved a hit across the globe thanks to a blend of cutting edge technology together with a slim and stylish look.

Since its release in April 2011 the Galaxy S2 has helped its predecessor the Galaxy S to achieve 30 million sales between them. In September it was announced that the S2 had already reached the 10 million mark and since that report the phone has been released in the US with plenty of media publicity. Main US networks AT&T, Sprint and T Mobile all offered packages on the phone and this has resulted in a further boost in sales figures for this popular model. Despite the popularity of the S2 the original Galaxy S is still selling well as a lower priced alternative. "Since its launch only five months ago, GALAXY S2 has seen tremendous sales success and garnered enthusiastic reviews from consumers and mobile industry watchers across the globe," said JK Shin, president of Samsung mobile communications. "This is in addition to the continued sales momentum behind GALAXY S, which we launched at Mobile World Congress 2010 as continues to be a run-away success with consumers.". And it seems the popularity of the Galaxy name is set to continue with the release of two new handsets in the range.

The Samsung Galaxy S2 will continue to run as the brands mains smartphone but it is joined by new arrivals in the shape of the Galaxy Note and the Galaxy R. The Galaxy Note is a larger screened version of the S2 that will strike a chord with multi media lovers but not replace the model as a mainstream hit thanks to its massive size. Boasting a 5.3 inch display the phone is almost a hybrid between a phone and a tablet device which offers massive advantage in areas such as video playback and gaming but lacks the portability of other models in the range. A powerful 1.4 Ghz processor ensures the model performs at lightning fast speeds and an 8 million pixel camera means the device will appeal to camera enthusiasts. The Samsung Galaxy R will sit slightly lower than the Galaxy S2 in the range a prove a great option for anybody looking for the smartphone experience at a more budget price. The phone features a 1Ghz processor together with a high quality 4.2 inch display. Media wise the phone offers a 5 million pixel main camera and a 2 mega pixel front facing camera perfect for self portraits and video calling.

It is easy to see why the Samsung Galaxy S2 has been such a runaway success. The addition of the two new models to the range will further cement the Galaxy's position as the ultimate smartphone family.

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Mimicking the brain -- in silicon: New computer chip models how neurons communicate with each other at synapses

ScienceDaily (Nov. 15, 2011) — For decades, scientists have dreamed of building computer systems that could replicate the human brain's talent for learning new tasks.

MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain's neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.

With about 400 transistors, the silicon chip can simulate the activity of a single brain synapse -- a connection between two neurons that allows information to flow from one to the other. The researchers anticipate this chip will help neuroscientists learn much more about how the brain works, and could also be used in neural prosthetic devices such as artificial retinas, says Chi-Sang Poon, a principal research scientist in the Harvard-MIT Division of Health Sciences and Technology.

Poon is the senior author of a paper describing the chip in the Proceedings of the National Academy of Sciences the week of Nov. 14. Guy Rachmuth, a former postdoc in Poon's lab, is lead author of the paper. Other authors are Mark Bear, the Picower Professor of Neuroscience at MIT, and Harel Shouval of the University of Texas Medical School.

Modeling synapses

There are about 100 billion neurons in the brain, each of which forms synapses with many other neurons. A synapse is the gap between two neurons (known as the presynaptic and postsynaptic neurons). The presynaptic neuron releases neurotransmitters, such as glutamate and GABA, which bind to receptors on the postsynaptic cell membrane, activating ion channels. Opening and closing those channels changes the cell's electrical potential. If the potential changes dramatically enough, the cell fires an electrical impulse called an action potential.

All of this synaptic activity depends on the ion channels, which control the flow of charged atoms such as sodium, potassium and calcium. Those channels are also key to two processes known as long-term potentiation (LTP) and long-term depression (LTD), which strengthen and weaken synapses, respectively.

The MIT researchers designed their computer chip so that the transistors could mimic the activity of different ion channels. While most chips operate in a binary, on/off mode, current flows through the transistors on the new brain chip in analog, not digital, fashion. A gradient of electrical potential drives current to flow through the transistors just as ions flow through ion channels in a cell.

"We can tweak the parameters of the circuit to match specific ion channels," Poon says. "We now have a way to capture each and every ionic process that's going on in a neuron."

Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. "If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based," Poon says.

The new chip represents a "significant advance in the efforts to incorporate what we know about the biology of neurons and synaptic plasticity onto CMOS [complementary metal-oxide-semiconductor] chips," says Dean Buonomano, a professor of neurobiology at the University of California at Los Angeles, adding that "the level of biological realism is impressive.

The MIT researchers plan to use their chip to build systems to model specific neural functions, such as the visual processing system. Such systems could be much faster than digital computers. Even on high-capacity computer systems, it takes hours or days to simulate a simple brain circuit. With the analog chip system, the simulation is even faster than the biological system itself.

Another potential application is building chips that can interface with biological systems. This could be useful in enabling communication between neural prosthetic devices such as artificial retinas and the brain. Further down the road, these chips could also become building blocks for artificial intelligence devices, Poon says.

Debate resolved

The MIT researchers have already used their chip to propose a resolution to a longstanding debate over how LTD occurs.

One theory holds that LTD and LTP depend on the frequency of action potentials stimulated in the postsynaptic cell, while a more recent theory suggests that they depend on the timing of the action potentials' arrival at the synapse.

Both require the involvement of ion channels known as NMDA receptors, which detect postsynaptic activation. Recently, it has been theorized that both models could be unified if there were a second type of receptor involved in detecting that activity. One candidate for that second receptor is the endo-cannabinoid receptor.

Endo-cannabinoids, similar in structure to marijuana, are produced in the brain and are involved in many functions, including appetite, pain sensation and memory. Some neuroscientists had theorized that endo-cannabinoids produced in the postsynaptic cell are released into the synapse, where they activate presynaptic endo-cannabinoid receptors. If NMDA receptors are active at the same time, LTD occurs.

When the researchers included on their chip transistors that model endo-cannabinoid receptors, they were able to accurately simulate both LTD and LTP. Although previous experiments supported this theory, until now, "nobody had put all this together and demonstrated computationally that indeed this works, and this is how it works," Poon says.

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The above story is reprinted from materials provided by Massachusetts Institute of Technology. The original article was written by Anne Trafton, MIT News Office.

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Mimicking the brain -- in silicon: New computer chip models how neurons communicate with each other at synapses

ScienceDaily (Nov. 15, 2011) — For decades, scientists have dreamed of building computer systems that could replicate the human brain's talent for learning new tasks.

MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain's neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.

With about 400 transistors, the silicon chip can simulate the activity of a single brain synapse -- a connection between two neurons that allows information to flow from one to the other. The researchers anticipate this chip will help neuroscientists learn much more about how the brain works, and could also be used in neural prosthetic devices such as artificial retinas, says Chi-Sang Poon, a principal research scientist in the Harvard-MIT Division of Health Sciences and Technology.

Poon is the senior author of a paper describing the chip in the Proceedings of the National Academy of Sciences the week of Nov. 14. Guy Rachmuth, a former postdoc in Poon's lab, is lead author of the paper. Other authors are Mark Bear, the Picower Professor of Neuroscience at MIT, and Harel Shouval of the University of Texas Medical School.

Modeling synapses

There are about 100 billion neurons in the brain, each of which forms synapses with many other neurons. A synapse is the gap between two neurons (known as the presynaptic and postsynaptic neurons). The presynaptic neuron releases neurotransmitters, such as glutamate and GABA, which bind to receptors on the postsynaptic cell membrane, activating ion channels. Opening and closing those channels changes the cell's electrical potential. If the potential changes dramatically enough, the cell fires an electrical impulse called an action potential.

All of this synaptic activity depends on the ion channels, which control the flow of charged atoms such as sodium, potassium and calcium. Those channels are also key to two processes known as long-term potentiation (LTP) and long-term depression (LTD), which strengthen and weaken synapses, respectively.

The MIT researchers designed their computer chip so that the transistors could mimic the activity of different ion channels. While most chips operate in a binary, on/off mode, current flows through the transistors on the new brain chip in analog, not digital, fashion. A gradient of electrical potential drives current to flow through the transistors just as ions flow through ion channels in a cell.

"We can tweak the parameters of the circuit to match specific ion channels," Poon says. "We now have a way to capture each and every ionic process that's going on in a neuron."

Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. "If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based," Poon says.

The new chip represents a "significant advance in the efforts to incorporate what we know about the biology of neurons and synaptic plasticity onto CMOS [complementary metal-oxide-semiconductor] chips," says Dean Buonomano, a professor of neurobiology at the University of California at Los Angeles, adding that "the level of biological realism is impressive.

The MIT researchers plan to use their chip to build systems to model specific neural functions, such as the visual processing system. Such systems could be much faster than digital computers. Even on high-capacity computer systems, it takes hours or days to simulate a simple brain circuit. With the analog chip system, the simulation is even faster than the biological system itself.

Another potential application is building chips that can interface with biological systems. This could be useful in enabling communication between neural prosthetic devices such as artificial retinas and the brain. Further down the road, these chips could also become building blocks for artificial intelligence devices, Poon says.

Debate resolved

The MIT researchers have already used their chip to propose a resolution to a longstanding debate over how LTD occurs.

One theory holds that LTD and LTP depend on the frequency of action potentials stimulated in the postsynaptic cell, while a more recent theory suggests that they depend on the timing of the action potentials' arrival at the synapse.

Both require the involvement of ion channels known as NMDA receptors, which detect postsynaptic activation. Recently, it has been theorized that both models could be unified if there were a second type of receptor involved in detecting that activity. One candidate for that second receptor is the endo-cannabinoid receptor.

Endo-cannabinoids, similar in structure to marijuana, are produced in the brain and are involved in many functions, including appetite, pain sensation and memory. Some neuroscientists had theorized that endo-cannabinoids produced in the postsynaptic cell are released into the synapse, where they activate presynaptic endo-cannabinoid receptors. If NMDA receptors are active at the same time, LTD occurs.

When the researchers included on their chip transistors that model endo-cannabinoid receptors, they were able to accurately simulate both LTD and LTP. Although previous experiments supported this theory, until now, "nobody had put all this together and demonstrated computationally that indeed this works, and this is how it works," Poon says.

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The above story is reprinted from materials provided by Massachusetts Institute of Technology. The original article was written by Anne Trafton, MIT News Office.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Note: If no author is given, the source is cited instead.

Disclaimer: This article is not intended to provide medical advice, diagnosis or treatment. Views expressed here do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Laptop Models

Laptops originally had one purpose – to enable the user to work from a wider variety of locations with ease. Once manufacturers found that more than just business people were interested in purchasing laptops, the interest in improved designs and more variety in the types of laptops available increased. Laptop development and improvements make it easy for anyone to select a laptop to match their needs.

source from about.com