Acer has begun developing and selling cloud-computing software and services. The Taiwan-based firm has long made PCs but has been hurt by that market’s contraction. In fact, the company’s ranking among the world’s PC makers recently fell from second to fourth. By entering the cloud market with its Build Your Own Cloud (BYOC) service, Acer will now compete with Amazon and Google, as well as Cisco Systems and Hewlett-Packard, the latter two of which which recently announced billion-dollar initiatives. “The computer is still our foundation, but BYOC is a new platform for integration, cross-compatibility, and convenience,” stated Acer founder and chair Stan Shih. The company is positioning the service for implementation with the Internet of Things by, for example, enabling users to control home appliances or automobiles via their smartphones. (Reuters)(AFP @ PhysOrg)
Wednesday, June 11, 2014
Saturday, March 23, 2013
Let’s Explore Quantum Computing
A quantum computer would be able to store more bits of information in its memory than there are particles in the universe. Image Credit: Alengo/iStockPhotoIt’s fairly easy to surmise how quantum computing will evolve in the future if/when it becomes a reality. Devices that are currently based around a system of electronic circuits would eventually die off. Quantum devices would ultimately become the new standard in computing. While Peter Shor’s research showed how quantum algorithms would speed up advanced calculations, they never really demonstrated why people would want to do this.
Today we have plenty of areas where quantum computing would certainly shine. Speed usually isn’t important when it comes to data storage and retrieval systems. Entertainment devices, however, are getting increasingly complex. This shouldn’t be taken as a suggestion that quantum computing would only be useful for a new generation of video game consoles, however.
Society would eventually start to merge all forms of media into one. Whether this would be the trigger to bring on the singularity is hard to say, but it’s easy to imagine that it would certainly usher in a very different form of art. Like the interactive media movement, quantum art would fundamentally change the way that people interact with the world.
Storage systems could still see a boost from the field of quantum computing as well. Electronic quantum holography also looks pretty promising. Holograms loaded with data could be projected onto a small mass. A piece of software could then reconstruct information from these holograms in the same way that software currently reconstructs data from magnetic or electrical impulses.
Some amount of energy would need to be expended to ensure that the holograms remain in a viable state. This shouldn’t be too much of a problem. Battery backup memory has worked that way for years. Even flash memory has to maintain a small amount of voltage to ensure that it works as desired. Electronic quantum holography could be viewed as the natural extension of these already proven examples of information technology.
Interestingly enough, no one has really been able to demonstrate the reason that quantum circuits would be superior to their regular electronic contemporaries. Most of what researchers believe is based wholly on assumptions/theory. While some people feel that quantum devices will never really replace microprocessors, it’s easy to imagine the microchip going the way of the vacuum tube. While transistors have almost completely replaced electronic valves, there remains few niche industries that continue to use them today.
On the totally other side of the spectrum, some people feel that quantum computers will someday be able to violate the basic theories of cognitive science. The idea of a self-aware machine has been bandied about for quite some time. When talking about the possibilities, it’s important to remember a few things. What currently defines a computer is at least in part based on the old Church-Turing thesis.
When this is violated, the whole idea of computational notions cease to be individual, autonomous units. Since quantum computers could solve equations that modern computers have found impossible, they force researchers to redefine the abstracts of efficient algorithms.
Superposition principles tell us that the bit is the smallest unit a machine can handle. A regular bit can only exhibit the features of one of two states. This is where the basic rules of binary math come from. Any single bit can be classified as 1 or 0. However, quantum computing defies these rules. By definition, a quantum computer is one that can handle bits assigned a third state. This state is somewhere between the two. Currently, computers can only tell if a circuit is switched on or not. A quantum computer would probably sense different voltages to ascribe values to some fraction of power. Some researchers use creative names like qubits to describe the components of quantum logic gates.
Quantum logic doesn’t even need to rely on electronics, however. Unconventional designs will probably evolve in the near future. Chemical computer systems, which are sometimes derisively referred to as gooware, would assign values to different chemical reactions. While it might seem weird to leave a tub of chemicals on a desk, practical designs might be closer to a dry cell battery. They could be quite small and portable.
Other logic systems have been proposed as well. Logic gates built around photons would allow nonlinear calculations. Photonic controlled gates would allow quantum computers to be built around electromagnetic models. Even with these types of advances however, future consumers would probably be more apt to buy something close to what they already know – at least in the early years of quantum computing. That makes photonic logic a good option for companies who want to pursue something they could actually market early on.
Reference:
Benningshof OW, Mohebbi HR, Taminiau IA, Miao GX, & Cory DG (2013). Superconducting microstrip resonator for pulsed ESR of thin films. Journal of magnetic resonance (San Diego, Calif. : 1997), 230C, 84-87 PMID: 23454577
Petersson KD, McFaul LW, Schroer MD, Jung M, Taylor JM, Houck AA, & Petta JR (2012). Circuit quantum electrodynamics with a spin qubit. Nature, 490 (7420), 380-3 PMID: 23075988
Monday, January 7, 2013
Quantum computing with recycled particles
The team have shown how it is possible to recycle the particles inside a quantum computer, so that quantum factoring can be achieved with only one third of the particles originally required. The research is published in the latest issue of Nature Photonics.
Using photons as the particles, the Bristol team constructed a quantum optical circuit that recycled one of the photons to set a new record for factoring 21 with a quantum algorithm -- all previous demonstrations have factored 15.
Dr Anthony Laing, who led the project, said: "Quantum computers promise to harness the counterintuitive laws of quantum mechanics to perform calculations that are forever out of reach of conventional classical computers. Realising such a device is one of the great technological challenges of the century."
While scientists and mathematicians are still trying to understand the full range of capabilities of quantum computers, the current driving application is the hard problem of factoring large numbers. The best classical computers can run for the lifetime of the universe, searching for the factors of a large number, yet still be unsuccessful.
In fact, Internet cryptographic protocols are based on this exponential overhead in computational time: if a third party wants to spy on your emails, they will need to solve a hard factoring problem first. A quantum computer, on the other hand, is capable of efficiently factoring large numbers, but the physical resources required mean that constructing such a device is highly challenging.
CQP PhD student Enrique Martín-López, who performed the experiment, said: "While it will clearly be some time before emails can be hacked with a quantum computer, this proof of principle experiment paves the way for larger implementations of quantum algorithms by using particle recycling."
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The above story is reprinted from materials provided by University of Bristol.
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Journal Reference:
Enrique Martín-López, Anthony Laing, Thomas Lawson, Roberto Alvarez, Xiao-Qi Zhou, Jeremy L. O'Brien. Experimental realization of Shor's quantum factoring algorithm using qubit recycling. Nature Photonics, 2012; DOI: 10.1038/nphoton.2012.259Note: If no author is given, the source is cited instead.
Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
Thursday, January 3, 2013
Researchers identify ways to exploit 'cloud browsers' for large-scale, anonymous computing
At issue are cloud browsers, which create a Web interface in the cloud so that computing is done there rather than on a user's machine. This is particularly useful for mobile devices, such as smartphones, which have limited computing power.The cloud-computing paradigm pools the computational power and storage of multiple computers, allowing shared resources for multiple users.
"Think of a cloud browser as being just like the browser on your desktop computer, but working entirely in the cloud and providing only the resulting image to your screen," says Dr. William Enck, an assistant professor of computer science at NC State and co-author of a paper describing the research.
Because these cloud browsers are designed to perform complex functions, the researchers wanted to see if they could be used to perform a series of large-scale computations that had nothing to do with browsing. Specifically, the researchers wanted to determine if they could perform those functions using the "MapReduce" technique developed by Google, which facilitates coordinated computation involving parallel efforts by multiple machines.
The research team knew that coordinating any new series of computations would entail passing large packets of data between different nodes, or cloud browsers. To address this challenge, researchers stored data packets on bit.ly and other URL-shortening sites, and then passed the resulting "links" between various nodes.
Using this technique, the researchers were able to perform standard computation functions using data packets that were 1, 10 and 100 megabytes in size. "It could have been much larger," Enck says, "but we did not want to be an undue burden on any of the free services we were using."
"We've shown that this can be done," Enck adds. "And one of the broader ramifications of this is that it could be done anonymously. For instance, a third party could easily abuse these systems, taking the free computational power and using it to crack passwords."
However, Enck says cloud browsers can protect themselves to some extent by requiring users to create accounts -- and then putting limits on how those accounts are used. This would make it easier to detect potential problems.
The paper, "Abusing Cloud-Based Browsers for Fun and Profit," will be presented Dec. 6 at the 2012 Annual Computer Security Applications Conference in Orlando, Fla. The paper was co-authored by Vasant Tendulkar and Ashwin Shashidharan, graduate students at NC State, and Joe Pletcher, Ryan Snyder and Dr. Kevin Butler, of the University of Oregon. The research was supported by the National Science Foundation and the U.S. Army Research Office.
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The above story is reprinted from materials provided by North Carolina State University.
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Note: If no author is given, the source is cited instead.
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Tuesday, October 16, 2012
A network to guide the future of computing
At the same time, the world is in the midst of a data explosion, with humans and machines generating, storing, sharing and accessing ever increasing amounts of data in many different forms, on a multitude of different devices that require more energy-efficient, higher-performance processors.
How can computing systems, now facing a post-Moore era, meet this ever growing demand?
It is an open-ended question, but one that European researchers are working hard to answer, thanks in large measure to the efforts of HiPEAC (1), a 'Network of excellence' from academia and industry that has been helping to steer European computing systems research since 2004. Currently in its third incarnation, supported over four years by EUR 3.8 million in funding from the European Commission, the project has become the most visible and far-reaching computing systems network in Europe.
'HiPEAC was set up with three main goals: to bring together academia and industry, to bring together hardware and software developers and to create a real, visible computer systems community in Europe. On those fronts, and many others, we have undoubtedly succeeded,' says Koen De Bosschere, professor of the computer systems lab of Ghent University in Belgium and coordinator of the HiPEAC network.
HiPEAC's conferences and networking events are now attended by hundreds of academic researchers and industry representatives from Europe and beyond; the network's summer schools, workshops and exchange grants between universities are helping train researchers in new and emerging areas of computing systems theory and technology; and the project's biannual roadmap has become a guideline for both the public and private sector as to where research funding should be channelled.
'We now have a portfolio of between 30 and 40 computer systems projects that we are working with. The researchers involved come to our events, which have become one of the sector's main networking opportunities, and several projects have actually emerged from people meeting at our conferences,' Prof. De Bosschere notes.
He points, for example, to the EuroCloud project, which began in 2010 with the support of EUR 3.3 million in funding from the European Commission. Coordinated by microprocessor designer ARM in the United Kingdom, the project is developing on-chip servers using multiple ARM cores and integrating 3D DRAM with the aim of reducing energy consumption and costs at data centres by as much as 90 %.
The idea for the project first arose at the HiPEAC conference in Cyprus in 2009, Prof. De Bosschere notes. 'These kinds of networking opportunities are really showing their worth in spurring collaboration and innovation."
A roadmap of challenges and opportunities for Europe
Meanwhile, the HiPEAC Roadmap, a new edition of which is due to be published this year, has become something of a guidebook for the future of computing systems research in Europe.
'We didn't really set out doing it with that aim in mind, but the Commission took notice of it, consulted with industry on it, found the challenges we had identified to be accurate and started to use it to focus research funding,' the HiPEAC coordinator explains. 'Since we produced the first edition in 2008, EU funding in the sector has almost tripled and the next call will offer around EUR 70 million.'
For the short and medium term, the latest edition of the HiPEAC report concludes that specialising computing devices is the most promising but difficult path for dramatically improving the performance of future computing systems. In this light, HiPEAC has identified seven concrete research objectives -- from energy efficiency to system complexity and reliability -- related to the design and the exploitation of specialised heterogeneous systems. But in the longer term, the HiPEAC researchers say it will be critical to pursue research directions that break with classical systems, and their traditional hardware/software boundary, by investigating new devices and new computing paradigms, such as bio-inspired systems, stochastic computing and swarm computing.
'We can only go so far by following current trends and approaches, but in the long run we will nonetheless want and require more processing power that is more reliable, consumes less energy, produces less heat and can fit into smaller devices. More processing power means more applications and entirely new markets -- just look at what's happened with smartphones and tablet computers over the last five years,' Prof. De Bosschere says. 'For industry, it means that today, instead of a person having just one desktop or laptop computer, they may have three or four devices.'
And, in the future, he sees ever higher-performance devices doing much more than is possible or even imaginable today: bio-inspired neural networks powering data mining applications at 1 % of the energy consumption of today's data centres, for example, or smartphones that can analyse a blood sample, sequence the DNA and detect a virus in a few minutes, rather than the days it takes using laboratory computer systems at present.
'The potential applications for computing technology in almost every aspect of life are almost endless -- we just need to make sure we have the processing power to run them,' he says.
HiPEAC received research funding under the European Union's Seventh Framework Programme.
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The above story is reprinted from materials provided by CORDIS Features, formerly ICT Results.
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Note: If no author is given, the source is cited instead.
Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
Saturday, September 1, 2012
Searching genomic data faster: Biologists' capacity for generating genomic data is increasing more rapidly than computing power
Since 2002, the rate at which genomes can be sequenced has been doubling every four months or so, whereas computing power doubles only every 18 months. Without the advent of new analytic tools, biologists' ability to generate genomic data will soon outstrip their ability to do anything useful with it.
In the latest issue of Nature Biotechnology, MIT and Harvard University researchers describe a new algorithm that drastically reduces the time it takes to find a particular gene sequence in a database of genomes. Moreover, the more genomes it's searching, the greater the speedup it affords, so its advantages will only compound as more data is generated.
In some sense, this is a data-compression algorithm -- like the one that allows computer users to compress data files into smaller zip files. "You have all this data, and clearly, if you want to store it, what people would naturally do is compress it," says Bonnie Berger, a professor of applied math and computer science at MIT and senior author on the paper. "The problem is that eventually you have to look at it, so you have to decompress it to look at it. But our insight is that if you compress the data in the right way, then you can do your analysis directly on the compressed data. And that increases the speed while maintaining the accuracy of the analyses."
Exploiting redundancy
The researchers' compression scheme exploits the fact that evolution is stingy with good designs. There's a great deal of overlap in the genomes of closely related species, and some overlap even in the genomes of distantly related species: That's why experiments performed on yeast cells can tell us something about human drug reactions.
Berger; her former grad student Michael Baym PhD '09, who's now a visiting scholar in the MIT math department and a postdoc in systems biology at Harvard Medical School; and her current grad student Po-Ru Loh developed a way to mathematically represent the genomes of different species -- or of different individuals within a species -- such that the overlapping data is stored only once. A search of multiple genomes can thus concentrate on their differences, saving time.
"If I want to run a computation on my genome, it takes a certain amount of time," Baym explains. "If I then want to run the same computation on your genome, the fact that we're so similar means that I've already done most of the work."
In experiments on a database of 36 yeast genomes, the researchers compared their algorithm to one called BLAST, for Basic Local Alignment Search Tool, one of the most commonly used genomic-search algorithms in biology. In a search for a particular genetic sequence in only 10 of the yeast genomes, the new algorithm was twice as fast as BLAST; but in a search of all 36 genomes, it was four times as fast. That discrepancy will only increase as genomic databases grow larger, Berger explains.
Matchmaking
The new algorithm would be useful in any application where the central question is, as Baym puts it: "I have a sequence; what is it similar to?" Identifying microbes is one example. The new algorithm could help clinicians determine causes of infections, or it could help biologists characterize "microbiomes," collections of microbes found in animal tissue or particular microenvironments; variations in the human microbiome have been implicated in a range of medical conditions. It could be used to characterize the microbes in particularly fertile or infertile soil, and it could even be used in forensics, to determine the geographical origins of physical evidence by its microbial signatures.
"The problem that they're looking at -- which is, given a sequence, trying to determine what known sequences are similar to it -- is probably the oldest problem in computational biology, and it's perhaps the most commonly asked question in computational biology," says Mona Singh, a professor of computer science at Princeton University and a faculty member at Princeton's Lewis-Sigler Institute for Integrative Genomics. "And the problem, just for that reason, is of central importance."
In the last 10 years, Singh says, biologists have tended to think in terms of "reference genomes" -- genomes, such as the draft human sequence released in 2001, that try to generalize across individuals within a species and even across species. "But as we're getting more and more individuals even within a species, and more very closely related sequenced distinct species, I think we're starting to move away from the idea of a single reference genome," Singh says. "Their approach is really going to shine when you have many closely related organisms."
Berger's group is currently working to extend the technique to information on proteins and RNA sequences, where it could pay even bigger dividends. Now that the human genome has been mapped, the major questions in biology are what genes are active when, and how the proteins they code for interact. Searches of large databases of biological information are crucial to answering both questions.
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Story Source:
The above story is reprinted from materials provided by Massachusetts Institute of Technology.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Journal Reference:
Po-Ru Loh, Michael Baym, Bonnie Berger. Compressive genomics. Nature Biotechnology, 2012; 30 (7): 627 DOI: 10.1038/nbt.2241Note: 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.
Tuesday, August 21, 2012
Cloud computing: Same weakness found in seven cloud storage services
Security experts at the Fraunhofer Institute for Secure Information Technology (SIT) in Darmstadt have discovered that numerous cloud storage service providers do not check the e-mail addresses provided during the registration process. This fact in combination with functions provided by these service providers, such as file sharing or integrated notifications, result in various possibilities for attacks.
For example, attackers can bring malware into circulation or spy out confidential data. As one of the supporters of the Center for Advanced Security Research Darmstadt (CASED), the Fraunhofer SIT scrutinized various cloud storage services. The testers discovered the same weakness with the free service offerings from CloudMe, Dropbox, HiDrive, IDrive, SugarSync, Syncplicity and Wuala. Scientists from Fraunhofer SIT presented their findings on the possible forms of attacks on June 26, 2012, at the 11th International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom) in Liverpool.
Attackers do not require any programming knowledge whatsoever to exploit these weaknesses. All they need is to create an account using a false e-mail account. The attacker can then bring malware into circulation using another person's identity. With the services provided by Dropbox, IDrive, SugarSync, Syncplicity and Wuala, attackers can even spy on unsuspecting computer users with the help of the false e-mail address by encouraging them to upload confidential data to the cloud for joint access.
Fraunhofer SIT informed the affected service providers many months ago. And although these weaknesses can be removed with very simple and well-known methods, such as sending an e-mail with an activation link, not all of them are convinced that there is a need for action. Dr. Markus Schneider, Deputy Director of Fraunhofer SIT: "Dropbox, HiDrive, SugarSync, Syncplicity and Wuala have reacted after receiving our information." Some of these providers are now using confirmation e-mails to avoid this weakness, a method that has been in use for quite some time now. Others have implemented other mechanisms. "We think it is important that users are informed about the existing problems," said Schneider. "Unfortunately, it is not possible to provide 100% protection against attacks, even if the affected services are avoided. It is therefore important that cloud storage services providers remove such weaknesses, as this helps to protect users more effectively."
Consumers who use the affected services should be careful. Those who receive a request to download data from the cloud or upload data to it should send an e-mail to the supposed requestor to verify whether the request was really sent by them.
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Story Source:
The above story is reprinted from materials provided by Fraunhofer SIT, via AlphaGalileo.
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: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
Sunday, July 22, 2012
Searching genomic data faster: Biologists' capacity for generating genomic data is increasing more rapidly than computing power
Since 2002, the rate at which genomes can be sequenced has been doubling every four months or so, whereas computing power doubles only every 18 months. Without the advent of new analytic tools, biologists' ability to generate genomic data will soon outstrip their ability to do anything useful with it.
In the latest issue of Nature Biotechnology, MIT and Harvard University researchers describe a new algorithm that drastically reduces the time it takes to find a particular gene sequence in a database of genomes. Moreover, the more genomes it's searching, the greater the speedup it affords, so its advantages will only compound as more data is generated.
In some sense, this is a data-compression algorithm -- like the one that allows computer users to compress data files into smaller zip files. "You have all this data, and clearly, if you want to store it, what people would naturally do is compress it," says Bonnie Berger, a professor of applied math and computer science at MIT and senior author on the paper. "The problem is that eventually you have to look at it, so you have to decompress it to look at it. But our insight is that if you compress the data in the right way, then you can do your analysis directly on the compressed data. And that increases the speed while maintaining the accuracy of the analyses."
Exploiting redundancy
The researchers' compression scheme exploits the fact that evolution is stingy with good designs. There's a great deal of overlap in the genomes of closely related species, and some overlap even in the genomes of distantly related species: That's why experiments performed on yeast cells can tell us something about human drug reactions.
Berger; her former grad student Michael Baym PhD '09, who's now a visiting scholar in the MIT math department and a postdoc in systems biology at Harvard Medical School; and her current grad student Po-Ru Loh developed a way to mathematically represent the genomes of different species -- or of different individuals within a species -- such that the overlapping data is stored only once. A search of multiple genomes can thus concentrate on their differences, saving time.
"If I want to run a computation on my genome, it takes a certain amount of time," Baym explains. "If I then want to run the same computation on your genome, the fact that we're so similar means that I've already done most of the work."
In experiments on a database of 36 yeast genomes, the researchers compared their algorithm to one called BLAST, for Basic Local Alignment Search Tool, one of the most commonly used genomic-search algorithms in biology. In a search for a particular genetic sequence in only 10 of the yeast genomes, the new algorithm was twice as fast as BLAST; but in a search of all 36 genomes, it was four times as fast. That discrepancy will only increase as genomic databases grow larger, Berger explains.
Matchmaking
The new algorithm would be useful in any application where the central question is, as Baym puts it: "I have a sequence; what is it similar to?" Identifying microbes is one example. The new algorithm could help clinicians determine causes of infections, or it could help biologists characterize "microbiomes," collections of microbes found in animal tissue or particular microenvironments; variations in the human microbiome have been implicated in a range of medical conditions. It could be used to characterize the microbes in particularly fertile or infertile soil, and it could even be used in forensics, to determine the geographical origins of physical evidence by its microbial signatures.
"The problem that they're looking at -- which is, given a sequence, trying to determine what known sequences are similar to it -- is probably the oldest problem in computational biology, and it's perhaps the most commonly asked question in computational biology," says Mona Singh, a professor of computer science at Princeton University and a faculty member at Princeton's Lewis-Sigler Institute for Integrative Genomics. "And the problem, just for that reason, is of central importance."
In the last 10 years, Singh says, biologists have tended to think in terms of "reference genomes" -- genomes, such as the draft human sequence released in 2001, that try to generalize across individuals within a species and even across species. "But as we're getting more and more individuals even within a species, and more very closely related sequenced distinct species, I think we're starting to move away from the idea of a single reference genome," Singh says. "Their approach is really going to shine when you have many closely related organisms."
Berger's group is currently working to extend the technique to information on proteins and RNA sequences, where it could pay even bigger dividends. Now that the human genome has been mapped, the major questions in biology are what genes are active when, and how the proteins they code for interact. Searches of large databases of biological information are crucial to answering both questions.
Share this story on Facebook, Twitter, and Google:Other social bookmarking and sharing tools:
Story Source:
The above story is reprinted from materials provided by Massachusetts Institute of Technology.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Journal Reference:
Po-Ru Loh, Michael Baym, Bonnie Berger. Compressive genomics. Nature Biotechnology, 2012; 30 (7): 627 DOI: 10.1038/nbt.2241Note: 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.
Monday, July 16, 2012
Cloud computing: Same weakness found in seven cloud storage services
Security experts at the Fraunhofer Institute for Secure Information Technology (SIT) in Darmstadt have discovered that numerous cloud storage service providers do not check the e-mail addresses provided during the registration process. This fact in combination with functions provided by these service providers, such as file sharing or integrated notifications, result in various possibilities for attacks.
For example, attackers can bring malware into circulation or spy out confidential data. As one of the supporters of the Center for Advanced Security Research Darmstadt (CASED), the Fraunhofer SIT scrutinized various cloud storage services. The testers discovered the same weakness with the free service offerings from CloudMe, Dropbox, HiDrive, IDrive, SugarSync, Syncplicity and Wuala. Scientists from Fraunhofer SIT presented their findings on the possible forms of attacks on June 26, 2012, at the 11th International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom) in Liverpool.
Attackers do not require any programming knowledge whatsoever to exploit these weaknesses. All they need is to create an account using a false e-mail account. The attacker can then bring malware into circulation using another person's identity. With the services provided by Dropbox, IDrive, SugarSync, Syncplicity and Wuala, attackers can even spy on unsuspecting computer users with the help of the false e-mail address by encouraging them to upload confidential data to the cloud for joint access.
Fraunhofer SIT informed the affected service providers many months ago. And although these weaknesses can be removed with very simple and well-known methods, such as sending an e-mail with an activation link, not all of them are convinced that there is a need for action. Dr. Markus Schneider, Deputy Director of Fraunhofer SIT: "Dropbox, HiDrive, SugarSync, Syncplicity and Wuala have reacted after receiving our information." Some of these providers are now using confirmation e-mails to avoid this weakness, a method that has been in use for quite some time now. Others have implemented other mechanisms. "We think it is important that users are informed about the existing problems," said Schneider. "Unfortunately, it is not possible to provide 100% protection against attacks, even if the affected services are avoided. It is therefore important that cloud storage services providers remove such weaknesses, as this helps to protect users more effectively."
Consumers who use the affected services should be careful. Those who receive a request to download data from the cloud or upload data to it should send an e-mail to the supposed requestor to verify whether the request was really sent by them.
Share this story on Facebook, Twitter, and Google:Other social bookmarking and sharing tools:
Story Source:
The above story is reprinted from materials provided by Fraunhofer SIT, via AlphaGalileo.
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: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
Monday, June 25, 2012
Grid-based computing to fight neurological disease
Through the Neugrid project, the pan-European grid computing infrastructure has opened up new channels of research into degenerative neurological disorders and other illnesses, while also holding the promise of quicker and more accurate clinical diagnoses of individual patients.
The infrastructure, set up with the support of EUR 2.8 million in funding from the European Commission, was developed over three years by researchers in seven countries. Their aim, primarily, was to give neuroscientists the ability to quickly and efficiently analyse 'Magnetic resonance imaging' (MRI) scans of the brains of patients suffering from Alzheimer's disease. But their work has also helped open the door to the use of grid computing for research into other neurological disorders, and many other areas of medicine.
'Neugrid was launched to address a very real need. Neurology departments in most hospitals do not have quick and easy access to sophisticated MRI analysis resources. They would have to send researchers to other labs every time they needed to process a scan. So we thought, why not bring the resources to the researchers rather than sending the researchers to the resources,' explains Giovanni Frisoni, a neurologist and the deputy scientific director of IRCCS Fatebenefratelli, the Italian National Centre for Alzheimer's and Mental Diseases, in Brescia.
Five years' work in two weeks The Neugrid team, led by David Manset from MaatG in France and Richard McClatchey from the University of the West of England in Bristol, laid the foundations for the grid infrastructure, starting with five distributed nodes of 100 cores (CPUs) each, interconnected with grid middleware and accessible via the internet with an easy-to-use web browser interface. To test the infrastructure, the team used datasets of images from the Alzheimer's Disease Neuroimaging Initiative in the United States, the largest public database of MRI scans of patients with Alzheimer's disease and a lesser condition termed 'Mild cognitive impairment'.
'In Neugrid we have been able to complete the largest computational challenge ever attempted in neuroscience: we extracted 6,500 MRI scans of patients with different degrees of cognitive impairment and analysed them in two weeks,' Dr. Frisoni, the lead researcher on the project, says, 'on an ordinary computer it would have taken five years!'.
Though Alzheimer's disease affects about half of all people aged 85 and older, its causes and progression remain poorly understood. Worldwide more than 35 million people suffer from Alzheimer's, a figure that is projected to rise to over 115 million by 2050 as the world's population ages.
Patients with early symptoms have difficulty recalling the names of people and places, remembering recent events and solving simple maths problems. As the brain degenerates, patients in advanced stages of the disease lose mental and physical functions and require round-the-clock care.
The analysis of MRI scans conducted as part of the Neugrid project should help researchers gain important insights into some of the big questions surrounding the disease such as which areas of the brain deteriorate first, what changes occur in the brain that can be identified as biomarkers for the disease and what sort of drugs might work to slow or prevent progression.
Neugrid built on research conducted by two prior EU-funded projects: Mammogrid, which set up a grid infrastructure to analyse mammography data, and AddNeuroMed, which sought biomarkers for Alzheimer's. The team are now continuing their work in a series of follow-up projects. An expanded grid and a new paradigm Neugrid for You (N4U), a direct continuation of Neugrid, will build upon the grid infrastructure, integrating it with 'High performance computing' (HPC) and cloud computing resources. Using EUR 3.5 million in European Commission funding, it will also expand the user services, algorithm pipelines and datasets to establish a virtual laboratory for neuroscientists.
'In Neugrid we built the grid infrastructure, addressing technical challenges such as the interoperability of core computing resources and ensuring the scalability of the architecture. In N4U we will focus on the user-facing side of the infrastructure, particularly the services and tools available to researchers,' Dr. Frisoni says. 'We want to try to make using the infrastructure for research as simple and easy as possible,' he continues, 'the learning curve should not be much more difficult than learning to use an iPhone!'
N4U will also expand the grid infrastructure from the initial five computing clusters through connections with CPU nodes at new sites, including 2,500 CPUs recently added in Paris in collaboration with the French Alternative Energies and Atomic Energy Commission (CEA), and in partnership with 'Enabling grids for e-science Biomed VO', a biomedical virtual organisation.
Another follow-up initiative, outGRID, will federate the Neugrid infrastructure, linking it with similar grid computing resources set up in the United States by the Laboratory of Neuro Imaging at the University of California, Los Angeles, and the CBRAIN brain imaging research platform developed by McGill University in Montreal, Canada. A workshop was recently held at the International Telecommunication Union, an agency of the United Nations, to foster this effort.
Dr. Frisoni is also the scientific coordinator of the DECIDE project, which will work on developing clinical diagnostic tools for doctors built upon the Neugrid grid infrastructure. 'There are a couple of important differences between using brain imaging datasets for research and for diagnosis,' he explains. 'Researchers compare many images to many others, whereas doctors are interested in comparing images from a single patient against a wider set of data to help diagnose a disease. On top of that, datasets used by researchers are anonymous, whereas images from a single patient are not and protecting patient data becomes an issue.'
The DECIDE project will address these questions in order to use the grid infrastructure to help doctors treat patients. Though the main focus of all these new projects is on using grid computing for neuroscience, Dr. Frisoni emphasises that the same infrastructure, architecture and technology could be used to enable new research -- and new, more efficient diagnostic tools -- in other fields of medicine. 'We are helping to lay the foundations for a new paradigm in grid-enabled medical research,' he says.
Neugrid received research funding under the European Union's Seventh Framework Programme (FP7).
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