As a result of “heightened demands” for secure computing, PC makers are taking a serious look at biometrics. Companies such as Apple, Dell, Gateway, and MicronPC (MPC) are marketing fingerprint readers or developing add-ons.
MPC’s TransPort laptops, for example, use heat-sensitive scans integrated into the system’s BIOS. The MPC’s TouchChip, manufactured for MPC by STMicroelectronics, captures fingerprint scans from the laptop’s palmrest. A laptop can be registered to multiple users, who can each designate which files, folders, or directories will be shared. Very James Bond.
Unfortunately, Linux and Unix users will have to wait a little while to get their hands on one of these new TransPorts; at the moment an individual’s fingerprint scans can only be tied in with Microsoft Windows’ security functions.
The other gotcha’? The TransPort’s thermal scans are so sensitive that users might experience difficulties logging on if they’ve been sipping a hot or cold beverage. As a failsafe, users must register the fingerprints of two fingers—one from each hand—which is probably just fine because, if you’re drinking two mugs of coffee or two chilled pints of beer, you probably shouldn’t be working on the computer anyway.
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http://www.gcn.com/22_14/security/22347-1.html
After approximately three years of development involving over 250 participants in five countries, IBM is finally readying WebFountain, its super spider that can slurp down the entire Internet—as well as intranet and third-party data—in a couple of weeks.
As a first step, WebFountain uses focused crawling to access all unstructured data on the Internet (Web pages, Word docs, PowerPoint presentations, etc.). After that comes a detailed analysis of its findings. This might emcompass, for instance, anything from popular trends in online publications to complex patterns in designated communities to consumer feelings as expressed in blogs, chat rooms, and bulletin boards.
WebFountain’s results can be gathered, organized, and delivered within a week—instead of the six-month to one-year turnaround that current analysis projects typically take.
Here’s the good news: WebFountain’s platform is open source and will be accessible to programmers and content developers.
The bad news? Leasing IBM’s 1,000-node Intel Linux cluster, with its half a petabyte of storage, is sure to cost a pretty penny.
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http://www.almaden.ibm.com/webfountain/
Open source software was a topic of concern during a May dedication ceremony for India’s new International Institute of Information Technology (I2IT). Dr. A.P.J. Abdul Kalam, president of India, lamented, “The most unfortunate thing is that India still seems to believe in proprietary solutions.” He then challenged current and future members of India’s techno-elite, stating that even a small shift toward business practices involving proprietary models could have a devastating impact on Indian society. “It is precisely for these reasons,” he continued, “that open source software needs to be built [so as to] be cost effective for the entire society.
Perhaps less of a highlight: During his speech, Kalam also referred to a “difficult” conversation he had with Bill Gates, a guy who tends to favor those maligned proprietary models.
Just six months prior to Kalam’s speech embracing open source, Microsoft made a three-year commitment to donate $400 million toward technology development and education in India.
No wonder the conversation was difficult.
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http://presidentofindia.nic.in/S/html/speeches/others/may28_2003_2.htm
Originally published in Queue vol. 1, no. 5—
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The principles of security, privacy, accountability, transparency, and fairness are the cornerstones of modern AI regulations. Classic FL was designed with a strong emphasis on security and privacy, at the cost of transparency and accountability. CFL addresses this gap with a careful combination of FL with TEEs and commitments. In addition, CFL brings other desirable security properties, such as code-based access control, model confidentiality, and protection of models during inference. Recent advances in confidential computing such as confidential containers and confidential GPUs mean that existing FL frameworks can be extended seamlessly to support CFL with low overheads.
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The experiments presented here demonstrate that Parma, the architecture that drives confidential containers on Azure container instances, adds less than one percent additional performance overhead beyond that added by the underlying TEE. Importantly, Parma ensures a security invariant over all reachable states of the container group rooted in the attestation report. This allows external third parties to communicate securely with containers, enabling a wide range of containerized workflows that require confidential access to secure data. Companies obtain the advantages of running their most confidential workflows in the cloud without having to compromise on their security requirements.
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Confidential computing has great potential to improve the security of general-purpose computing platforms by taking supervisory systems out of the TCB, thereby reducing the size of the TCB, the attack surface, and the attack vectors that security architects must consider. Confidential computing requires innovations in platform hardware and software, but these have the potential to enable greater trust in computing, especially on devices that are owned or controlled by third parties. Early consumers of confidential computing will need to make their own decisions about the platforms they choose to trust.