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    ABSTRACT: Automotive electronics are becoming ever more com-plex. The quantity and sensitivity of data that is transmitted throughout a car is expected to continue to increase in coming years. On board computers can contain information about the car and dic-tate how the car behaves. This means that these systems need to be secure to protect the data held within such system so that the behaviour cannot be modified by an unauthorised user. This paper outlines a method for implementing AES encryption over a CAN bus and how such a system could be attacked using Correlation Power Analysis.
    Full-text · Article · Jul 2019
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    ABSTRACT: A generic DPA strategy is one which is able to recover secret information from physically observable device leakage without any a priori knowledge about the device’s leakage characteristics. Here we provide much-needed clarification on results emerging from the existing literature, demonstrating precisely that such methods (strictly defined) are inherently restricted to a very limited selection of target functions. Continuing to search related techniques for a ‘silver bullet’ generic attack appears a bootless errand. However, we find that a minor relaxation of the strict definition-the incorporation of some minimal non-device-specific intuition-produces scope for generic-emulating strategies, able to succeed against a far wider range of targets. We present stepwise regression as an example of such, and demonstrate its effectiveness in a variety of scenarios. We also give some evidence that its practical performance matches that of ‘best bit’ DoM attacks which we take as further indication for the necessity of performing profiled attacks in the context of device evaluations.
    Full-text · Article · Feb 2014
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    ABSTRACT: Biologists are increasingly confronted with the challenge of quickly understanding genome-wide biological data, which usually involve a large number of genomic coordinates (e.g. genes) but a much smaller number of samples. To meet the need for data of this shape, we present an open-source package called 'supraHex' for training, analysing and visualising omics data. This package devises a supra-hexagonal map to self-organise the input data, offers scalable functionalities for post-analysing the map, and more importantly, allows for overlaying additional data to explore possible relationships, via the specific application to DNA replication timing data of mouse embryogenesis, we demonstrate that supraHex is capable of simultaneously carrying out gene clustering and sample correlation, providing intuitive visualisation at each step of the analysis. By overlaying CpG and expression data onto the trained replication-timing map, we also show that supraHex is able to intuitively capture an inherent relationship between late replication of low CpG density promoters and low expression levels. As part of the Bioconductor project, supraHex makes accessible to a wide community in a simple way, what would otherwise be a complex framework for the ultrafast understanding of any tabular omics data, both scientifically and artistically. This package can run on Windows, Mac and Linux, and is freely available together with many tutorials on featuring real examples at http://supfam.org/SUPERFAMILY/dcGO/supraHex.html.
    Full-text · Article · Dec 2013 · Biochemical and Biophysical Research Communications
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