1,018,582 research outputs found

    On the Machine Learning Techniques for Side-channel Analysis

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    Side-channel attacks represent one of the most powerful category of attacks on cryptographic devices with profiled attacks in a prominent place as the most powerful among them. Indeed, for instance, template attack is a well-known real-world attack that is also the most powerful attack from the information theoretic perspective. On the other hand, machine learning techniques have proven their quality in a numerous applications where one is definitely side-channel analysis, but they come with a price. Selecting the appropriate algorithm as well as the parameters can sometimes be a difficult and time consuming task. Nevertheless, the results obtained until now justify such an effort. However, a large part of those results use simplification of the data relation from the one perspective and extremely powerful machine learning techniques from the other side. In this paper, we concentrate first on the tuning part, which we show to be of extreme importance. Furthermore, since tuning represents a task that is time demanding, we discuss how to use hyperheuristics to obtain good results in a relatively short amount of time. Next, we provide an extensive comparison between various machine learning techniques spanning from extremely simple ones ( even without any parameters to tune), up to methods where previous experience is a must if one wants to obtain competitive results. To support our claims, we give extensive experimental results and discuss the necessary conditions to conduct a proper machine learning analysis. Besides the machine learning algorithms' results, we give results obtained with the template attack. Finally, we investigate the influence of the feature (in)dependence in datasets with varying amount of noise as well as the influence of feature noise and classification noise. In order to strengthen our findings, we also discuss provable machine learning algorithms, i.e., PAC learning algorithms

    Parallel single cell analysis on an integrated microfluidic platform for cell trapping, lysis and analysis

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    We report here a novel and easily scalable microfluidic platform for the parallel analysis of hundreds of individual cells, with controlled single cell trapping, followed by their lysis and subsequent retrieval of the cellular content for on-chip analysis. The device consists of a main channel and an array of shallow side channels connected to the main channel via trapping structures. Cells are individually captured in dam structures by application of a negative pressure from an outlet reservoir, lyzed on site and the cellular content controllably extracted and transported in the individual side channels for on-chip analysis.\u

    Virtual Analysis and Reduction of Side-Channel Vulnerabilities of Smartcards

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    This paper focuses on the usability of the PINPAS tool. The PINPAS tool is an instruction-level interpreter for smartcard assembler languages, augmented with facilities to study side-channel vulnerabilities. The tool can simulate side-channel leakage and has a suite of utilities to analyze this. The usage of the tool, for the analysis of a cryptographic algorithm is illustrated using the standard AES and RSA. Vulnerabilities of the implementations are identified and protective measures added. It is argued, that the tool can be instrumental for the design and realization of secure smartcard implementations in a systematic wa

    Investment cost channel and monetary transmission

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    We show that a standard DSGE model with investment cost channels has important model stability and policy implications. Our analysis suggests that in economies characterized by supply side well as demand side channels of monetary transmission, policymakers may have to resort to a much more aggressive stand against inflation to obtain locally unique equilibrium. In such an environment targeting output gap may cause model instability. We also show that it is difficult to distinguish between the New Keynesian model and labor cost channel only case, while with investment cost channel differences are more significant. This result is important as it suggests that if one does not take into account the investment cost channel, one is underestimating the importance of supply side effects
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