65 research outputs found

    Reducing the Attack Surface of Dynamic Binary Instrumentation Frameworks

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    Malicious applications pose as one of the most relevant issues in today’s technology scenario, being considered the root of many Internet security threats. In part, this owes the ability of malware developers to promptly respond to the emergence of new security solutions by developing artifacts to detect and avoid them. In this work, we present three countermeasures to mitigate recent mechanisms used by malware to detect analysis environments. Among these techniques, this work focuses on those that enable a malware to detect dynamic binary instrumentation frameworks, thus increasing their attack surface. To ensure the effectiveness of the proposed countermeasures, proofs of concept were developed and tested in a controlled environment with a set of anti-instrumentation techniques. Finally, we evaluated the performance impact of using such countermeasures

    Enhanced detection techniques of orbital angular momentum states in the classical and quantum regimes

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    The orbital angular momentum (OAM) of light has been at the center of several classical and quantum applications for imaging, information processing and communication. However, the complex structure inherent in OAM states makes their detection and classification nontrivial in many circumstances. Most of the current detection schemes are based on models of the OAM states built upon the use of Laguerre-Gauss (LG) modes. However, this may not in general be sufficient to capture full information on the generated states. In this paper, we go beyond the LG assumption, and employ hypergeometric-Gaussian (HyGG) modes as the basis states of a refined model that can be used - in certain scenarios - to better tailor OAM detection techniques. We show that enhanced performances in OAM detection are obtained for holographic projection via spatial light modulators in combination with single-mode fibers (SMFs), and for classification techniques based on a machine learning approach. Furthermore, a three-fold enhancement in the SMF coupling efficiency is obtained for the holographic technique, when using the HyGG model with respect to the LG one. This improvement provides a significant boost in the overall efficiency of OAM-encoded single-photon detection systems. Given that most of the experimental works using OAM states are effectively based on the generation of HyGG modes, our findings thus represent a relevant addition to experimental toolboxes for OAM-based protocols in quantum communication, cryptography and simulation

    Adaptive two-phase estimation on a photonic integrated device

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    Efficient adaptive multiphase estimation has been demonstrated experimentally on an integrated three-arm interferometer injected by single photons. Bayesian learning and Sequential Monte Carlo approximation have been employed as machine learning tools to achieve this goal

    Математическая модель полупроводникового преобразователя с семизонным регулированием выходного напряжения

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    У статті проведено дослідження електромагнітних процесів в електричних колах з напівпровідниковими комутаторами. Створено математичну модель для аналізу електромагнітних процесів у напівпровідникових перетворювачах з широтно-імпульсним регулюванням вихідної напруги. Наведено графіки, що відображають електромагнітні процеси у електричних колах.Analysis of the electromagnetic processes is organized beside this article in electric circuit with semiconductor commutator. Mathematical model is created for analysis electro-magnetic processes in semiconductor converter with width pulsed regulation of the output voltage. The broughted graphs, which reflect the electromagnetic processes in electric circuit. Method much parametric functions was used when performing calculation. The mathematical model of the converter is created for seven zoned regulations of the output voltage.В этой статье проведено анализ электромагнитных процессов в электрических цепях с полупроводниковыми коммутаторами. Создано математическую модель для анализа электромагнитных процессов в полупроводниковых преобразователях с широтно-импульсным регулированием выходного напряжения. Приведено графики, которые отражают электромагнитные процессы в электрических цепях. При выполнении расчетов использовался метод многопараметрических функций. Математическая модель преобразователя создана для семизонным регулирования выходного напряжения

    Daylight entanglement-based quantum key distribution with a quantum dot source

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    Entanglement-based quantum key distribution can enable secure communication in trusted node-free networks and over long distances. Although implementations exist both in fiber and in free space, the latter approach is often considered challenging due to environmental factors. Here, we implement a quantum communication protocol during daytime for the first time using a quantum dot source. This technology presents advantages in terms of narrower spectral bandwidth-beneficial for filtering out sunlight-and negligible multiphoton emission at peak brightness. We demonstrate continuous operation over the course of three days, across an urban 270 m-long free-space optical link, under different light and weather conditions

    The future of Cybersecurity in Italy: Strategic focus area

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    This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

    Quantum sensing networks for the estimation of linear functions

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    The theoretical framework for networked quantum sensing has been developed to a great extent in the past few years, but there are still a number of open questions. Among these, a problem of great significance, both fundamentally and for constructing efficient sensing networks, is that of the role of inter-sensor correlations in the simultaneous estimation of multiple linear functions, where the latter are taken over a collection local parameters and can thus be seen as global properties. In this work we provide a solution to this when each node is a qubit and the state of the network is sensor-symmetric. First we derive a general expression linking the amount of inter-sensor correlations and the geometry of the vectors associated with the functions, such that the asymptotic error is optimal. Using this we show that if the vectors are clustered around two special subspaces, then the optimum is achieved when the correlation strength approaches its extreme values, while there is a monotonic transition between such extremes for any other geometry. Furthermore, we demonstrate that entanglement can be detrimental for estimating non-trivial global properties, and that sometimes it is in fact irrelevant. Finally, we perform a non-asymptotic analysis of these results using a Bayesian approach, finding that the amount of correlations needed to enhance the precision crucially depends on the number of measurement data. Our results will serve as a basis to investigate how to harness correlations in networks of quantum sensors operating both in and out of the asymptotic regime
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