USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation

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Publications associées (32)

What can linearized neural networks actually say about generalization?

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Guillermo Ortiz Jimenez

For certain infinitely-wide neural networks, the neural tangent kernel (NTK) theory fully characterizes generalization, but for the networks used in practice, the empirical NTK only provides a rough first-order approximation. Still, a growing body of work ...

2021

A conformal dispersion relation: correlations from absorption

Din Carmi

We introduce the analog of Kramers-Kronig dispersion relations for correlators of four scalar operators in an arbitrary conformal field theory. The correlator is expressed as an integral over its "absorptive part", defined as a double discontinuity, times ...

Springer Nature2020

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Michele Ceriotti, Michael John Willatt

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020

Malware in the SGX supply chain: Be careful when signing enclaves!

Pascal Felber, Rafael Pereira Pires

Malware attacks are a significant part of the new software security threats detected each year. Intel Software Guard Extensions (SGX) are a set of hardware instructions introduced by Intel in their recent lines of processors that are intended to provide a ...

2022

Symmetric Asynchronous Ratcheted Communication with Associated Data

Serge Vaudenay, Hailun Yan

Following up mass surveillance and privacy issues, modern secure communication protocols now seek strong security, such as forward secrecy and post-compromise security, in the face of state exposures. To address this problem, ratcheting was thereby introdu ...

Springer, Cham2020

Kernel Density Estimation through Density Constrained Near Neighbor Search

Mikhail Kapralov, Navid Nouri

In this paper we revisit the kernel density estimation problem: given a kernel K(x, y) and a dataset of n points in high dimensional Euclidean space, prepare a data structure that can quickly output, given a query q, a (1 + epsilon)-approximation to mu := ...

IEEE2020

Snap-On User-Space Manager for Dynamically Reconfigurable System-on-Chips

Paolo Ienne, Sahand Kashani, Andrea Guerrieri

Due to increased embedded processing requirements, modern SoCs are becoming heterogeneous computing platforms by combining traditional processing units with custom reconfigurable hardware accelerators (HAs) on an FPGA fabric. However, efficiently managing ...

2019

i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing

David Atienza Alonso, Soumya Subhra Basu, Giovanni Ansaloni, Loris Gérard Duch, Miguel Peon Quiros

Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...

2019

Fully-Asynchronous Cache-Efficient Simulation of Detailed Neural Networks

Felix Schürmann, Michael Lee Hines

Modern asynchronous runtime systems allow the re-thinking of large-scale scientific applications. With the example of a simulator of morphologically detailed neural networks, we show how detaching from the commonly used bulk-synchronous parallel (BSP) exec ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

BenchIoT: A Security Benchmark for the Internet of Things

Mathias Josef Payer

Attacks against IoT systems are increasing at an alarming pace. Many IoT systems are and will be built using low-cost micro-controllers (IoT-pCs). Different security mechanisms have been proposed for IoT-mu Cs with different trade-offs. To guarantee a real ...

IEEE COMPUTER SOC2019

Material and Electrical study of HfO2-Based Resistive Random Access Memories (ReRAMs)

Behnoush Attarimashalkoubeh

Resistive Random Access Memories (ReRAMs) have been researched intensively in the last past decades as a promising alternatives technology for the next-generation non-volatile memory (NVM) devices. ReRAMâ s excellent performance properties such as high sw ...

EPFL2019

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Michaël Unser, Quy Ha Nguyen

In our recent work, the sampling and reconstruction of non-decaying signals, modeled as members of weighted-L-p spaces, were shown to be stable with an appropriate choice of the generating kernel for the shift-invariant reconstruction space. In this paper, ...

2019

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