Publications associées à USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation

Publications associées (33)

Secure Interface Design Leveraging Hardware/Software Support

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

EPFL2024

ACTOR: Action-Guided Kernel Fuzzing

Mathias Josef Payer

Fuzzing reliably and efficiently finds bugs in software, including operating system kernels. In general, higher code coverage leads to the discovery of more bugs. This is why most existing kernel fuzzers adopt strategies to generate a series of inputs that ...

Usenix Assoc2023

Arvin: Greybox Fuzzing Using Approximate Dynamic CFG Analysis

Mathias Josef Payer

Fuzzing has emerged as the most broadly used testing technique to discover bugs. Effective fuzzers rely on coverage to prioritize inputs that exercise new program areas. Edge-based code coverage of the Program Under Test (PUT) is the most commonly used cov ...

ASSOC COMPUTING MACHINERY2023

End-to-end kernel learning via generative random Fourier features

Fanghui Liu

Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...

ELSEVIER SCI LTD2023

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Benoît Walter Denkinger

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

EPFL2023

VIDEZZO: Dependency-aware Virtual Device Fuzzing

Mathias Josef Payer, Flavio Toffalini, Qiang Liu

A virtual machine interacts with its host environment through virtual devices, driven by virtual device messages, e.g., I/O operations. By issuing crafted messages, an adversary can exploit a vulnerability in a virtual device to escape the virtual machine, ...

Institute of Electrical and Electronics Engineers Inc.2023

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

David Daniel Girardier, Fabio Pietrucci, Sara Bonella

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Aip Publishing2023

A 3.3-Gb/s SPAD-Based Quantum Random Number Generator

Edoardo Charbon, Francesco Gramuglia, Pouyan Keshavarzian

Quantum random number generators (QRNGs) are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in or ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

Mathias Josef Payer

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

Usenix Assoc2023

Creating Trust by Abolishing Hierarchies

Mathias Josef Payer, Edouard Bugnion, Evangelos Marios Kogias, Adrien Ghosn, Charly Nicolas Lucien Castes, Yuchen Qian, Neelu Shivprakash Kalani

Software is going through a trust crisis. Privileged code is no longer trusted and processes insufficiently protect user code from unverified libraries. While usually treated separately, confidential computing and program compartmentalization are both symp ...

Association for Computing Machinery2023

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Bogdan Kulynych

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

EPFL2023

Midas: Systematic Kernel TOCTTOU Protection

Uros Tesic, Mathias Josef Payer, Atri Bhattacharyya

Double-fetch bugs are a plague across all major operating system kernels. They occur when data is fetched twice across the user/kernel trust boundary while allowing concurrent modification. Such bugs enable an attacker to illegally access memory, cause den ...

2022

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Antonio Sclocchi, Umberto Maria Tomasini

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Deep Reinforcement Learning for Random Access in Machine-Type Communication

Fernando Perez Cruz

Random access (RA) schemes are a topic of high interest in machine-type communication (MTC). In RA protocols, backoff techniques such as exponential backoff (EB) are used to stabilize the system to avoid low throughput and excessive delays. However, these ...

IEEE2022

Toward Mobile Distributed Ledgers

Boi Faltings, Sujit Prakash Gujar

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on Device-to-Device (D2D) ecosystems (e.g., crowdsensing). Sophisticated applications, like cryptocurrencies, need distr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Kernel Memory Networks: A Unifying Framework for Memory Modeling

Wulfram Gerstner, Johanni Michael Brea, Georgios Iatropoulos

We consider the problem of training a neural network to store a set of patterns with maximal noise robustness. A solution, in terms of optimal weights and state update rules, is derived by training each individual neuron to perform either kernel classifica ...

Curran Associates2022

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!

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