Concept

Attaque par déni de service

Publications associées (144)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Consensus protocols for asynchronous networks are usually complex and inefficient, leading practical systems to rely on synchronous protocols. The invention proposes an approach to simplify asynchronous consensus by building it atop a novel threshold logic ...

2021

Towards Efficient LPN-Based Symmetric Encryption

Serge Vaudenay, Sonia Mihaela Bogos, Dario Korolija, Thomas Locher

Due to the rapidly growing number of devices that need to communicate securely, there is still significant interest in the development of efficient encryption schemes. It is important to maintain a portfolio of different constructions in order to enable a ...

Springer International Publishing2021

QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval

Shaokai Ye, Yuan He, Hang Su, Jinfeng Li

We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-1 ranked unlabeled images from the database. Compared with que ...

IEEE COMPUTER SOC2021

A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

Giancarlo Ferrari Trecate, Mustafa Sahin Turan

DC microgrids often present a hierarchical control architecture, requiring integration of communication layers. This leads to the possibility of malicious attackers disrupting the overall system. Motivated by this application, in this article, we present a ...

2020

Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...

IEEE2020

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

2020

, ,

The High-Quality Wide Multi-Channel Attack database (HQ-WMCA) database extends the previous Wide Multi-Channel Attack database(WMCA) \citegeorge_mccnn_tifs2019, with more channels including color, depth, thermal, infrared (spectra), and short-wave infrared ...

Idiap2020

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

Rafael Pereira Pires, Pascal Felber

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 ...

2020

Deep Models and Shortwave Infrared Information to Detect Face Presentation Attacks

Sébastien Marcel, Guillaume Heusch, Zohreh Mostaani

This paper addresses the problem of face presentation attack detection using different image modalities. In particular, the usage of short wave infrared (SWIR) imaging is considered. Face presentation attack detection is performed using recent models based ...

IEEE2020

Learning One Class Representations for Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Sébastien Marcel

Idiap2020