Publications associées à Sécurité du réseau

Machine Learning Security Against Data Poisoning: Are We There Yet?

Poisoning attacks compromise the training data utilized to train machine learning (ML) models, diminishing their overall performance, manipulating predictions on specific test samples, and implanting backdoors. This article thoughtfully explores these atta ...

Ieee Computer Soc2024

Machine Learning Security in Industry: A Quantitative Survey

Kathrin Grosse

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

HyperLogLog: Exponentially Bad in Adversarial Settings

Mathilde Aliénor Raynal

Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a ...

IEEE COMPUTER SOC2022

Safeguarding the IoT From Malware Epidemics: A Percolation Theory Approach

Ainur Zhaikhan

The upcoming Internet of Things (IoT) is foreseen to encompass massive numbers of connected devices, smart objects, and cyber-physical systems. Due to the large scale and massive deployment of devices, it is deemed infeasible to safeguard 100% of the devic ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads

Martin Jaggi, Sebastian Urban Stich, Hossein Shokri Ghadikolaei

In distributed optimization, parameter updates from the gradient computing node devices have to be aggregated in every iteration on the orchestrating server. When these updates are sent over an arbitrary commodity network, bandwidth and latency can be limi ...

MICROTOME PUBLISHING2021

OrthoNet: Multilayer Network Data Clustering

Pascal Frossard, Mireille El Gheche, Giovanni Chierchia

Network data appears in very diverse applications, like biological, social, or sensor networks. Clustering of network nodes into categories or communities has thus become a very common task in machine learning and data mining. Network data comes with some ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

FirmFuzz: Automated IoT Firmware Introspection and Analysis

Mathias Josef Payer, Hui Peng

While the number of IoT devices grows at an exhilarating pace their security remains stagnant. Imposing secure coding standards across all vendors is infeasible. Testing individual devices allows an analyst to evaluate their security post deployment. Any d ...

ASSOC COMPUTING MACHINERY2019

Labeled PSI from Fully Homomorphic Encryption with Malicious Security

Zhicong Huang

Private Set Intersection (PSI) allows two parties, the sender and the receiver, to compute the intersection of their private sets without revealing extra information to each other. We are interested in the unbalanced PSI setting, where (1) the receiver's s ...

ASSOC COMPUTING MACHINERY2018

OmniLedger: A Secure, Scale-Out, Decentralized Ledger via Sharding

Bryan Alexander Ford, Linus Gasser, Eleftherios Kokoris Kogias, Philipp Svetolik Jovanovic, Nicolas Gailly

Designing a secure permissionless distributed ledger (blockchain) that performs on par with centralized payment processors, such as Visa, is a challenging task. Most existing distributed ledgers are unable to scale-out, i.e., to grow their total processing ...

IEEE2018

Adding flexibility to multi-tenant networks

Georgios Ioannidis

Cloud computing has been experiencing sharp development over the last years, leading to an increased demand for application migration to the cloud. Cloud providers, in an effort to attract more customers and earn their confidence, offer to tenants the illu ...

EPFL2018