Concept

Deep packet inspection

Publications associées (50)

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

EPFL2023

On Calculating the Minimum Rate for the Cooperative Data Exchange Problem Over Fully Connected Networks

Michael Christoph Gastpar, Su Li

We study the cooperative data exchange problem for fully connected networks. In this problem, nodes make broadcast transmissions to recover a file consisting of K independent packets. Each node initially only possesses a subset of the packets. We propose ( ...

2021

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Pascal Fua, Mathieu Salzmann, Agata Justyna Mosinska, Mateusz Kozinski

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation giv ...

ELSEVIER2020

Joint Segmentation and Path Classification of Curvilinear Structures

Pascal Fua, Agata Justyna Mosinska, Mateusz Kozinski

Detection of curvilinear structures in images has long been of interest. One of the most challenging aspects of this problem is inferring the graph representation of the curvilinear network. Most existing delineation approaches first perform binary segment ...

2020

Content Based Status Updates

Emre Telatar, Elie Najm, Rajai Nasser

Consider a stream of status updates generated by a source, where each update is of one of two types: high priority or ordinary (low priority). These updates are to be transmitted through a network to a monitor. However, the transmission policy of each pack ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Joint Segmentation and Path Classification of Curvilinear Structures

Pascal Fua, Agata Justyna Mosinska, Mateusz Kozinski

2019

Collaborative Filtering Under a Sybil Attack: Similarity Metrics do Matter!

Rachid Guerraoui, Anne-Marie Kermarrec, Davide Frey, Antoine Rault, Florestan Laurentin Marie De Moor

Recommendation systems help users identify interesting content, but they also open new privacy threats. In this paper, we deeply analyze the effect of a Sybil attack that tries to infer information on users from a user-based collaborative-filtering recomme ...

IEEE2018

Automated Synthesis of Adversarial Workloads for Network Functions

Arseniy Zaostrovnykh, Rishabh Ramesh Iyer, Jonas Fietz, Luis David Figueiredo Mascarenhas Moreira Pedrosa

Software network functions promise to simplify the deployment of network services and reduce network operation cost. However, they face the challenge of unpredictable performance. Given this performance variability, it is imperative that during deployment, ...

ACM2018

Multiple Objectives of Lawful-Surveillance Protocols

Bryan Alexander Ford

In recent work on open, privacy-preserving, accountable surveillance, we have proposed the use of cryptographic protocols that enable law-enforcement and intelligence agencies to obtain actionable information about targeted users of mass-communication syst ...

2017

Data-Driven, Personalized Usable Privacy

Hamza Harkous

We live in the "inverse-privacy" world, where service providers derive insights from users' data that the users do not even know about. This has been fueled by the advancements in machine learning technologies, which allowed providers to go beyond the supe ...

EPFL2017

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