Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

CORNET

Financiado

Cerrado

Provably Correct Networks

Networks are the backbone of our society, but configuring them is error-prone and tedious: misconfigured networks result in headline grabbing network outages that affect many users and hurt company revenues while security breaches... ver más

30/06/2023

TAT

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

TARGET ACTIVE TRAINING No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-06-30

ERC-2017-STG: ERC Starting Grant

I+D

Cerrada hace 8 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

TAT

1.33M€ | Lider

Proyectos interesantes

SYMBIOSYS

Software

Cybersecurity

2M€ Cerrado

PROOFCERT

Software

Cybersecurity

2M€ Cerrado

SafeNet

Software

Cybersecurity

150K€ Cerrado

iTrust6G

Cybersecurity

Software

5M€ Cerrado

CARBS

Software

Data Science

92K€ Cerrado

REVEN-X1

Cybersecurity

Software

71K€ Cerrado

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Duración del proyecto: 69 meses Fecha Inicio: 2017-09-18
Fecha Fin: 2023-06-30

Líder del proyecto

TARGET ACTIVE TRAINING No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Networks are the backbone of our society, but configuring them is error-prone and tedious: misconfigured networks result in headline grabbing network outages that affect many users and hurt company revenues while security breaches that endanger millions of customers. There are currently no guarantees that deployed networks correctly implement their operator’s policy. Existing research has focused on two directions: a) low level analysis and instrumentation of real networking code prevents memory bugs in individual network elements, but does not capture network-wide properties desired by operators such as reachability or loop freedom; b) high-level analysis of network-wide properties to verify operator policies on abstract network models; unfortunately, there are no guarantees that the models are an accurate representation of the real network code, and often low-level errors invalidate the conclusions of the high-level analysis. We propose to achieve provably correct networks by simultaneously targeting both low-level security concerns and network-wide policy compliance checking. Our key proposal is to rely on exhaustive network symbolic execution for verification and to automatically generate provably correct implementations from network models. Generating efficient code that is equivalent to the model poses great challenges that we will address with three key contributions: a) We will develop a novel theoretical equivalence framework based on symbolic execution semantics, as well as equivalence-preserving model transformations to automatically optimize network models for runtime efficiency. b) We will develop compilers that take network models and generate functionally equivalent and efficient executable code for different targets (e.g. P4 and C). c) We will design algorithms that generate and insert runtime guards that ensure correctness of the network with respect to the desired policy even when legacy boxes are deployed in the network.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores