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SafeScale project C. CERIN, J.L. PAZAT, J.L. ROCH, R. KERYELL
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SafeScale project C. CERIN, J.L. PAZAT, J.L. ROCH, R. KERYELL https://www-lipn.univ-paris13.fr/safescale/
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Transcript of SafeScale project C. CERIN, J.L. PAZAT, J.L. ROCH, R. KERYELL
SafeScale projectC. CERIN, J.L. PAZAT, J.L. ROCH, R. KERYELL
https://www-lipn.univ-paris13.fr/safescale/
SafeScale overview
Funded by ANR (Agence Nationale de la Recherche)
3 years term project (started on January 1st, 2006)
Partners LIPN (Paris XIII) (coordinator) [email protected] IMAG/INRIA (Grenoble), [email protected] IRISA/INRIA (Rennes), [email protected] ENSTB (Brest) [email protected] Université Joseph Fourier (Grenoble). [email protected]
Research focus Security and safety in global ambient computing systems
computational grid peer-to-peer environments.
Environment Middleware provides strong authentication, secure communications and
resource management. Computational nodes operate in an unbounded environment subjected to
a wide range of attacks.
• Fail-stop failures: connection/disconnections of heterogeneous resources
• Malicious failures: forgery of results on resources (Trojan horses, …) Challenge
Develop applications with guarantees on correctness of computed results.
Two kinds of security issues (1/2)
Internet
1. Node failures “fail stop” model
User
Two kinds of security issues (2/2)
Internet
1. Task forgery– “massive attacks”
Userworm,virus
bad result
Works objective
• study and evaluate a methodology and tools to obtain certified results. our approach
• Adaptability to support addition / resilience of resources– dynamic task scheduling and mapping– adaptability of software components
• Probabilistic certification of results to support forgeries– Verifications of few randomly chosen tasks– Performed on trusted resources (hardware crypto-processor)
• Validation on two class of large scale computational applications– data merging and sorting– finite field computations
experiments • on the grid'5000 architecture
Running an application: from this...
To that...
How to detect: random faults (type 1) or malicious (systematic) faults (type 2)?
Send certified codes on ill machines to detect the natureof faults? (testing?)
Known/Unknown tools, results Platforms: Kaapi, XtremWeb, Grid5000 Fault-tolerance and adaptive programming (IRISA, IMAG)
Key point : application adaptability• Fine-grain work stealing [IMAG] (provable
performances on processors with changing speeds)• Adaptation of components [IRISA]
Probabilistic certification (ENSTB, IMAG) Detection of massive attacks [IMAG] Crypto-processor (ENSTB)
Applications: Sorting on an heterogeneous cluster (LIPN) Classification of provably secure cryptographic boxes (UJF)
Conclusionhttps://www-lipn.univ-paris13.fr/safescale/pôle « Grille Système Parallélisme »
(http://gsp.asr.cnrs.fr/)action sécurité et sûreté
