355,890 research outputs found
Purging of untrustworthy recommendations from a grid
In grid computing, trust has massive significance. There is lot of research
to propose various models in providing trusted resource sharing mechanisms. The
trust is a belief or perception that various researchers have tried to
correlate with some computational model. Trust on any entity can be direct or
indirect. Direct trust is the impact of either first impression over the entity
or acquired during some direct interaction. Indirect trust is the trust may be
due to either reputation gained or recommendations received from various
recommenders of a particular domain in a grid or any other domain outside that
grid or outside that grid itself. Unfortunately, malicious indirect trust leads
to the misuse of valuable resources of the grid. This paper proposes the
mechanism of identifying and purging the untrustworthy recommendations in the
grid environment. Through the obtained results, we show the way of purging of
untrustworthy entities.Comment: 8 pages, 4 figures, 1 table published by IJNGN journal; International
Journal of Next-Generation Networks (IJNGN) Vol.3, No.4, December 201
GridCertLib: a Single Sign-on Solution for Grid Web Applications and Portals
This paper describes the design and implementation of GridCertLib, a Java
library leveraging a Shibboleth-based authentication infrastructure and the
SLCS online certificate signing service, to provide short-lived X.509
certificates and Grid proxies. The main use case envisioned for GridCertLib, is
to provide seamless and secure access to Grid/X.509 certificates and proxies in
web applications and portals: when a user logs in to the portal using
Shibboleth authentication, GridCertLib can automatically obtain a Grid/X.509
certificate from the SLCS service and generate a VOMS proxy from it. We give an
overview of the architecture of GridCertLib and briefly describe its
programming model. Its application to some deployment scenarios is outlined, as
well as a report on practical experience integrating GridCertLib into portals
for Bioinformatics and Computational Chemistry applications, based on the
popular P-GRADE and Django softwares.Comment: 18 pages, 1 figure; final manuscript accepted for publication by the
"Journal of Grid Computing
A Security Monitoring Framework For Virtualization Based HEP Infrastructures
High Energy Physics (HEP) distributed computing infrastructures require
automatic tools to monitor, analyze and react to potential security incidents.
These tools should collect and inspect data such as resource consumption, logs
and sequence of system calls for detecting anomalies that indicate the presence
of a malicious agent. They should also be able to perform automated reactions
to attacks without administrator intervention. We describe a novel framework
that accomplishes these requirements, with a proof of concept implementation
for the ALICE experiment at CERN. We show how we achieve a fully virtualized
environment that improves the security by isolating services and Jobs without a
significant performance impact. We also describe a collected dataset for
Machine Learning based Intrusion Prevention and Detection Systems on Grid
computing. This dataset is composed of resource consumption measurements (such
as CPU, RAM and network traffic), logfiles from operating system services, and
system call data collected from production Jobs running in an ALICE Grid test
site and a big set of malware. This malware was collected from security
research sites. Based on this dataset, we will proceed to develop Machine
Learning algorithms able to detect malicious Jobs.Comment: Proceedings of the 22nd International Conference on Computing in High
Energy and Nuclear Physics, CHEP 2016, 10-14 October 2016, San Francisco.
Submitted to Journal of Physics: Conference Series (JPCS
Grid enabled virtual screening against malaria
34 pages, 5 figures, 3 tables, to appear in Journal of Grid Computing - PCSV, à paraître dans Journal of Grid ComputingWISDOM is an international initiative to enable a virtual screening pipeline on a grid infrastructure. Its first attempt was to deploy large scale in silico docking on a public grid infrastructure. Protein-ligand docking is about computing the binding energy of a protein target to a library of potential drugs using a scoring algorithm. Previous deployments were either limited to one cluster, to grids of clusters in the tightly protected environment of a pharmaceutical laboratory or to pervasive grids. The first large scale docking experiment ran on the EGEE grid production service from 11 July 2005 to 19 August 2005 against targets relevant to research on malaria and saw over 41 million compounds docked for the equivalent of 80 years of CPU time. Up to 1,700 computers were simultaneously used in 15 countries around the world. Issues related to the deployment and the monitoring of the in silico docking experiment as well as experience with grid operation and services are reported in the paper. The main problem encountered for such a large scale deployment was the grid infrastructure stability. Although the overall success rate was above 80%, a lot of monitoring and supervision was still required at the application level to resubmit the jobs that failed. But the experiment demonstrated how grid infrastructures have a tremendous capacity to mobilize very large CPU resources for well targeted goals during a significant period of time. This success leads to a second computing challenge targeting Avian Flu neuraminidase N1
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