Download PhD Thesis Proposition Peer group management for

PhD Thesis Proposition
Proposition done by LIRIS laboratory in collaboration with LIP6 laboratory.
LIRIS (Computer of Science Laboratory specialized in pictures and information systems)
CNRS UMR 5205 – Claude Bernard University (Lyon I).
Bâtiment Nautibus (710), 43 Boulevard du 11 Novembre 1918 – 69622 Villeurbanne Cedex – FRANCE.
Contacts: Nicolas Lumineau ([email protected]) , Parisa Ghodous ([email protected])
and Anne Doucet ([email protected]).
Peer group management for personal data adaptive access
Nowadays Peer-to-Peer (P2P) Systems are essential to develop scalable application for resources sharing
like file, data, documents, etc. In order to improve resource sharing in unstructured P2P architecture, peer
clustering solutions have been proposed. The main idea is to logically cluster the peers which have similar
content or which have frequent interactions in order to improve the global behavior of the system.
Actually a large amount of personal data is shared through Internet, in particular through blogs and
community sites. Those systems perform as social network where profiles are exploited to put in tough
peoples. User profiles can be manually defined or automatically discovered from the own published data.
Thus, profiles and data are in free access for all users.
The purpose of this thesis is to define a privacy data model on which can be based an efficient network
auto-organization strategy. This research aims to consider data content and data privacy to cluster peer
and define an access control on shared data. A learning approach should be defined in order to discovery
some knowledge about peer. However, considering learning techniques in the dynamic and scalable
context of P2P architecture is not easy and relevant. In order to avoid the inconsistency of learnt
knowledge, a distributed strategy of peer group building, memorization and management should be
proposed.
This thesis is oriented around three research axes: P2P network auto-organization, data privacy model and
learning. During this thesis, a state of art will be done on secure systems [1] for data sharing, the research
will focus on P2P auto-organization process [2] which security limits are well identified [3] and it will
define solution to adapt peer clustering [4,5] in the context of personal data sharing. In order to collect
peer knowledge that will be necessary to learn, MAS technologies [6] should be considered.
References
[1] C. S. Powers, P. Ashley, M. Schunter, Privacy Promises, Access Control and Privacy Management. In proc. Of
the 3rd International Symposium on Electronic Commerce (ISEC’02). 2002.
[2] J. Risson, T. Moors Survey of research towards robust peer-to-peer networks: Search methods. Computer
Networks 50(17): 3485-3521 (2006)
[3] D. S. Wallach, A Survey of Peer-to-Peer Security Issues, International Symposium on Software Security
(Tokyo, Japan), November 2002.
[4] N. Lumineau, A. Doucet, B. Defude, VENISE: Content-based Clustering for Data Sharing in Peer-to-Peer
Architecture, In Proc. Base de Données Avancées (BDA'04), Montpellier, October 2004
[5] A. Chen, R.R. Muntz, "Peer Clustering: A Hybrid Approach to Distributed Virtual Environments," Proceedings
of the 5th Workshop on Network and System Support for Games (NetGames 2006), October 2006.
[6] J. Ferber, Les Systèmes multi-agents : Vers une intelligence collective, InterEditions, 1995.
Competences
This PhD thesis is defined for students with an Artificial Intelligence or Data Base profile. Theorical
competences are required on security of information systems and P2P architecture. Technical
competences will be useful on JAVA and JXTA.