Name
Fadhlallah
Family name
Baklouti
Birthday
5th of February 1991
Job
Ph.D. student
Emails
fadhlallah.baklouti@univ-ubs.fr
baklouti.fadhlallah@gmail.com
Address
n/a
Team
CASA, IRISA Lab
Languages
Arab: native
French: fluent
English:fluent
Spanish:elementary

Fadhlallah Baklouti is a computer engineer and a Ph.D. student at University of South Brittany. Interested in networks, security and operating systems.
He is particularly fascinated by:

  • Wireless networking,
  • Networks security,
  • Operating systems (GNU/Linux),
  • Network Flows and log analysis,
  • Delay tolerant networks,
  • Opportunistic networks.

University of South Brittany(2014-)
Ph.D. in computer science
National School of Computer Science(ENSI tunisie)(2011-2014)
National engineering diploma in computer science with Network and Distributed System option
Sfax Engineering Study Preparatory Institute (IPEIS)(2009-2011)
First cycle diploma (MP mathematics-physics)
Ph.D. in CASA, IRISA Lab

Definition of an adaptive service-oriented shared space for spontaneous ephemeral social networks


The objective of the thesis is to facilitate sharing and access to digital contents (photo, video, text…) produced within an SESN, through the definition of a adaptive distributed shared space. The data, the offered functions and the behavior of this shared space will be dynamically defined, according to the services provided by the participants of the SESN. For example, if a participant proposes a service that produces pictures of a certain quality (e.g. color pictures of more than 5 millions of pixels), the shared space will allow the users to know that such kind of pictures are available for consultation. The space will ease the access to the pictures by hiding the invocation of the service that provides them. Some data may be private, or destined to a specific community of users. The services that provide these data will implement an authentication mecanism, which will be automatically inherited by the shared space. By frequently consulting the data produced by some users, or by annotating them favorably, the shared space will perform dynamic service recommendation, thus favoring the invocation of some services and limiting data traffic in the SESN (only the relevant data will be present in the shared space).
This shared space should be operational even in the case where no cellular network is permanently reachable. Using Wi-Fi in ad hoc mode (or in P2P mode) could be an alternative, by leveraging on Disruption-Tolerant Networking, or Opportunistic Networking, so as to ensure an end-to-end connectivity between the devices participating in the SESN.

Graduation Internship in Madynes, INRIA Nancy Grand Est

Analysis and Visualization of Flow-based Mobile Traffic


the work consist in the conception and development of a tool that is capable of analizing and visualizing network flows collected by probes integrated in Android environments. The goal is, first, to elaborate analysis and correlation methods for flows collected and saved in a database. Second, the visualization tool will be developed and integrated within a software framework dedicated to Android environment security analysis .
Technologies: Cisco systems netflow services export version 9, HBASE, D3JS, Apache Spark, Android.
Key words: Machine learning, neural networks(SOM), unsupervised learning, networking.