  The e-learning systems are designed to provide an easy and constant access to
educational resources online. Indeed, E-learning systems have capacity to adapt
content and learning process according to the learner profile. Adaptation
techniques using advanced behavioral analysis mechanisms, called "Learner
Modeling" or "Profiling". The latter require continuous tracking of the
activities of the learner to identify gaps and strengths in order to tailor
content to their specific needs or advise and accompany him during his
apprenticeship. However, the disadvantage of these systems is that they cause
learners' discouragement, for learners, alone with his screen loses its
motivation to improve. Adding social extension to learning, to avoid isolation
of learners and boost support and interaction between members of the learning
community, was able to increase learner's motivation. However, the tools to
facilitate social interactions integrated to E-learning platforms can be used
for purposes other than learning. These needs, which can be educational,
professional or personal, create a mixture of data from the private life and
public life of learners. With the integration of these tools for e-learning
systems and the growth of the amount of personal data stored in the databases
of these latter, protecting the privacy of students becomes a major concern.
Indeed, the exchange of profiles between e-learning systems is done without the
permission of their owners. Furthermore, the profiling behavior analysis
currently represents a very cost-effective way to generate profits by selling
these profiles advertising companies. Today, the right to privacy is threatened
from all sides. In addition to the threat from pirates, the source of the most
dangerous threats is that from service providers online that users devote a
blind trust. Control and centralized data storage and access privileges that
have suppliers are responsible for the threat. Our work is limited to the
protection of personal data in e-learning systems. We try to answer the
question: How can we design a system that protects the privacy of users against
threats from the provider while benefiting from all the services, including
analysis of behavior? In the absence of solutions that take into account the
protection and respect of privacy in e-learning systems that integrate social
learning tools, we designed our own solution. Our "ApprAide" system uses a set
of protocols based on security techniques to protect users' privacy. In
addition, our system incorporates tools that promote social interactions as a
social learning network, a chat tool and a virtual table. Our solution allows
the use of adaptation techniques and profiling to assist learners. Keywords:
Social learning, privacy, security, e-learning, agents
