عنوان انگلیسی مقاله:
Privacy Preservation for Social Networks Sequential Publishing
ترجمه فارسی عنوان مقاله:
حفظ حریم خصوصی برای انتشارات متوالی شبکه های اجتماعی
Sciencedirect - Elsevier - © 2020 Published by Elsevier B:V:
Safia Bourahla, Maryline Laurent, Yacine Challal
The proliferation of social networks allowed creating a big quantity of data
about users and their relationships. Such data contain much private information.
Therefore, anonymization is required before publishing the data for
data mining purposes (scientific research, marketing, decision support, etc).
Most of the anonymization works in social networks focus on publishing one
instance while not considering the need for anonymizing sequential releases.
However, many cases show that sequential releases may infer private information
even though individual instances are anonymized. This paper studies
the privacy issues of sequential releases and proposes a privacy preserving
solution for this case. The proposed solution ensures three privacy requirements
(users’ privacy, groups’ privacy and edges’ privacy), and it considers
the case where many users and groups may share the same profiles. Some
experiments over some complex queries show that the utility of the released
data is better preserved than other solutions, with regard to the privacy of
users, groups and edges.
Keywords: Privacy preserving | Social networks | Anonymization | Sequential releases