Privacy Enhancing Solutions for Personal Information Based Multimedia Content Sharing

With the development and diffusion of compact and portable mobile devices, users can use multimedia content such as music and movie on personal mobile devices, anytime and anywhere. However, even with the rapid development of mobile device technology, it is still not easy to search multimedia content or manage large volume of content in a mobile device with limited resources. To resolve these problems, an approach for recommending content on the server-side is one of the popular solutions. However, the recommendation in a server also leads to some problems like the scalability for a lot of users and the management of personal information. Therefore, this paper defines a personal content manager which acts between content providers (server) and mobile devices and proposes a method for recommending multimedia content in the personal content manager. For the recommendation based on user's personal characteristic and preference, this paper adopts and applies the DISC model which is verified in psychology field for classifying user's behavior pattern. The proposed recommendation method also includes an algorithm for reflecting dynamic environmental context. Through the implements and evaluation of a prototype system, this paper shows that the proposed method has acceptable performance for multimedia content recommendation.

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PANOLA: A Personal Assistant for Supporting Users in Preserving Privacy

ACM Transactions on Internet Technology ◽

10.1145/3471187 ◽

2022 ◽

Vol 22 (1) ◽

pp. 1-32

Author(s):

Onuralp Ulusoy ◽

Pinar Yolum

Keyword(s):

Personal Information ◽

Online Social Network ◽

Single Individual ◽

Online Systems ◽

Content Sharing ◽

Shared Content ◽

Personal Assistant ◽

Privacy Constraints ◽

Personal Assistants ◽

The Right

Privacy is the right of individuals to keep personal information to themselves. When individuals use online systems, they should be given the right to decide what information they would like to share and what to keep private. When a piece of information pertains only to a single individual, preserving privacy is possible by providing the right access options to the user. However, when a piece of information pertains to multiple individuals, such as a picture of a group of friends or a collaboratively edited document, deciding how to share this information and with whom is challenging. The problem becomes more difficult when the individuals who are affected by the information have different, possibly conflicting privacy constraints. Resolving this problem requires a mechanism that takes into account the relevant individuals’ concerns to decide on the privacy configuration of information. Because these decisions need to be made frequently (i.e., per each piece of shared content), the mechanism should be automated. This article presents a personal assistant to help end-users with managing the privacy of their content. When some content that belongs to multiple users is about to be shared, the personal assistants of the users employ an auction-based privacy mechanism to regulate the privacy of the content. To do so, each personal assistant learns the preferences of its user over time and produces bids accordingly. Our proposed personal assistant is capable of assisting users with different personas and thus ensures that people benefit from it as they need it. Our evaluations over multiagent simulations with online social network content show that our proposed personal assistant enables privacy-respecting content sharing.

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