AnonyLikes: Anonymous Quantitative Feedback on Social Networks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

AnonyLikes: Anonymous Quantitative Feedback on Social Networks

Résumé

Social network applications (SNAs) can have a tremendous impact in raising awareness to important controversial topics such as religion or politics. Sharing and liking are powerful tools to make some of those topics emerge to a global scale, as already witnessed in the recent Tunisian and Egyptian revolutions.However, in several countries the simple act of liking an anti-government article or video can be (and has already been) used to pursue and detain activists. Therefore, it is of utmost relevance to allow anyone to anonymously ”like” any social network content (e.g. at Facebok) even in presence of malicious administrators managing the social network infrastructure.We present anonyLikes, a protocol which allows SNAs users to ”like” a certain post (e.g., news, photo, video) without revealing their identity (even to the SNA itself) but still make their ”like” count to the total number of ”likes”. This is achieved using cryptographic techniques such as homomorphic encryption and shared threshold key pairs. In addition, the protocol ensures all other desirable properties such as preventing users from ”liking” a particular post more than once, while preserving anonymity.The anonyLikes protocol is fully implemented using Facebook as an example and can be easily used by developers (e.g. Facebook itself or other social network applications and infrastructures) to provide an alternative ”like” button called ”anonyLike”.
Fichier principal
Vignette du fichier
978-3-642-45065-5_24_Chapter.pdf (380.12 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01480788 , version 1 (01-03-2017)

Licence

Paternité

Identifiants

Citer

Pedro Alves, Paulo Ferreira. AnonyLikes: Anonymous Quantitative Feedback on Social Networks. 14th International Middleware Conference (Middleware), Dec 2013, Beijing, China. pp.466-484, ⟨10.1007/978-3-642-45065-5_24⟩. ⟨hal-01480788⟩
94 Consultations
113 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More