Title :
Large Online Social Footprints--An Emerging Threat
Author :
Irani, Danesh ; Webb, Steve ; Li, Kang ; Pu, Calton
Author_Institution :
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
We study large online social footprints by collecting data on 13,990 active users. After parsing data from 10 of the 15 most popular social networking sites, we find that a user with one social network reveals an average of 4.3 personal information fields. For users with over 8 social networks, this average increases to 8.25 fields. We also investigate the ease by which an attacker can reconstruct a person´s social network profile. Over 40% of an individual´s social footprint can be reconstructed by using a single pseudonym (assuming the attacker guesses the most popular pseudonym), and an attacker can reconstruct 10% to 35% of an individual´s social footprint by using the person´s name. We also perform an initial investigation of matching profiles using public information in a person´s profile.
Keywords :
data privacy; social networking (online); information privacy; malicious attacker; online social footprint; person social network profile; personal information field; single pseudonym; social networking site; Computer science; Data engineering; Educational institutions; Facebook; MySpace; Preforms; Privacy; Size measurement; Social network services;
Conference_Titel :
Computational Science and Engineering, 2009. CSE '09. International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-5334-4
Electronic_ISBN :
978-0-7695-3823-5
DOI :
10.1109/CSE.2009.459