SocialSpy: Browsing (Supposedly) Hidden Information in Online Social Networks

Abstract

Online Social Networks are becoming the most important "places" where people share information about their lives. With the increasing concern that users have about privacy, most social networks offer ways to control the privacy of the user. Unfortunately, we believe that current privacy settings are not as effective as users might think. In this paper, we highlight this problem focusing on one of the most popular social networks, Facebook. In particular, we show how easy it is to retrieve information that a user might have set as (and hence thought as) "private". As a case study, we focus on retrieving the list of friends for users that did set this information as "hidden" (to non-friends). We propose four different strategies to achieve this goal, and we evaluate them. The results of our thorough experiments show the feasibility of our strategies as well as their effectiveness: our approach is able to retrieve a significant percentage of the names of the "hidden" friends: i.e., some 25% on average, and more than 70% for some users.

The insider on the outside: a novel system for the detection of information leakers in social networks

“…Among these four strategies, Strategy 4 has proven to be the fastest and with the highest average (37.12%) of friends found. Respectively Strategy 1 with an average of 17.5% of retrieved friends, Strategy 2 with an average of 17.4% of retrieved friends and Strategy 3 with an average of 20.8% of retrieved friends (Burattin, Cascavilla, and Conti 2015). Based on these results we follow Strategy 4 in our experiments.…”

“…To rebuild the egocentric network of a UoI we use SocialSpy (Burattin, Cascavilla, and Conti 2015). SocialSpy was developed to retrieve the lists of friends of each UoI, given her publicly available information, such as public friends, pictures, group memberships, and page likes.…”

“…The cyber environment is becoming increasingly complex. The field of intelligence gathering is concerned with covert operations, attempts to crack and access protected information assets and supporting infrastructures, and the collection and analysis of Open Source INTelligence (OSINT) (Burattin, Cascavilla, and Conti 2015;Kandias et al 2013). In the intelligence community, the term 'open' refers to overt publicly available sources -as opposed to covert or clandestine sources.…”

TRAP: Using Targeted ads to unveil Google personal profiles

“…More broadly, one can run campaigns in order to infer age or gender distribution of employees of particular companies, estimate the amount of time employees spend on Facebook, the fraction of employees who are interested in job opportunities elsewhere, etc. Similarly, in [6], [7], Cascavilla et al show several techniques to retrieve supposedly hidden information from Facebook user profile, while they do not rely on advertisements.…”

Who framed Roger Reindeer? De-censorship of Facebook posts by snippet classification

“…This work places itself amongst a few ones, like, e.g., [4,2] that investigate to which extent the connections among news articles, comments, and social media influence the effectiveness of identities censorship procedures. In particular, we present a novel approach to unveil a censored identity in a news post, by exploiting the fact that, on the social Web, it is not unusual to find the same content, or a very similar one, published elsewhere, e.g., by another publisher with different censorship policies.…”