Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 17-2-1 Attacking anonymized Information <s> Nowadays, partly driven by many Web 2.0 applications, more and more social network data has been made publicly available and analyzed in one way or another. Privacy preserving publishing of social network data becomes a more and more important concern. In this paper, we present a brief yet systematic review of the existing anonymization techniques for privacy preserving publishing of social network data. We identify the new challenges in privacy preserving publishing of social network data comparing to the extensively studied relational case, and examine the possible problem formulation in three important dimensions: privacy, background knowledge, and data utility. We survey the existing anonymization methods for privacy preservation in two categories: clustering-based approaches and graph modification approaches. <s> BIB001 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 17-2-1 Attacking anonymized Information <s> Many applications of social networks require identity and/or relationship anonymity due to the sensitive, stigmatizing, or confidential nature of user identities and their behaviors. Recent work showed that the simple technique of anonymizing graphs by replacing the identifying information of the nodes with random ids does not guarantee privacy since the identification of the nodes can be seriously jeopardized by applying background based attacks. In this paper, we investigate how well an edge based graph randomization approach can protect node identities and sensitive links. We quantify both identity disclosure and link disclosure when adversaries have one specific type of background knowledge (i.e., knowing the degrees of target individuals). We also conduct empirical comparisons with the recently proposed K-degree anonymization schemes in terms of both utility and risks of privacy disclosures. <s> BIB002 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 17-2-1 Attacking anonymized Information <s> Social networking sites have been increasingly gaining popularity. Well-known sites such as Facebook have been reporting growth rates as high as 3% per week. Many social networking sites have millions of registered users who use these sites to share photographs, contact long-lost friends, establish new business contacts and to keep in touch. In this paper, we investigate how easy it would be for a potential attacker to launch automated crawling and identity theft attacks against a number of popular social networking sites in order to gain access to a large volume of personal user information. The first attack we present is the automated identity theft of existing user profiles and sending of friend requests to the contacts of the cloned victim. The hope, from the attacker's point of view, is that the contacted users simply trust and accept the friend request. By establishing a friendship relationship with the contacts of a victim, the attacker is able to access the sensitive personal information provided by them. In the second, more advanced attack we present, we show that it is effective and feasible to launch an automated, cross-site profile cloning attack. In this attack, we are able to automatically create a forged profile in a network where the victim is not registered yet and contact the victim's friends who are registered on both networks. Our experimental results with real users show that the automated attacks we present are effective and feasible in practice. <s> BIB003 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 17-2-1 Attacking anonymized Information <s> In recent years, social networking sites (SNSs) gained high popularity among Internet users as they combine the best of both worlds: befriending people outside real life situations and staying in touch with people already known. An important aspect of any SNS are user profiles, which allow users to virtually publish anything about themselves, including highly personal or sensitive information. With the inception of SNSs, the problem of personal information disclosure and privacy implications has turned into a serious issue. While privacy issues in SNSs have been extensively analyzed in the past five years showcasing flagships of "western" SNSs like Facebook and MySpace, SNSs that target mainly Russian speaking audiences are not yet analyzed and demand investigation. The goals of this paper are twofold: (1) to raise the awareness of the public to the problems of information revelation by studying the amount and type of information disclosed by users of Runet (Russian Segment of the Internet) SNSs (2) to compare our findings to the results of previous studies in the context of "western" SNSs. We investigate different aspects of information revelation of more than 30 million user profiles collected from five Runet SNS considered in this paper. In addition, we conducted a survey among a Russian speaking population to assess both the level of awareness of the privacy issues and the level of trust, and compared the results to previous studies. While the results indicate that Runet users tend to disclose less information and are more concerned about privacy implications, there is still a substantial gap between western and Runet SNS providers in understanding of privacy implications and implementation of security measures, which leads to exposure of extensive amounts of personal information. <s> BIB004 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 17-2-1 Attacking anonymized Information <s> Anonymization of social networks before they are published or shared has become an important research question. Recent work on anonymizing social networks has looked at privacy preserving techniques for publishing a single instance of the network. However, social networks evolve and a single instance is inadequate for analyzing the evolution of the social network or for performing any longitudinal data analysis. We study the problem of repeatedly publishing social network data as the network evolves, while preserving privacy of users. Publishing multiple instances of the same network independently has privacy risks, since stitching the information together may allow an adversary to identify users in the networks. We propose methods to anonymize a dynamic network such that the privacy of users is preserved when new nodes and edges are added to the published network. These methods make use of link prediction algorithms to model the evolution of the social network. Using this predicted graph to perform group-based anonymization, the loss in privacy caused by new edges can be reduced. We evaluate the privacy loss on publishing multiple social network instances using our methods. <s> BIB005
Despite the efforts towards protecting users' private information when publishing SNSs information using anonymization, this information is still exposed to a special kind of attacks that aim at discovering information in anonymized information. Adversaries may use some background information to accomplish this kind of attacks. BIB001 [52] BIB004 For example the attacker may have some specific information about her target (the person who the attacker intends to get access to her information), and be able to recognize her target among the anonymized information BIB001 . In BIB004 three types of attacks are presented as active attacks, passive attacks, and semi-passive attacks : Passive attacks are described as those in which attackers begin their work to detect the identity of nodes after anonymized information is published; at the other side in active attacks the adversary tries to create some accounts in the SNS and establish some links in the network so that these links will be present in the anonymized version of the information; in semi-passive attacks there is no new account creation but some links are established with the target user before the information is anonymized. Having background information (both the information that the attackers themselves has injected to the network and the information that they have acquired in other ways) is an important tool in the hand of anonymized information attackers. In BIB001 some examples of background information are mentioned like attributes of vertices, vertex degree, and neighborhoods. In [69] using neighborhood information is presented as an example of a type of attacks called neighborhood attacks. In BIB002 vertex degree is said to be the most vastly used parameter. In BIB004 some studies about using interesting information like user prepared text for attacking anonymized data are cited (although in different contexts from the SN context of that paper). In BIB003 good information is presented about anonymization and deanonymization. In this paper a passive method is proposed for identity detection in anonymized information, and using it along with the information of two well known SNSs (twitter, flickr) notable results are obtained regarding identity detection of some members of these SNSs in the anonymized graph of twitter. In this work the information inside flickr is used as background information. An important point mentioned in BIB005 is that in the area of social networks anonymization, the main focus so far has been on a single instance of the network's information in a specific time, and this is inconsistent with the very dynamic nature of these networks. It is noted there that having several copies of anonymized data of a social network, which are taken in different times may lead to information revelation by comparing these copies.