CP2: Cryptographic privacy protection framework for online social networks

In Online Social Networks (OSNs), users interact with each other by sharing their personal information. One of the concerns in OSNs is how user privacy is protected since the OSN providers have full control over users’ data. The OSN providers typically store users’ information permanently; the privacy controls embedded in OSNs offer few options to users for customizing and managing the dissipation of their data over the network. In this paper, we propose an efficient privacy protection framework for OSNs that can be used to protect the privacy of users’ data and their online social relationships from third parties. The recommended framework shifts the control over data sharing back to the users by providing them with flexible and dynamic access policies. We employ a public-key broadcast encryption scheme as the cryptographic tool for managing information sharing with a subset of a user’s friends. The privacy and complexity evaluations show the superiority of our approach over previous.     

Not Even Past: Information Aging and Temporal Privacy in Online Social Networks

Online social networks (OSNs) make information accessible for unlimited periods and provide easy access to past information by arranging information in time lines or by providing sophisticated search mechanisms. Despite increased concerns over the privacy threat that is posed by digital memory, there is little knowledge about retrospective privacy: the extent to which the age of the exposed information affects sharing preferences. In this article, we investigate how information aging impacts users’ sharing preferences on Facebook. Our findings are based on a between-subjects experiment (n = 272), in which we measured the impact of time since first publishing an OSN post on its sharing preferences. Our results quantify how willingness to share is lower for older Facebook posts and show that older posts have lower relevancy to the user’s social network and are less representative of the user’s identity. We show that changes in the user’s social circles, the occurrence of significant life changes and a user’s young age are correlated with a further decrease in the willingness to keep sharing past information. We discuss our findings by juxtaposing digital memory theories and privacy theories and suggest a vision for mechanisms that can help users manage longitudinal privacy.     

Assessment of subjective influence and trust with an online social network game

The deduction of influence and trust between two individuals only from objective data in online social networks (OSNs) is a rather vague approach. Subjective assessments via surveys produce better results, but are harder to conduct considering the vast amount of friendships of OSN users. This work presents a framework for personalized surveys on relationships in OSNs, which follows a gamification approach. A Facebook game was developed, which was used to subjectively assess social influence and interpersonal trust based on models from psychology. The results show that it is possible to obtain subjective opinions and (limited) objective data about relationships with an OSN game. Also an implicit assessment of influence and trust with subcategory questions is feasible in this case.     

Customized Share Level Monitoring System for Users in OSN-Third Party Applications

Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches costs to the users as well as to the OSN. Despite paying millions of dollars as fine every year, the OSN has not done any significant changes, as data is the fuel and what it loses as fine is far less compared to the money OSN makes out of the shared data. In this work, we have discussed a wide range of possible privacy threats and solutions prevailing in OSN-Third Party Application (TPA) data sharing scenario. Our solution models the behavior of the user, as well as TPA and pinpoints the avenues of over sharing to the users, thereby limiting the privacy loss of the user.     

社交网络研究综述

社交网络已成为Web2.0时代最流行的应用,其服务范围已逐步从社交关系管理扩展到媒体信息、应用集成、电子商务等领域。社交网络中大量的活跃用户为研究网络行为、数据安全、信息传播以及其他跨学科问题提供了宝贵的数据和场景。自Facebook出现以来,研究者先后从不同的角度对社交网络进行了大量的研究,这些研究对人们认识社交网络内部规律、促进ICP服务改进具有重大意义。首先对社交网络的发展进行了简单的回顾;然后从社交网络的数据采集技术、社交网络用户行为分析、社交网络中的信息传播及社交网络中的用户隐私4个方面对已有的研究工作进行总结评价;最后,总结了当前研究中出现的问题并对未来研究发展趋势进行了展望。希望能为该领域的研究者提供一些有益的启示。     

Privacy as information access and illusory control: The case of the Facebook News Feed privacy outcry

Increasingly, millions of people, especially youth, post personal information in online social networks (OSNs). In September 2006, one of the most popular sites—Facebook.com—introduced the features of News Feed and Mini Feed, revealing no more information than before, but resulting in immediate criticism from users. To investigate the privacy controversy, we conducted a survey among 172 current Facebook users in a large US university to explore their usage behaviors and privacy attitudes toward the introduction of the controversial News Feed and Mini Feed features. We examined the degree to which users were upset by the changes, explored the reasons as to why, and examined the influences of the News Feed privacy outcry on user behavior changes. The results have demonstrated how an easier information access and an “illusory” loss of control prompted by the introduction of News Feed features, triggered users’ privacy concerns. In addition to enhancing our theoretical understanding of privacy issues in the online social networks, this research is also potentially useful to privacy advocates, regulatory bodies, service providers, and marketers to help shape or justify their decisions concerning the online social networks.     

Interplay between trust,information privacy concerns and behavioural intention of users on online social networks

Trust and privacy features of websites have evolved as an important concern for any businesses or interactions, particularly in online networks. The study investigates the relationship between trust, privacy concerns and behavioural intention of users on the social network. The behavioural intention of users on the online social network (OSN) is captured by intention to disclose information and intention to interact with others in OSN. The study was conducted on a sample of 457 active users from one of the major social networking website, Facebook. Partial least squares based structural equation modelling was used for analysing the results. The findings of the study reveal that intention to disclose information mediates the relationship between trust in the website and the intention to interact with others. Another important finding of the study indicates that prior positive experience with the website significantly impacts the trust in website, and the trust in website also plays a crucial role while determining the information privacy concerns in the OSN.     

A survey on privacy in decentralized online social networks

Decentralized Online Social Networks (DOSNs) have recently captured the interest of users because of the more control given to them over their shared contents. Indeed, most of the user privacy issues related to the centralized Online Social Network (OSN) services (such as Facebook or Google+) do not apply in the case of DOSNs because of the absence of the centralized service provider. However, these new architectures have motivated researchers to investigate new privacy solutions that allow DOSN’s users to protect their contents by taking into account the decentralized nature of the DOSNs platform.In this survey, we provide a comprehensive overview of the privacy solutions adopted by currently available DOSNs, and we compare them by exploiting several criteria. After presenting the differences that existing DOSNs present in terms of provided services and architecture, we identify, for each of them, the privacy model used to define the privacy policies and the mechanisms for their management (i.e., initialization and modification of the privacy policy). In addition, we evaluate the overhead introduced by the security mechanisms adopted for privacy policy management and enforcement by discussing their advantages and drawbacks.     

DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks

Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. One of the most important challenges is the data availability problem when a user is offline. In this paper we propose DiDuSoNet, a novel P2P Distributed Online Social Network where users can exercise full access control on their data. Our system exploits trust relationships for providing a set of important social services, such as trustness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability.     

Effect of online social networking on student academic performance

Online social networks (OSNs) have permeated all generations of Internet users, becoming a prominent communications tool, particularly in the student community. Thus, academic institutions and faculty are increasingly using social networking sites, such as Facebook and LinkedIn, to connect with current and potential students and to deliver instructional content. This has led to a rise in questions about the impact of OSN on academic performance and the possibility of using it as an effective teaching tool. To learn more about the impact on academic performance, we conducted a survey of business students at a large state university. Survey results were analyzed using structural equation modeling (SEM). The results revealed a statistically significant negative relationship between time spent by students on OSN and their academic performance. The time spent on OSN was found to be heavily influenced by the attention span of the students. Specifically, we determined that the higher the attention span, the lower is the time spent on OSN. Further, attention span was found to be highly correlated with characteristics that predict or influence student behavior, such as their perceptions about society’s view of social networking, their likes and dislikes of OSN, ease of use of OSN, etc.     

OSN Crawling Schedulers and Their Implications on k‐Plexes Detection

Web crawlers are complex applications that explore the Web for different purposes. Web crawlers can be configured to crawl online social networks (OSNs) to obtain relevant data about their global structure. Before a web crawler can be launched to explore the Web, a large amount of settings have to be configured. These settings define the crawler's behavior and they have a big impact on the collected data. Both the amount of collected data and the quality of the information that it contains are affected by the crawler settings and, therefore, by properly configuring these web crawler settings we can target specific goals to achieve with our crawl. In this paper, we review the configuration choices that an attacker who wants to obtain information from an OSN by crawling it has to make to conduct his attack. We analyze different scheduler algorithms for web crawlers and evaluate their performance in terms of how useful they are to pursue a set of different adversary goals.     

Content delivery simulations supported by social network-awareness

In this study we conduct experiments on a modified content delivery simulation framework, as we aspire to compare miscellaneous policies for dynamic OSN-aware content delivery. The incorporation of an OSN-aware dynamic mechanism becomes indispensable for CDN services, since (i)significantly large proportion of Internet traffic results from -easily produced via online media services and transmitted over OSNs- bandwidth-intensive multimedia content and (ii)multimedia content providers, such as YouTube, often rely on ubiquitous Content Distribution Networks (CDNs) infrastructures. Our policies take patterns of user activity over OSNs and exploit geo-social properties of users participating in retransmissions of items over OSNs (social cascades), proceed to incorporate various caching schemes of the underlying infrastructure, different policies for the handling of OSN data and various approaches that take into account the efficient timing of prefetching. The simulation framework we introduce can serve as the basis of further parameterized content delivery experimentation that exploits information transmission over OSNs and decreases replication costs by selectively copying items to locations where items are likely to be consumed.     

HoneyCirculator: distributing credential honeytoken for introspection of web-based attack cycle

A web user who falsely accesses a compromised website is usually redirected to an adversary’s website and is forced to download malware after being exploited. Additionally, the adversary steals the user’s credentials by using information-leaking malware. The adversary may also try to compromise public websites owned by individual users by impersonating the website administrator using the stolen credentials. These compromised websites then become landing sites for drive-by download malware infection. Identifying malicious websites using crawling techniques requires a large amount of resources and time. To monitor the web-based attack cycle for effective detection and prevention, we propose a monitoring system called HoneyCirculator based on a honeytoken, which actively leaks bait credentials and lures adversaries to our decoy server that behaves like a compromised web content management system. To recursively analyze attack phases on the web-based attack cycle, our proposed system involves collecting malware, distributing bait credentials, monitoring fraudulent access, and inspecting compromised web content. It can instantly discover unknown malicious entities without conducting large-scale web crawling because of the direct monitoring behind the compromised web content management system. Our proposed system enables continuous and stable monitoring for about one year. In addition, almost all the malicious websites we discovered had not been previously registered in public blacklists.     

粒子群属性聚类的位置隐私保护

针对基于位置服务中连续查询情况下，用户自身属性信息很容易被攻击者获取，并通过关联获得用户位置隐私的情况，提出了一种利用粒子群聚类加速相似属性用户寻找，并由相似属性匿名实现用户位置泛化的隐私保护方法。该方法利用位置隐私保护中常用的可信中心服务器，通过对发送到中心服务器中的查询信息进行粒子群属性聚类，在聚类的过程中加速相似属性用户的寻找过程，由相似属性用户完成位置泛化，以此实现位置隐私保护。实验结果证明，这种基于粒子群属性聚类的隐私保护方法具有高于同类算法的隐私保护能力，以及更快的计算处理速度。     

Understanding the privacy behavior of adolescents on Facebook: The role of peers,popularity and trust

We study whether peer influence processes, popularity and trust predict privacy settings on Facebook. We use large-scale survey data from 3434 Dutch adolescents combined with observed privacy behavior on Facebook. The findings show that peer influence processes play a role and that adolescents imitate the privacy settings of their peers in the classroom. Such imitation processes are particularly pronounced for highly connected classrooms. The results show that more popular adolescents in the classroom are more likely to publicly display their Facebook profiles. Furthermore, we find that low-trust groups (ethnic minorities, lower educated and younger adolescents, and girls) more frequently opt for private Facebook profiles.     

UbCadet: detection of compromised accounts in twitter based on user behavioural profiling

Multimedia Tools and Applications - Online Social Networks(OSNs) are generally at the risk of many potential dangers. Malicious attackers use compromised OSN accounts to spread fake news, to send...     

Content delivery simulations supported by social network-awareness

In this study we conduct experiments on a modified content delivery simulation framework, as we aspire to compare miscellaneous policies for dynamic OSN-aware content delivery. The incorporation of an OSN-aware dynamic mechanism becomes indispensable for CDN services, since (i)significantly large proportion of Internet traffic results from -easily produced via online media services and transmitted over OSNs- bandwidth-intensive multimedia content and (ii)multimedia content providers, such as YouTube, often rely on ubiquitous Content Distribution Networks (CDNs) infrastructures. Our policies take patterns of user activity over OSNs and exploit geo-social properties of users participating in retransmissions of items over OSNs (social cascades), proceed to incorporate various caching schemes of the underlying infrastructure, different policies for the handling of OSN data and various approaches that take into account the efficient timing of prefetching. The simulation framework we introduce can serve as the basis of further parameterized content delivery experimentation that exploits information transmission over OSNs and decreases replication costs by selectively copying items to locations where items are likely to be consumed.     

The Taste for Privacy: An Analysis of College Student Privacy Settings in an Online Social Network

The rapid growth of contemporary social network sites (SNSs) has coincided with an increasing concern over personal privacy. College students and adolescents routinely provide personal information on profiles that can be viewed by large numbers of unknown people and potentially used in harmful ways. SNSs like Facebook and MySpace allow users to control the privacy level of their profile, thus limiting access to this information. In this paper, we take the preference for privacy itself as our unit of analysis, and analyze the factors that are predictive of a student having a private versus public profile. Drawing upon a new social network dataset based on Facebook, we argue that privacy behavior is an upshot of both social influences and personal incentives. Students are more likely to have a private profile if their friends and roommates have them; women are more likely to have private profiles than are men; and having a private profile is associated with a higher level of online activity. Finally, students who have private versus public profiles are characterized by a unique set of cultural preferences—of which the “taste for privacy” may be only a small but integral part.     

Rationality-based beliefs affecting individual’s attitude and intention to use privacy controls on Facebook: An empirical investigation

Online social networking sites like Facebook provides a fast and easy way to connect with friends and family. Users need to post and share their personal information in order to get the best possible experiences on Facebook. However, the spreading of private information can also lead to serious and harmful issues. Therefore, privacy becomes an important component in the use of Facebook and it is the user’s responsibility to protect his or her profile. This study draws upon the theory of planned behavior and the rational choice theory to investigate the rationality-based beliefs affecting individual’s attitude and intention to use privacy controls on Facebook. The results show that individual’s attitude toward using privacy controls is influenced by benefit of using privacy controls, cost of using privacy controls, and cost of not using privacy controls. Further, benefits of using privacy controls is shaped by beliefs regarding intrinsic benefit and resource safety; cost of not using privacy controls is shaped by beliefs regarding resource vulnerability, threat severity, privacy risk and privacy intrusion; and cost of using privacy controls is shaped by beliefs about intrinsic cost and work impediment. Theoretical and practical implications of the findings are discussed in the paper.     

从脸书用户个人信息泄露事件谈我国社交媒体用户隐私保护

The rapid development of information technology has promoted the popularization of social media applications. Social me- dia has become a platform for users to search for real-time information and communicate and interact. Privacy protection is an im- portant symbol of the progress of human modern civilization. While enjoying the benefits brought by social media, human rights al- so face unprecedented challenges. Therefore, the protection of privacy highlights its importance. This paper analyzes the information leakage of Facebook users in order to discover the various risks faced by the privacy protection of social media users. Then it re- views the user privacy protection measures of major social media platforms at home and abroad. Finally, it is recommended that the government level should speed up the improvement of the social media platform user privacy supervision system, the enterprise lev- el should strengthen the implementation of the social media platform user privacy protection subject responsibility, and the user must improve personal information security literacy and protect personal information and privacy together.