Saving face on Facebook: privacy concerns,social benefits,and impression management

The nearly ubiquitous use of online social networks generally entails substantial personal disclosure and elicits significant privacy concerns. This research uses Social Exchange Theory and the impression management (IM) literature to examine how privacy concerns can be counterbalanced by the perceived social benefits afforded by a social network’s ability to support IM. We frame social network use as an attempt to engage in IM, and we highlight the importance of a social network’s IM affordances in predicting social benefits from, and disclosure through, a social network. We test our model with a sample of 244 Facebook users, finding support for the proposed relationships and yielding the following contributions. First, this research provides a novel positioning of perceived IM affordances as a primary driver of both perceived social benefits and IM disclosure propensity. Second, this research illuminates that trust in both the social network provider and social network peers influences privacy concerns, social benefits, and perceived IM affordances. Our theory has important implications for researchers and practitioners interested in privacy issues within social networks.     

Privacy,trust and control: Which relationships with online self-disclosure?

A number of studies have examined the relationship between privacy concerns, perceived control over information, trust and online self-disclosure, highlighting different points of view to understand this connection. This paper intends to compare these different models of explanation for self-disclosure behaviors in online social networks. Three different hypotheses are verified, using mediation and moderation analyses. The results allow underling the effect of the interaction between privacy concerns and trust on online self-disclosure, along with the absence of a direct influence of privacy concerns on disclosure itself. The results suggest practical implications for online social network providers, most of all with regard to privacy policies in online environments.     

Anonymizing popularity in online social networks with full utility

With the rapid growth of social network applications, more and more people are participating in social networks. Privacy protection in online social networks becomes an important issue. The illegal disclosure or improper use of users’ private information will lead to unaccepted or unexpected consequences in people’s lives. In this paper, we concern on authentic popularity disclosure in online social networks. To protect users’ privacy, the social networks need to be anonymized. However, existing anonymization algorithms on social networks may lead to nontrivial utility loss. The reason is that the anonymization process has changed the social network’s structure. The social network’s utility, such as retrieving data files, reading data files, and sharing data files among different users, has decreased. Therefore, it is a challenge to develop an effective anonymization algorithm to protect the privacy of user’s authentic popularity in online social networks without decreasing their utility. In this paper, we first design a hierarchical authorization and capability delegation (HACD) model. Based on this model, we propose a novel utility-based popularity anonymization (UPA) scheme, which integrates proxy re-encryption with keyword search techniques, to tackle this issue. We demonstrate that the proposed scheme can not only protect the users’ authentic popularity privacy, but also keep the full utility of the social network. Extensive experiments on large real-world online social networks confirm the efficacy and efficiency of our scheme.     

基于随机模型检验的社交网络隐私保护研究

针对现有社交网络所提供静态隐私策略的隐私设置不够灵活且难以定量验证问题,提出一种动态隐私保护框架,将社交网络建模为离散时间马尔科夫链模型,通过设置触发条件实现用户动态隐私规约并将其转化为概率计算树逻辑公式,同时结合随机模型检验和运行时验证中的参数化与监控技术,保护社交网络发生随机故障情况下的用户动态隐私信息。在Diaspora开源社交网络上的实验结果表明,与静态隐私保护框架相比,动态隐私保护框架具有更高的安全性和灵活性,能较好满足用户的隐私保护需求。     

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.     

LotusNet: Tunable privacy for distributed online social network services

The evolution of the role of online social networks in the Web has led to a collision between private, public and commercial spheres that have been inevitably connected together in social networking services since their beginning. The growing awareness on the opaque data management operated by many providers reveals that a privacy-aware service that protects user information from privacy leaks would be very attractive for a consistent portion of users. In order to meet this need we propose LotusNet, a framework for the development of social network services relying on a peer-to-peer paradigm which supports strong user authentication. We tackle the trade-off problem between security, privacy and services in distributed social networks by providing the users the possibility to tune their privacy settings through a very flexible and fine-grained access control system. Moreover, our architecture is provided with a powerful suite of high-level services that greatly facilitates custom application development and mash up.     

WSN源位置隐私技术研究

随着无线传感器网络的应用深入到日常生活领域,隐私已成为无线传感器网络成功应用的一大障碍。当无线传感器网络用于监控敏感对象,被监控对象的位置隐私成为一个重要问题。首先分析无线传感器网络的安全特点、信源位置隐私性能评价标准、面临的隐私威胁,最后,基于对无线传感器网络信源位置隐私问题的分析和评述,指出了今后该领域的研究方向。     

线上社交网络访问控制模型综述

就线上社交网络访问控制模型的研究现状进行了分析、总结,指出当前研究中存在的关键问题和面临的挑战,并对此类模型的发展趋势和未来研究方向做出预测. 线上社交网络方兴未艾,数据共享、隐私保护等问题日渐引起公众注意. 作为信息安全手段,传统访问控制模型已不适应线上社交网络复杂环境下的安全需求. 近年来针对线上社交网络访问控制模型的研究正成为热点问题,多个研究小组均从不同角度提出了新的访问控制模型.     

社交网络中用户隐私推理与保护研究综述

如今微博和Twitter等社交网络平台被广泛地用于交流、创建在线社区并进行社交活动。用户所发布的内容可以被推理出大量隐私信息,这导致社交网络中针对用户的隐私推理技术的兴起。利用用户的文本内容及在线行为等知识可以对用户进行推理攻击,社交关系推理和属性推理是对社交网络用户隐私的两种基本攻击。针对推理攻击保护机制和方法的研究也在日益增加,对隐私推理和保护技术相关的研究和文献进行了分类并总结,最后进行了探讨和展望。     

Guest Editors' Introduction: Security & Privacy

Security and privacy concerns touch on all aspects of pervasive computing, including hardware, operating systems, networks, databases, user interfaces, and applications. The seven articles selected for this special issue draw on ideas from many of these fields and provide a flavor of the kinds of security and privacy challenges and opportunities in pervasive computing. This article is part of a special issue on security and privacy.     

无线传感器网络中的隐私保护研究

随着无线传感器网络的广泛应用,安全问题发生变化,通信安全成为重要的一部分,隐私保护日渐重要。首先分析了无线传感器网络的通信安全特点、通信安全的需求、面临的保密性威胁及攻击模型。最后,基于对无线传感器网络隐私保护问题的分析和评述,指出了今后该领域的研究方向。     

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.     

Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards

Technological innovations are increasingly helping people expand their social capital through online networks by offering new opportunities for sharing personal information. Online social networks are perceived to provide individuals new benefits and have led to a surge of personal data uploaded, stored, and shared. While privacy concerns are a major issue for many users of social networking sites, studies have shown that their information disclosing behavior does not align with their concerns. This gap between behavior and concern is called the privacy paradox. Several theories have been explored to explain this, but with inconsistent and incomplete results. This study investigates the paradox using a construal level theory lens. We show how a privacy breach, not yet experienced and psychologically distant, has less weight in everyday choices than more concrete and psychologically-near social networking activities and discuss the implications for research and practice.     

社交网络用户浏览轨迹信息隐私保护方法仿真

随着网络应用的广泛普及,QQ、微信、YY语音、陌陌等社交软件走进千家万户,但社交网络用户浏览轨迹信息隐私保护问题也随之而来。由于社交网络平台安全机制存在漏洞,抵御网络攻击性能不强,使社交网络用户信息纷纷泄露。针对问题根源,提出ACP用户隐私信息防护系统,建立社交网络用户真空登陆模块(VM)、通讯信息密码文模块(RDT)及信息储存保护墙模块(LDM)一体化ACP用户隐私信息防护系统,从根源保护社交网络用户浏览轨迹信息的隐私安全。通过数据模拟仿真实验证明提出的ACP用户隐私信息防护系统,对社交网络用户浏览轨迹信息隐私保护具有可用性与有效性。     

WSNs中的位置隐私评述

随着无线传感器网络（WSNs）的广泛应用,隐私已成为WSNs成功应用的一大障碍。当WSNs用于监控敏感对象,被监控对象的位置隐私成为一个重要问题。特别是WSNs在军事上的应用,基站一旦被控制或破坏,后果不堪设想。分析了WSNs的安全特点、位置隐私性能评价、面临的隐私威胁,并基于对WSNs位置隐私问题的分析和评述,指出了今后该领域的研究方向。     

A Usable Security Heuristic Evaluation for the Online Health Social Networking Paradigm

The security, privacy, and usability of health social networking websites remain key concerns for their successful adoption by patients. As far as it is known, no studies have developed a usable security heuristic evaluation to test these websites for the usability of their security and privacy features. This article describes the development of such a usable security heuristic evaluation in the context of the online health social networking paradigm. The tailored method approach was applied to transform themes identified from relevant literature and convert them into high-level heuristics for usable security. Checklist items were created for each high-level heuristic. The result is 13 high-level heuristics with individualized checklist items that help examine usable security. The results can identify which security and privacy features are lacking from a usability perspective and would, therefore, require design improvement. The improvements would enhance the users' experiences, which in turn can assist in the adoption of health social networking websites.     

一种基于随机投影的加权社会网络隐私保护方法

针对加权社会网络的发布,提出了一种基于随机投影的隐私保护方法——向量集随机投影,该方法通过对加权社会网络的结构和边权重进行干扰实现敏感信息的隐私保护。通过对加权社会网络进行分割,得到节点数相同的若干个子网络;依据边空间理论,采用由边信息构建的向量描述子网络,构建加权社会网络的向量集作为发布模型;利用随机投影技术对原始向量集进行降维操作得到目标向量集;依据目标向量集构建加权社会网络的发布集。实验结果表明,向量集随机投影方法能够在确保隐私信息安全的同时仍然保护社会网络分析所需要的某些结构特征。     

Factors affecting privacy disclosure on social network sites: an integrated model

The self-disclosure of personal information by users on social network sites (SNSs) play a vital role in the self-sustainability of online social networking service provider platforms. However, people’s levels of privacy concern increases as a direct result of unauthorized procurement and exploitation of personal information from the use of social networks which in turn discourages users from disclosing their information or encourages users to submit fake information online. After a review of the Theory of Planned Behavior (TPB) and the privacy calculus model, an integrated model is proposed to explain privacy disclosure behaviors on social network sites. Thus, the aim of this paper is to find the key factors affecting users’ self-disclosure of personal information. Using privacy calculus, the perceived benefit was combined into the Theory of Planned Behavior, and after some modifications, an integrated model was prescribed specifically for the context of social network sites. The constructs of information sensitivity and perceived benefit were redefined after reviewing the literature. Through a study on the constructs of privacy concern and self-disclosure, this article aims at reducing the levels of privacy concern, while sustaining online transactions and further stimulating the development of social network sites.     

社交网络中的社团隐私研究综述

社团是社交网络的重要特征,社团检测技术的发展给网络用户带来隐私泄露的危险。如何保护敏感的社团信息不被泄露,保障用户与社团安全已经成为网络安全领域的研究热点。近几年,社团保护技术取得了初步进展,但针对社交网络中的社团隐私或社团安全研究进展综述较少,不利于该研究方向的长远发展。因此,主要针对社团结构隐私方面的研究进展进行综述,对最新的相关研究成果进行系统地归纳、总结、比较,并展望了未来的研究方向。     

The ‘Privacy Paradox’ in the Social Web: The Impact of Privacy Concerns,Individual Characteristics,and the Perceived Social Relevance on Different Forms of Self‐Disclosure

Given the diffusion of the Social Web and increased disclosure of personal information online, the ‘privacy paradox’ suggests that while Internet users are concerned about privacy, their behaviors do not mirror those concerns. This study investigates the potential influence of privacy concerns, psychological traits, attitudes to the Social Web and age on self‐disclosure. Using an online survey of a representative sample of German Internet users (n = 2, 739), the variety and quality of self‐disclosure as well as access were measured. The findings indicate that privacy concerns hardly impact self‐disclosure, but different variables moderate this relation. Perceived social relevance and the number of applications used proved important. Users' general willingness to disclose is most important when providing sensitive information.