Privacy Protection for Big Data Linking using the Identity Correlation Approach

Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.

反垄断视阈下的数据隐私保护

随着信息时代的到来和数字平台的崛起,隐私保护与反垄断开始产生交集。对于如何处理二者的关系,存在着分离模式与统一模式两种争论。分离模式基于二者在法律目标与实施方式上的差异,主张数据隐私不应当纳入反垄断;统一模式则将数据隐私类比于产品质量或纳入产品质量的分析中,主张反垄断应当考虑数据隐私。由于数据隐私保护提升与市场竞争强化之间可能存在不一致,且反垄断将隐私保护纳入其中也存在分析方法上的困难,统一模式的适用应当慎重;相比之下,分离模式更具可执行性,也更符合数据隐私保护的实践需求,是更为可取的选择。在我国数据隐私保护相关法律制度不断完善的背景下,分离模式也是我国的应然选择。

Computer Assisted Alerts Using Mental Model Approach for Customer Service Improvement

Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs improvement and to review the decisions of security experts in terms of improving warning designs and dialogues, and timely inform the authorities to take quick action at the right time and choice. Human behaviour is deeply involved in most of the security failures and its poor response. If we are able to check and monitor human behaviour in any organisation, we can achieve quality assurance and provide best services to our customers. We have arranged a study in the Center of Post Graduate Studies, International Islamic University, Malaysia (CPS-IIUM), department of Hajj Services-Makkah, and Hospital Management System-Makkah comprised of Observation, Interviews, Questionnaire and discussion based on organizational structure and job activities of people involved in different scenarios and positions under one umbrella of organizational objectives in order to trap the human error in order to take rapid action and response from the management team. Human behaviour is deeply observed and checked while performing different job activities in order to identify the serious errors at the right time during job performance at various levels. We have applied the concept of Brahm’s Language for the simulation of human behaviour which proves an opportunity to simulate human behaviour while performing job activities. Customer service can be improved easily if necessary measures and decisions are taken at the right time and place in any organisation.

An Information-Theoretic Approach to Effective Inference for Z-functionals

In this paper, through an information-theoretic approach, we construct estimations and confidence intervals of Z-functionals involving finite population and with the presence of auxiliary information. In particular, we give a method of estimating the variance of finite population with known mean. The modified estimates and confidence intervals for Z-functionals can adequately use the auxiliary information, at least not worse than what the standard ones do. A simulation study is presented to assess the performance of the modified estimates for the finite sample case.

一种基于GSNPP算法的社交网络隐私保护方法研究

随着网络信息技术的快速发展,社交网络迅速涌现。针对社交网络隐私保护问题,提出了一种基于GSNPP算法的隐私保护方法。它通过对社交网络中节点进行聚类,再对生成的簇进行簇内泛化及簇间泛化,来对社交网络进行匿名化处理,拟达到隐私保护的目的;同时量化了社交网络匿名化处理过程中所带来的不同类型信息的丢失。最后通过实验验证了该方法的可行性和有效性。

网络时代的隐私权——兼论美国和欧盟网络隐私权保护规则及其对我国的启示

随着网络和信息技术的快速发展,网络上的个人隐私权正在被严重地侵害,面对这种侵害,各国都致力于建立完善的网络隐私权法律保护体系。从比较研究的角度讨论美国和欧盟的网络隐私权立法保护模式和规则,并对我国网络隐私权的保护提出立法建议。

移动无线网络的移动终端安全认证方案

针对当前移动云计算的双向认证方案无法解决完全的安全性与隐私性问题,提出一种隐私保护的移动云计算终端认证方案。首先,通过双线性映射与加密hash函数建立智能卡的参数;然后,基于用户的生物学特征与身份ID进行用户注册;最终,在双向认证过程中,基于用户输入的生物学特征、身份ID与密码进行用户认证,基于服务提供者的身份ID进行对服务提供者的认证。实验结果表明:认证方案可抵御主流的恶意攻击,实现了会话秘钥的安全性、用户隐私保护性、双向认证性以及不可追踪性,并降低了终端的通信与计算成本。

FHE~* KDFRS:全同态加密相容的核基人脸识别系统

生物特征识别是一种有着特征唯一、不易复制等良好特性的个人身份鉴定与识别技术.但在识别过程中,个人信息通过公开信道传输或网络服务器存储时,有可能会受到第三方的截获和修改,或通信双方提供虚假信息进行相互欺骗.可通过引入全同态加密协议以保护数据与分类器.此类方案设计主要存在2方面问题:一方面是只支持"加乘"运算的全同态加密算法与识别算法的运算相容性问题;另一方面是由于加密算法的约束导致识别率与运行效率的降低.以C/S模型为基础,采用了Gabor小波和核主成分分析法,利用数据的非线性信息和高阶统计特性以提高识别率;并设计了通信协议,使用了多项式核和改进后的DGHV加密方案,以解决相容性问题.原型实现的实验数据表明,该方案在承接源自全同态加密的隐私保护的前提下,有着较高的识别率与运行效率,其累积匹配率为91.9%,最高识别率为97.62%,最大识别时间花销约为1 s.

隐私保护方法与应用研究综述

综述隐私保护机制中匿名技术、信息论隐私方法、面向位置服务差分隐私和人脸生物特征隐私增强等方面的研究进展。基于已有的研究动态,分析相关隐私保护机制的思路及其在社交网络、移动群智感知、基于位置服务、人脸生物特征等方面的适用性,并介绍了信息论方法在隐私量化、隐私-效用权衡的应用。最后,探讨若干开放问题和挑战。

基于连续近邻服务请求的位置匿名方法的研究

为了使用户在使用基于位置的服务时,用户的位置信息不被泄露,国内外学者提出很多种解决方案,其中一种典型的方法是冗余地址查询方法。然而之前的方法在连续的近邻查询过程中存在处理速度较慢,反应延迟较大的问题。为了提高冗余匿名方法连续近邻查询的查询速度和效率,利用局部性原理,提出了一种改进算法,能够有效提高服务器的处理速度和查询时间,减少响应延迟。实验结果表明,对连续性较强的近邻查询,该方法相对于之前的方法查询性能有较大的提高。

基于感知控制视角的网络隐私忧虑实证研究

研究不同的网络隐私保障手段对网民们网络隐私忧虑的影响,对于互联网行业未来的发展具有相当重要的意义.以技术威胁规避理论中的控制理论为基础,构建网络隐私忧虑影响机制研究模型,并针对模型提出假设.实证结果表明在中国:1)政府立法与网络隐私忧虑没有关系.2)互联网业界行规的自律与网络隐私忧虑没有关系.3)自我保护手段中的技术性自我保护手段虽然与感知避免能力正相关,但感知避免能力与网络隐私忧虑负相关的假设没有得到证实,无法进一步验证两者关系.4)感知威胁与网络隐私忧虑正相关.提出网络隐私忧虑影响机制模型,对未来相关领域研究提供新的研究视角;影响机制中的因素对网络隐私忧虑测量模型中二阶因子的影响,也可为学术界进一步研究相关问题提供有益参考.

非授权信息使用与信息脆弱性、转换行为的关系研究--隐私保护措施的调节作用

基于企业非授权信息使用在手机购物APP情境下对消费者的影响,根据收集的269份消费者问卷,对提出的概念模型与研究假设进行检验。研究结果显示,非授权信息使用会增加消费者感知的信息脆弱性,而信息脆弱性则会促进消费者的转换行为;另外,信息设置有效性和信息政策有效性都可以减弱信息脆弱性与转换行为之间的正向关系。研究不仅促进相关理论研究的发展,同时也为手机购物APP企业如何管理消费者信息与隐私提供策略建议。

A roadmap for security challenges in the Internet of Things

Unquestionably, communicating entities （object, or things） in the Internet of Things （IoT） context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA （Defense Advanced Research Projects Agency） as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the loT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the loT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current stan dardization activities are surveyed and discussed to the ensure the security of loT components and applications.

隐私权的判定——“合理隐私期待标准”的确立与适用

隐私权存在与否的判定问题是隐私侵权责任承担的关键所在。而美国联邦最高法院在1967年Katz v.United States案中确立的"合理的隐私期待"标准,在世界多个国家的适用已被证明是比较可行的隐私权的判定方法。我国隐私权司法实践在吸收、借鉴"合理的隐私期待"标准时应明确"私人事实"、"法律规定"、"社会习俗"和"利益平衡"四种隐私期待的客观判断要素,实现判决结果的一致性,及对他人隐私利益最大程度的保护。

基于信息论方法的多等级位置隐私度量与保护

针对位置数据拥有者对数据使用者具有不同的信任程度时,会对使用者进行不同等级的划分并向其发布不同扰动程度的位置数据这一场景中的隐私泄露问题,提出了基于信息论中的互信息的隐私度量方法与保护问题。此外,基于互信息提出了度量攻击者获取不同等级的扰动数据而对真实位置数据进行更精确的推断分析所造成的隐私泄露的方法。借鉴用于求解率失真函数的Blahut-Arimoto算法提出了多等级位置隐私保护机制。实验结果表明,在上述2种问题场景中,所提位置隐私保护机制与基于差分隐私的位置隐私保护方法相比具有更低的隐私泄露,且当真实位置数据具有显著不同的受欢迎程度时,优势更明显。

大数据时代下个人隐私将面临的新问题及防护对策研究——以大学生群体为切入点

现如今大数据的经济价值被愈来愈多人所发觉。然而大数据下的隐私权保护问题始终难以解决。而大学生群体电子产品的依赖度高但同时安全意识也较差,是大数据时代重要的受益者和受害者。现从此群体入手,通过研究厘清新形势下个人隐私保护问题中各方的权利义务关系,就个人隐私将面临的新形势及防护对策等相关法律问题提出建议。

Cyber Security-Protecting Personal Data

Many organizations have datasets which contain a high volume of personal data on individuals,e.g.,health data.Even without a name or address,persons can be identified based on the details(variables)on the dataset.This is an important issue for big data holders such as public sector organizations(e.g.,Public Health Organizations)and social media companies.This paper looks at how individuals can be identified from big data using a mathematical approach and how to apply this mathematical solution to prevent accidental disclosure of a person’s details.The mathematical concept is known as the“Identity Correlation Approach”(ICA)and demonstrates how an individual can be identified without a name or address using a unique set of characteristics(variables).Secondly,having identified the individual person,it shows how a solution can be put in place to prevent accidental disclosure of the personal details.Thirdly,how to store data such that accidental leaks of the datasets do not lead to the disclosure of the personal details to unauthorized users.

基于MT-TF模型的个人隐私定价问题研究

大数据时代带给人们方便的同时,也因为信息泄露问题,引起了人们对于自身隐私数据信息的重视。本文基于市场时效性和三角模糊数提出运用隐私信息定价模型MT-TF量化个人隐私信息。MT-TF模型从时间成本、财产损失和精神损失三个方面确定隐私信息初始价值,应用信息新度函数确定隐私信息的时效性价值,利用基于均衡理论的市场方法准确量化个人隐私的价值。为获得部分信息价格,该模型利用三角模糊数来获得相应的信息权重。模型实证分析结果显示,某真实个人隐私泄露案件中法院判决为13684元,模型计算为15802元,总体效果较好。该模型能够较好地完成个人隐私信息定价的精准计算,为我国司法、安全及合法隐私交易等领域提供有力的技术支持。

A detailed study on trust management techniques for security and privacy in IoT:challenges,trends,and research directions

The Internet of Things is a modern technology that is directed at easing human life by automating most of the things used in daily life.The never-ending dependency on the network for communication is attracting adversaries to exploit the vulnerabilities of IoT.Therefore,this technology is facing some serious issues and challenges concerning security and privacy.These issues and challenges are the real motivation behind considering this study.Hence,this survey includes a discussion about security and privacy challenges as well as available solutions for IoT based wireless sensor networks.This systematic literature review(SLR)focuses particularly on a popular and applicable security approach known as Trust Management System(TMS).Firstly,all aspects of trust management,including trust indicators,trust properties,trust evaluation,trust building,trust models and the importance of those models for security and privacy,trust prediction methodologies,and ultimately trust-based attacks,are covered in this literature.Secondly,trust management schemes are classified into four groups based on the methodology used for trust-based security solutions in the IoT:cryptography-based,computational and probabilistic-based,information theory-based,and others.Then,an understanding of the problems and difficulties with current methodologies is given,along with suggestions for further research.Finally,the SLR is concluded by formulating the desirable characteristics of a trust management system in the IoT and proposing a trust model suitable for IoT networks.

非洲网络安全治理初探

非洲互联网发展起步晚、普及快,与之相伴随的是网络犯罪日益猖獗、相关法律制度及执法能力滞后、公众和企业网络安全意识相对薄弱的现状。近年来,非洲各行为体开始加快设计网络安全治理方面的制度框架。除了电子交易和网络犯罪外,个人数据保护也是非洲网络安全治理的重要内容,这和西方发达国家的"传授"以及非政府组织的积极倡导有关。非洲网络安全治理的制度设计中,不论是在国家层面、次区域组织层面、非盟层面,还是非政府组织层面,都有西方发达国家和西方主宰的国际组织的身影,部分制度的内容借鉴甚至照搬了西方国家原有的设计。这可能造成非洲大陆在网络空间被再度"殖民化"。而且,根据西方经验设计的制度是否适合非洲国家的文化和观念,还有待于实践的检验。