Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

Compensation paradox: the influence of monetary rewards on user behaviour

Many e-commerce companies collect users’ personal data for marketing purposes despite privacy concerns. Information-collecting companies often offer a monetary reward to users to alleviate privacy concerns and ease the collection of personal information. This study focused on the negative effects of monetary rewards on both information privacy concerns (IPC) and information disclosure. A survey approach was used to collect data and 370 final responses were analysed using a two-way analysis of variance and a binomial logistic regression model. The results show that monetary rewards increase IPC when an information-collecting company requires sensitive information. Additional results indicate that building trust is a more effective way of collecting personal data. This study identifies how organisations can best execute information-collection activities and contributes additional insights for academia and practitioners.     

信息社会的理念与发展

首先介绍了信息社会的基本特征，并围绕信息的接入、信息的发布、知识产权、隐私权、信息安全和文化多元性等阐述了信息伦理的内容和概念。最后介绍了信息对人类生活的影响，主要包括交往方式、信息处理方式、学习方式、商业运作方式、医疗方式、产品设计方式、科研方式和政府工作方式等。     

An Evaluation of Public Concerns About Water Management in the Palestinian Territory Pre,During, and Post the National Uprising

We have evaluated the extent of public concerns about water management in the Palestinian Territory (PT) through a survey of the main Palestinian newspaper over the last thirteen years divided in three periods: pre (1984–1987), during (1988–1991), and post national uprising period (1992–1996). The public concern in the PT about various water management aspects was clear and influenced by the prevailing political conditions indicating (1) poor concerns in the first and second period where full Israeli military control of the PT and harsh practices prevailed with relatively more emphasis on regional water issues and (2) extensive-strong concerns in the third period when the peace process started and a partial lift of some of the Israeli water practices took place, along with an increased freedom in expressing public concerns which was granted with more emphasis on local issues and problems. Lack and limitation of water available to Palestinians, alternative solutions, and water quality and pollution control constituted the overwhelming majority of the topics of concern to the public for the three periods studied. Palestinian concerns were always greater than regional ones for the three periods and all of the topics considered. Public concern in the PT about all other water management aspects was poor and negligible especially in the first two periods. A massive increase in public concern has been observed in the third period in which the public expressed their concern over most water management aspects, indicating a possible change in public attitude toward water and water management and reflecting the change of the political status by the start of the peace process and the signing of the peace agreements.     

Aligning principal and agent’s incentives: A principal–agent perspective of social networking sites

The viability of networked communities depends on the creation and disclosure of user-generated content and the frequency of user visitation (Facebook 10-K Annual Report, 2012). However, little is known about how to align the interests of user and social networking sites. In this study, we draw upon the principal-agent perspective to extend Pavlou et al.’s uncertainty mitigation model of online exchange relationships (2007) and propose an empirically tested model for aligning the incentives of the principal (user) and the agent (service provider). As suggested by Pavlou et al., we incorporated a multi-dimensional measure of trust: trust of provider and trust of members. The proposed model is empirically tested with survey data from 305 adults aged 20-55. The results support our model, delineating how real individuals with bounded rationality actually make decision about information disclosure under uncertainty in the social networking site context. There is show little to no relationship between online privacy concerns and information disclosure on online social network sites. Perceived benefits provide the linkage between the incentives of principal (user) and agent (provider) while usage intensity demonstrated the most significant impact on information disclosure. We argue that the phenomenon may be explained through Communication Privacy Management Theory. The present study enhances our understanding of agency theory and human judgment theory in the context of social media. Practical implications for understanding and facilitating online social exchange relationships are also discussed.     

RFID系统隐私安全问题研究综述

随着物联网事业的飞速发展,RFID技术做为物联网最底层的感知技术也得到飞速的发展。但是由于RFID系统开放式的应用环境以及设备的特殊性和局限性,使得RFID系统面临许多隐私安全问题。对RFID系统进行概述,并且对现有的RFID安全协议和安全模型进行综述和评价,并给出RFID系统隐私保护今后的研究方向。     

供应链环境下安全的RFID认证方案

供应链环境下RFID安全认证方案不仅要保证各节点的隐私安全,还应该满足供应链管理需求。针对现有方案存在不能同时兼顾两者的不足,提出一种基于"双重签名"的认证方案。标签的认证信息先后采用访问密钥和认证密钥进行双重签名生成,只有同时具备这两个密钥才能识别标签身份。该方案既可以实现标签在供应链内的安全传递,又能方便供应链的管理。分析表明,该方案较现有方案优势明显。     

面向云存储的高性能数据隐私保护方法

随着云计算和云存储技术的飞速发展,越来越多的企业和个人使用云存储来保存数据或备份数据。但用户将私有数据上传到云端的同时,也丧失了对数据的绝对控制权,用户数据的隐私保护问题成为云存储发展不得不解决的问题。为了解决这一问题,提出一种新的针对云存储的数据隐私保护方法 BSBC(Bit Split Bit Combine),它在上传前,将数据按照比特位进行拆分,重新组装后形成多个数据文件,再分别上传到云存储服务器;下载时,先将所有数据文件下载,然后通过位合并再恢复成原始文件。实验证明这种方法可以保护用户数据的隐私,同时可比传统加解密获得17~35倍的性能提升。然后将核心的位拆分、位合并代码模块用汇编语言进行优化,对汇编语言进行指令调度优化,以减少数据冲突和流水线停顿。最终,采用BSBC方法比传统加解密可以获得25~35倍的性能提升。     

支持本地化差分隐私保护的k-modes聚类方法

如何在保护数据隐私的同时进行可用性的数据挖掘已成为热点问题。鉴于在很多实际应用场景中,很难找到一个真正可信的第三方对用户的敏感数据进行处理,文中首次提出了一种支持本地化差分隐私技术的聚类方案——LDPK-modes(Local Differential Privacy K-modes)。与传统的基于中心化差分隐私的聚类算法相比,其不再需要一个可信的第三方对数据进行收集和处理,而由用户担任数据隐私化的工作,极大地降低了第三方窃取用户隐私的可能性。用户使用满足本地d-隐私(带有距离度量的本地差分隐私技术)定义的随机响应机制对敏感数据进行扰动,第三方收集到用户扰动数据后,恢复其统计特征,生成合成数据集,并进行k-modes聚类。在聚类过程中,将数据集上频繁出现的特征分配给初始聚类中心点,进一步提高了聚类结果的可用性。理论分析和实验结果表明了LDPK-modes的隐私性和聚类可用性。     

Virt-RSBAC:一种防御云计算内部威胁的框架

针对来自云计算平台的内部威胁,为了保护云用户的隐私,缓减平台提供者的安全监控需求与用户隐私之间的策略冲突,本文提出一种虚拟化环境下的特权控制框架Virt-RSBAC。通过在虚拟机监视器（VMM）中添加特权控制和基于角色的资源隔离规则,实现对特权域管理权限的分离,简化对云用户的管理,借助于创建相互信任的安全虚拟机（SVM）为云平台提供者和云用户提供安全服务。最后,在Xen上实现了该框架的原型,实验与分析表明该框架能够防止恶意管理员获取用户隐私并提供检测功能,对原有系统的性能损耗在可接受范围内。