Ethics is fragile,goodness is not

This paper first illustrates what kind of ethical issues arise from the new information, communication and automation technology. It then argues that we may embrace the popular idea that technology is ethically neutral or even ambivalent without having to close our eyes to those issues and in fact, that the ethical neutrality of technology makes them all the more urgent. Finally, it suggests that the widely ignored fact of normal responsible behaviour offers a new and fruitful starting point for any future thinking about such issues.     

基于隐私保护的序列模式挖掘

隐私保护是当前数据挖掘领域的一个研究热点,其目标是在不暴露原始数据信息的前提下准确地实现挖掘任务。针对隐私保护序列模式挖掘问题,提出了项集的布尔集合关系概念,设计了基于随机集和扰乱函数对原始序列库进行数据干扰的方法模型,并通过扰乱函数的特性还原出原始序列库的频繁序列模式的真实支持度,完成了在保护原始数据隐私的前提下准确地挖掘出频繁序列模式的任务。理论分析和实验结果表明,该方法模型具有很好的数据隐私保护性、挖掘结果准确性和算法执行高效性。     

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。     

Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps

In the midst of the COVID-19 pandemic, contact-tracing apps have emerged as reliable tools for public health communication and the promotion of preventative health. However, to function properly, contact-tracing apps require users to provide sensitive information, which has raised concerns about data disclosure, misuse and social surveillance. Little is known about how different types of risk perception simultaneously hinder and motivate individuals' engagement in mobile health apps, particularly in the context of a pandemic. Based on the privacy calculus theory and the risk-risk tradeoff concept, this study examined the risk-risk tradeoff model to enhance the understanding of COVID-19 contact-tracing app users’ decision from the perspective of risk minimization. Findings from PLS-SEM and fsQCA revealed that users engage in health risk-privacy risk tradeoff when evaluating and deciding to use the apps. The focal study therefore contributes to the research on privacy calculus theory and calls for a balanced managerial solution to mitigate this tradeoff dilemma.     

Security and privacy in 6G networks: New areas and new challenges

With the deployment of more and more 5g networks, the limitations of 5g networks have been found, which undoubtedly promotes the exploratory research of 6G networks as the next generation solutions. These investigations include the fundamental security and privacy problems associated with 6G technologies. Therefore, in order to consolidate and solidify this foundational research as a basis for future investigations, we have prepared a survey on the status quo of 6G security and privacy. The survey begins with a historical review of previous networking technologies and how they have informed the current trends in 6G networking. We then discuss four key aspects of 6G networks – real-time intelligent edge computing, distributed artificial intelligence, intelligent radio, and 3D intercoms – and some promising emerging technologies in each area, along with the relevant security and privacy issues. The survey concludes with a report on the potential use of 6G. Some of the references used in this paper along and further details of several points raised can be found at: security-privacyin5g-6g.github.io.     

On the existence of statistically hiding bit commitment schemes and fail-stop signatures

We show that the existence of a statistically hiding bit commitment scheme with noninteractive opening and public verifiability implies the existence of fail-stop signatures. Therefore such signatures can now be based on any one-way permutation. We also show that genuinely practical fail-stop signatures follow from the existence of any collision-intractable hash function. These are the weakest assumptions known to be sufficient for fail-stop signatures. Conversely, we show that any fail-stop signature scheme with a property we call thealmost unique secret key property can be transformed into a statistically hiding bit commitment scheme. All previously known fail-stop signature schemes have this property. We even obtain an equivalence, because we can modify the construction of fail-stop signatures from bit commitments such that it has this property.     

浅谈办公室电脑隐私保护

本文针对日常办公中存在的隐私保护问题,从简单实用的角度出发,从六个方面介绍了电脑隐私保护的小技巧和常用工具。     

Instagram versus Snapchat: Self-expression and privacy concern on social media

With the increasing popularity of image-based social networking applications (apps), such as Snapchat and Instagram, social media users express multifaceted aspects of their self-concept online, while remaining concerned about privacy issues. This study investigates the determinants behind the choice to use a social networking site (SNS) platform and predicts that the type of self an individual wants to express through the platform and their level of privacy concerns will play an important role in this choice. A total of 547 SNS users completed an online survey. Expression of multiple aspects of the self – true, actual, and ideal self – and online privacy concerns were empirically tested as the key determinants of SNS platform choice. The findings show that the expression of true and actual self are significant determinants for using Snapchat as a primary SNS, whereas the expression of ideal self and greater privacy concerns are associated with active Instagram use. The authors discuss the implications of these findings and recommend future research.     

基于k-匿名的隐私保护计算卸载方法

针对移动边缘计算(MEC)中用户的卸载任务及卸载频率可能使用户被攻击者锁定的问题,该文提出一种基于k-匿名的隐私保护计算卸载方法。首先,该方法基于用户间卸载任务及其卸载频率的差异性,提出隐私约束并建立基于卸载频率的隐私保护计算卸载模型;然后,提出基于模拟退火的隐私保护计算卸载算法(PCOSA)求得最优的k-匿名分组结果和组内各任务的隐私约束频率;最后,在卸载过程中改变用户原始卸载频率满足隐私约束,最小化终端能耗。仿真结果表明,PCOSA算法能找出用户所处MEC节点下与用户卸载表现最相近的k个用户形成匿名集,有效保护了所有用户隐私。