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 intelligent and privacy-enhanced data sharing strategy for blockchain-empowered Internet of Things

With the development of the Internet of Things (IoT), the massive data sharing between IoT devices improves the Quality of Service (QoS) and user experience in various IoT applications. However, data sharing may cause serious privacy leakages to data providers. To address this problem, in this study, data sharing is realized through model sharing, based on which a secure data sharing mechanism, called BP2P-FL, is proposed using peer-to-peer federated learning with the privacy protection of data providers. In addition, by introducing the blockchain to the data sharing, every training process is recorded to ensure that data providers offer high-quality data. For further privacy protection, the differential privacy technology is used to disturb the global data sharing model. The experimental results show that BP2P-FL has high accuracy and feasibility in the data sharing of various IoT applications.     

CPFinder: Finding an unknown caller's profession from anonymized mobile phone data

Identifying an unfamiliar caller's profession is important to protect citizens' personal safety and property. Owing to the limited data protection of various popular online services in some countries, such as taxi hailing and ordering takeouts, many users presently encounter an increasing number of phone calls from strangers. The situation may be aggravated when criminals pretend to be such service delivery staff, threatening the user individuals as well as the society. In addition, numerous people experience excessive digital marketing and fraudulent phone calls because of personal information leakage. However, previous works on malicious call detection only focused on binary classification, which does not work for the identification of multiple professions. We observed that web service requests issued from users' mobile phones might exhibit their application preferences, spatial and temporal patterns, and other profession-related information. This offers researchers and engineers a hint to identify unfamiliar callers. In fact, some previous works already leveraged raw data from mobile phones (which includes sensitive information) for personality studies. However, accessing users' mobile phone raw data may violate the more and more strict private data protection policies and regulations (e.g., General Data Protection Regulation). We observe that appropriate statistical methods can offer an effective means to eliminate private information and preserve personal characteristics, thus enabling the identification of the types of mobile phone callers without privacy concerns. In this paper, we develop CPFinder —- a system that exploits privacy-preserving mobile data to automatically identify callers who are divided into four categories of users: taxi drivers, delivery and takeouts staffs, telemarketers and fraudsters, and normal users (other professions). Our evaluation of an anonymized dataset of 1,282 users over a period of 3 months in Shanghai City shows that the CPFinder can achieve accuracies of more than 75.0% and 92.4% for multiclass and binary classifications, respectively.     

A suite of algorithms for key distribution and authentication in centralized secure multicast environments

The Extended Euclidean algorithm provides a fast solution to the problem of finding the greatest common divisor of two numbers. In this paper, we present three applications of the algorithm to the security and privacy field. The first one allows one to privately distribute a secret to a set of recipients with only one multicast communication. It can be used for rekeying purposes in a Secure Multicast scenario. The second one is an authentication mechanism to be used in environments in which a public-key infrastructure is not available. Finally, the third application of the Extended Euclidean algorithm is a zero-knowledge proof that reduces the number of messages between the two parts involved, with the aid of a central server.     

Validating the moderating role of age in multi-perspective acceptance model of wearable healthcare technology

The recent trend of aging population, not to mention the unprecedented pandemic, draws great attention from the general public about health concerns. Since healthcare information technology is different from non-healthcare information technology, additional contexts should be properly incorporated into technology acceptance research to accurately identify influential factors affecting the acceptance of wearable healthcare technology. Thus, we selectively reconfigured factors from health, privacy, and socio-demographic contexts to formulate a health-aware acceptance model. Then, it was empirically analyzed using structural equation modeling. Based on the results, whereas privacy concerns were directly associated with intention to use wearable healthcare technology, health concerns were not. Moreover, age had a moderating effect on social influence and facilitating conditions. These findings suggest valuable insights that the adoption rate of healthcare technology is increased by 1) keeping personal information securely, 2) facilitating social interaction among users, and 3) offering intuitive user experience for elderly people.     

Face Threat and Facework Strategies When Family (Health) Secrets Are Revealed: A Comparison of South Korea and the United States

This study examined face threat and facework strategies when people witness family members disclosing sensitive health information to family outsiders. Korean and U.S. participants were expected to view these situations differently based on Confucian versus individualist identity and in‐group privacy norms. Korean and U.S. college samples evaluated vignettes in which health information was disclosed to family outsiders. Koreans regarded the situations as more face threatening and endorsed dominating facework in these situations to a greater extent than did Americans. The 2 cultures also showed strong similarities. Results confirmed the cultural basis of privacy expectations but contradicted some accounts of culturally based facework. Koreans did not consistently endorse indirect facework, nor did Americans show notable directness in response to privacy violations.     

User location privacy protection mechanism for location-based services

With the rapid development of the Internet of Things (IoT), Location-Based Services (LBS) are becoming more and more popular. However, for the users being served, how to protect their location privacy has become a growing concern. This has led to great difficulty in establishing trust between the users and the service providers, hindering the development of LBS for more comprehensive functions. In this paper, we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem. This mechanism not only guarantees the confidentiality of the user’s information during the subsequent information interaction and dynamic data transmission, but also meets the service provider’s requirements for related data.     

Oblivious Transfers and Privacy Amplification

Oblivious transfer (OT) is an important primitive in cryptography. In chosen one-out-of-two string OT, a sender offers two strings, one of which the other party, called the receiver, can choose to read, not learning any information about the other string. The sender on the other hand does not obtain any information about the receivers choice. We consider the problem of reducing this primitive to OT for single bits. Previous attempts to doing this were based on self-intersecting codes. We present a new technique for the same task, based on so-called privacy amplification. It is shown that our method has two important advantages over the previous approaches. First, it is more efficient in terms of the number of required realizations of bit OT, and second, the technique even allows for reducing string OT to (apparently) much weaker primitives. An example of such a primitive is universal OT, where the receiver can adaptively choose what type of information he wants to obtain about the two bits sent by the sender subject to the only constraint that some, possibly very small, uncertainty must remain about the pair of bits.     

Assessing mobile phone communication utility preferences in a social support network

While it is generally accepted that the mobile cell phone has become ubiquitous within society for communicating, the actual use of the utilities on a phone have not been reported. Understanding how communication patterns are changing in society as a result of the mobile cell phone will enable the development and/or modification of existing cell phone utilities, the concept of privacy, and a mobile literacy research domain. To explore mobile cell phone utility use, 99 people completed a mobile phone usage questionnaire. Key results from the questionnaire are physical location when using a mobile cell phone, the length of communication episodes, the usage of phone utilities and existing privacy concerns related to mobile cell phones.     

Quantum protocol for millionaire problem

We present a quantum protocol for the solution of a two-party comparison task with the help of a semi-honest third party, which can be used to solve the millionaire problem. The secrets are coded into the phases of d-level entangled states by local operations and read by the third party's collective measurements. The two parties can deduce the results of comparisons based on the secret bits shared between them beforehand and the announcement of the third party. Moreover, others will learn no information of the comparison results, even the third party. Our scheme is private and fair, and the security has also been discussed.