How the Information and Communications Technology Threaten Our Privacy： The Case of Email and P2P Propagation Models

With the rapid growth of information and communication technology （ICT）, the violation of information privacy has increased in recent years. The privacy concerns now re-emerge right because people perceives a threat from new ICT that are equipped with enhanced capabilities for surveillance, storage, retrieval, and diffusion of personal information. With the trend in the prevalence and the easy use of ICT, it is of necessary to pay much attention to the issue how the ICT can threaten the privacy of individuals on the Internet. While the Email and P2P （Peer-to-Peer） tools are the most popular ICT, this paper aims at understanding their respectively dissemination patterns in spreading of personal private information. To this purpose, this paper using dynamic model technique to simulate the pattern of sensitive or personal private information propagating situation. In this study, an Email propagation model and a Susceptible-lnfected-Removed （SIR） model are proposed to simulate the propagation patterns of Email and P2P network respectively. Knowing their dissemination patterns would be helpful for system designers, ICT manager, corporate IT personnel, educators, policy makers, and legislators to incorporate consciousness of social and ethical information issues into the protection of information privacy.

Preliminary Analysis of the Protection of Privacy in the Information Network Age

The development and appli- cation of modern computer information and network technology is a double- edged sword. On the one hand, thanks to the rapid and convenient spread and exchange of computer- ized information and the compressed time and space on the Internet, computerized information plays a positive role in many areas like the economy, culture, education, sci- ence and technology, and politics. On the other hand, it also leads to various online rights infringements： citizens＇ individual information is revealed online; personal comput- ers are hacked; and online shopping lists are copied. Many Internet users worry about these problems to some extent. Especially in recent years, as information technology has devel- oped rapidly, people＇s online privacy rights have faced unprecedented challenges. How to strengthen pro- tection of online individual privacy has become an important challenge to the healthy development of informa- tion networks.

OTT Messages Modeling and Classification Based on Recurrent Neural Networks

A vast amount of information has been produced in recent years,which brings a huge challenge to information management.The better usage of big data is of important theoretical and practical significance for effectively addressing and managing messages.In this paper,we propose a nine-rectangle-grid information model according to the information value and privacy,and then present information use policies based on the rough set theory.Recurrent neural networks were employed to classify OTT messages.The content of user interest is effectively incorporated into the classification process during the annotation of OTT messages,ending with a reliable trained classification model.Experimental results showed that the proposed method yielded an accurate classification performance and hence can be used for effective distribution and control of OTT messages.

Challenges and Solutions of Information Security Issues in the Age of Big Data

Big data has been taken as a Chinese national strategy in order to satisfy the developments of the social and economic requirements and the development of new information technology. The prosperity of big data brings not only convenience to people's daily life and more opportunities to enterprises, but more challenges with information security as well. This paper has a research on new types and features of information security issues in the age of big data, and puts forward the solutions for the above issues: build up the big data security management platform, set up the establishment of information security system and implement relevant laws and regulations.

Blockchain and Artificial Intelligence Applications to Defeat COVID-19 Pandemic

The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020,provide critical research criteria to assess the vulnerabilities of our current health system.The paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness,about public health and healthcare mechanisms.In view of this unprecedented health crisis,distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages,and with the higher efficacy.At the implementation level,blockchain integration,early detection and avoidance of an outbreak,identity protection and safety,and a secure drug supply chain can be realized.At the opposite end of the continuum,artificial intelligence methods are used to detect corona effects until they become too serious,avoiding costly drug processing.The paper explores the application of blockchain and artificial intelligence in order to fight with COVID-19 epidemic scenarios.This paper analyzes all possible newly emerging cases that are employing these two technologies for combating a pandemic like COVID-19 along with major challenges which cover all technological and motivational factors.This paper has also discusses the potential challenges and whether further production is required to establish a health monitoring system.

Preserving privacy information flow security in composite service evolution

After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. We propose an approach to preserve privacy information flow security in composite service evolution. First, a privacy data item dependency analysis method based on a Petri net model is presented. Then the set of privacy data items collected by each component service is derived through a privacy data item dependency graph, and the security scope of each component service is calculated. Finally, the evolution operations that preserve privacy information flow security are defined. By applying these evolution operations, the re-verification process is avoided and the evolution efficiency is improved. To illustrate the effectiveness of our approach, a case study is presented. The experimental results indicate that our approach has high evolution efficiency and can greatly reduce the cost of evolution compared with re-verifying the entire composite service.

Information Privacy Protection in the New Chinese Civil Code:Priority or Replacement?

The right to privacy has been developed through judicial practice and has evolved from"the protection of the right to reputation" to"privacy interest"then to"privacy right." The Civil Code of the People's Republic of China(2020)clarifies the right to information privacy and the right to personal information as two independent personality rights and establishes a privacy priority protection mechanism for private information in civil law.The comparative efficiency of the right to personal information may mean that the protection of the right to information privacy is weakened or even replaced by the right to personal information.The uncertainty and fragmentation of private information also creates a wide gray space for judicial decisions.The development from traditional privacy right to information privacy right and personal information right is generally positive and shows the active legal response to the protection of private information in multiple ways.However,clarifications and systematization are required to increase the effectiveness of such protections.

Data Secure Transmission Model Based on Compressed Sensing and Digital Watermarking Technology

Since the Internet of Things（IoT） secret information is easy to leak in data transfer,a data secure transmission model based on compressed sensing（CS） and digital watermarking technology is proposed here. Firstly, for node coding end, the digital watermarking technology is used to embed secret information in the conventional data carrier. Secondly, these data are reused to build the target transfer data by the CS algorithm which are called observed signals. Thirdly, these signals are transmitted to the base station through the wireless channel. After obtaining these observed signals, the decoder reconstructs the data carrier containing privacy information. Finally, the privacy information is obtained by digital watermark extraction algorithm to achieve the secret transmission of signals. By adopting the watermarking and compression sensing to hide secret information in the end of node code, the algorithm complexity and energy consumption are reduced. Meanwhile, the security of secret information is increased.The simulation results show that the method is able to accurately reconstruct the original signal and the energy consumption of the sensor node is also reduced significantly in consideration of the packet loss.