Achieving dynamic privacy measurement and protection based on reinforcement learning for mobile edge crowdsensing of IoT

With the maturity and development of 5G field,Mobile Edge CrowdSensing(MECS),as an intelligent data collection paradigm,provides a broad prospect for various applications in IoT.However,sensing users as data uploaders lack a balance between data benefits and privacy threats,leading to conservative data uploads and low revenue or excessive uploads and privacy breaches.To solve this problem,a Dynamic Privacy Measurement and Protection(DPMP)framework is proposed based on differential privacy and reinforcement learning.Firstly,a DPM model is designed to quantify the amount of data privacy,and a calculation method for personalized privacy threshold of different users is also designed.Furthermore,a Dynamic Private sensing data Selection(DPS)algorithm is proposed to help sensing users maximize data benefits within their privacy thresholds.Finally,theoretical analysis and ample experiment results show that DPMP framework is effective and efficient to achieve a balance between data benefits and sensing user privacy protection,in particular,the proposed DPMP framework has 63%and 23%higher training efficiency and data benefits,respectively,compared to the Monte Carlo algorithm.

The Protection of Human Rights in the Construction of Barrier-free Environment--Viewed from the perspective of the Marxist Human Rights Concept

The construction of a barrier-free environment contains a rich connotation of human rights protection,and is closely related to the study of human rights protection in China.With the evolution of the concept of barrier-free design and the expansion of its beneficiary groups,constructing a barrier-free environment has become a basic task that benefits all members of society and meets the public needs of all the people,with its core goal expanding from the protection of the rights of the disabled to the protection of the basic rights and interests of all members of society.Building a barrier-free environment from the perspective of the Marxist human rights concept is conducive to safeguarding the people’s right to subsistence and development,and at the same time,it satisfies their demand for the right to pursue a high-quality and better life and reflects the common vision of everyone in society fully enjoying human rights.promoting the construction of a barrier-free environment in terms of legal protection based on China’s institutional advantages can improve and innovate the country’s legislation on the construction of a barrier-free environment,so as to play an exemplary and guiding role in enhancing the international barrier-free level and enable all people to enjoy the good life created through the drive to build a barrier-free environment.

Research on Residents’Willingness to Protect Privacy in the Context of the Personal Information Protection Law:A Survey Based on Foshan Residents’Data

The Personal Information Protection Law,as the first law on personal information protection in China,hits the people’s most concerned,realistic and direct privacy and information security issues,and plays an extremely important role in promoting the development of the digital economy,the legalization of socialism with Chinese characteristics and social public security,and marks a new historical development stage in the protection of personal information in China.However,the awareness of privacy protection and privacy protection behavior of the public in personal information privacy protection is weak.Based on the literature review and in-depth understanding of current legal regulations,this study integrates the relevant literature and theoretical knowledge of the Personal Protection Law to construct a conceptual model of“privacy information protection willingness-privacy information protection behavior”.Taking the residents of Foshan City as an example,this paper conducts a questionnaire survey on their attitudes toward the Personal Protection Law,analyzes the factors influencing their willingness to protect their privacy and their behaviors,and explores the mechanisms of their influencing variables,to provide advice and suggestions for promoting the protection of privacy information and building a security barrier for the high-quality development of public information security.

Changes and Adjustments:The Rule of Law Response to Medical Institution Data Compliance

Medical institution data compliance is an exogenous product of the digital society,serving as a crucial means to maintain and balance the relationship between data protection and data sharing,as well as individual interests and public interests.The implementation of the Healthy China Initiative greatly benefits from its practical significance.In practice,data from medical institutions takes varied forms,including personally identifiable data collected before diagnosis and treatment,clinical medical data generated during diagnosis and treatment,medical data collected in public health management,and potential medical data generated in daily life.In the new journey of comprehensively promoting the Chinese path to modernization,it is necessary to clarify the shift from an individual-oriented to a societal-oriented value system,highlighting the reinforcing role of the trust concept.Guided by the principle of minimizing data utilization,the focus is on the new developments and changes in medical institution data in the postpandemic era.This involves a series of measures such as fulfilling the obligation of notification and consent,specifying the scope of data collection and usage,strengthening the standardized use of relevant technical measures,and establishing a sound legal responsibility system for data compliance.Through these measures,a flexible and efficient medical institution data compliance system can be constructed.

Secure Blockchain-Enabled Internet of Vehicles Scheme with Privacy Protection

The car-hailing platform based on Internet of Vehicles(IoV)tech-nology greatly facilitates passengers’daily car-hailing,enabling drivers to obtain orders more efficiently and obtain more significant benefits.However,to match the driver closest to the passenger,it is often necessary to process the location information of the passenger and driver,which poses a considerable threat to privacy disclosure to the passenger and driver.Targeting these issues,in this paper,by combining blockchain and Paillier homomorphic encryption algorithm,we design a secure blockchain-enabled IoV scheme with privacy protection for online car-hailing.In this scheme,firstly,we propose an encryp-tion scheme based on the lattice.Thus,the location information of passengers and drivers is encrypted in this system.Secondly,by introducing Paillier homomorphic encryption algorithm,the location matching of passengers and drivers is carried out in the ciphertext state to protect their location privacy.At last,blockchain technology is used to record the transactions in online car-hailing,which can provide a security guarantee for passengers and drivers.And we further analyze the security and performance of this scheme.Compared with other schemes,the experimental results show that the proposed scheme can protect the user’s location privacy and have a better performance.

Privacy Protection Algorithm for the Internet of Vehicles Based on Local Differential Privacy and Game Model

In recent years,with the continuous advancement of the intelligent process of the Internet of Vehicles(IoV),the problem of privacy leakage in IoV has become increasingly prominent.The research on the privacy protection of the IoV has become the focus of the society.This paper analyzes the advantages and disadvantages of the existing location privacy protection system structure and algorithms,proposes a privacy protection system structure based on untrusted data collection server,and designs a vehicle location acquisition algorithm based on a local differential privacy and game model.The algorithm first meshes the road network space.Then,the dynamic game model is introduced into the game user location privacy protection model and the attacker location semantic inference model,thereby minimizing the possibility of exposing the regional semantic privacy of the k-location set while maximizing the availability of the service.On this basis,a statistical method is designed,which satisfies the local differential privacy of k-location sets and obtains unbiased estimation of traffic density in different regions.Finally,this paper verifies the algorithm based on the data set of mobile vehicles in Shanghai.The experimental results show that the algorithm can guarantee the user’s location privacy and location semantic privacy while satisfying the service quality requirements,and provide better privacy protection and service for the users of the IoV.

Discussion on the application of the concept of environmental protection and energy saving in the design of building water supply and drainage

With the current,our country social economy rapid development,people's living standard and quality of life and therefore have got improved,at the same time,it is the concept of environmental protection and energy saving is also enhanced value,many fields in our country environmental protection and energysaving concept can be seen in the application,especially the application in building water supply and drainage design more widely,to protect the environment,to maximize the use of limited resources,how to reasonable use of water resources in building water supply and drainage construction,above is current the paper mainly discusses the problems in the construction field,this paper based on environmental protection and energy-saving concept,discusses its application in the building water supply and drainage design,for your reference.

Interpretation of Information Security and Data Privacy Protection According to the Data Use During the Epidemic

COVID-19 has swept the whole our country and the world in the beginning of 2020.31 provinces and municipalities across the country have launched the first-level response to major public health emergencies since January 24,and China has carried out intensive epidemic control.It is critical for effectively responding to COVID-19 to collect,collate and analyze people’s personal data.What’s more,obtaining identity information,travel records and health information of confirmed cases,suspected cases and close contacts has become a crucial step in epidemic investigation.All regions have made full use of big data to carry out personnel screening,travel records analysis and other related work in epidemic prevention and control,effectively improving the efficiency of epidemic prevention and control.However,data leakage,personnel privacy data exposure,and personal attack frequently occurred in the process of personnel travel records analysis and epidemic prevention and control.It even happened in the WeChat group to forward a person’s name,phone number,address,ID number and other sensitive information.It brought discrimination,telephone and SMS harassment to the parties,which caused great harm to individuals.Based on these,lack of information security and data security awareness and other issues were exposed.Therefore,while big data has been widely concerned and applied,attention should be paid to protecting personal privacy.It is urgent to pay more attention to data privacy and information security in order to effectively protect the legitimate rights of the people.Therefore,measures can be taken to achieve this goal,such as improving the relevant legal system,strengthening technical means to enhance the supervision and management of information security and data protection.

On the protection of the right of privacy of patients by the civil law

The development of China＇s medical industry is very fast, which has provided a great help for people, but in the process, there are also a lot of problems violating the privacy of the patients. Based on these circumstances, we must offer the maximum protection of the privacy of the patients. From the point of view of the civil law, the medical institutions or the medical professionals must respect the patients, and protect the patients＇ privacy, so as to build a more harmonious relationship between the doctors and the patients.

Authenticated Digital Currency Redaction with Stronger Privacy and Usability

With the promotion of digital currency,how to effectively solve the authenticity,privacy and usability of digital currency issuance has been a key problem.Redactable signature scheme(RSS)can provide the verification of the integrity and source of the generated sub-documents and solve the privacy problem in digital currency by removing blocks from the signed documents.Unfortunately,it has not realized the consolidation of signed documents,which can not solve the problem of merging two digital currencies.Now,we introduce the concept of weight based on the threshold secret sharing scheme(TSSS)and present a redactable signature scheme with merge algorithm(RSS-MA)using the quasi-commutative accumulator.Our scheme can reduce the communication overhead by utilizing the merge algorithm when transmitting multiple digital currency signatures.Furthermore,this can effectively hide the scale of users’private monetary assets and the number of transactions between users.While meeting the three properties of digital currency issuance,in order to ensure the availability of digital currency after redacting,editors shall not remove the relevant identification information block form digital currency.Finally,our security proof and the analysis of efficiency show that RSS-MA greatly improves the communication and computation efficiency when transmitting multiple signatures.

Redundant Data Detection and Deletion to Meet Privacy Protection Requirements in Blockchain-Based Edge Computing Environment

With the rapid development of information technology,IoT devices play a huge role in physiological health data detection.The exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge nodes.The storage capacity of edge nodes close to users is limited.We should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging problem.Our paper proposes a redundant data detection method that meets the privacy protection requirements.By scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot data.It has the same effect as zero-knowledge proof,and it will not reveal the privacy of users.In addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the data.We use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is deleted.The feasibility of the scheme is proved through safety analysis and efficiency analysis.

A linkable signature scheme supporting batch verification for privacy protection in crowd-sensing

The maturity of 5G technology has enabled crowd-sensing services to collect multimedia data over wireless network,so it has promoted the applications of crowd-sensing services in different fields,but also brings more privacy security challenges,the most commom which is privacy leakage.As a privacy protection technology combining data integrity check and identity anonymity,ring signature is widely used in the field of privacy protection.However,introducing signature technology leads to additional signature verification overhead.In the scenario of crowd-sensing,the existing signature schemes have low efficiency in multi-signature verification.Therefore,it is necessary to design an efficient multi-signature verification scheme while ensuring security.In this paper,a batch-verifiable signature scheme is proposed based on the crowd-sensing background,which supports the sensing platform to verify the uploaded multiple signature data efficiently,so as to overcoming the defects of the traditional signature scheme in multi-signature verification.In our proposal,a method for linking homologous data was presented,which was valuable for incentive mechanism and data analysis.Simulation results showed that the proposed scheme has good performance in terms of security and efficiency in crowd-sensing applications with a large number of users and data.

Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this paper.Here,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its performance.Then,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation platforms.Subsequently,it is used toward secure communication application scenarios.Taking it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)model.Eventually,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.

Review on application progress of federated learning model and security hazard protection

Federated learning is a new type of distributed learning framework that allows multiple participants to share training results without revealing their data privacy.As data privacy becomes more important,it becomes difficult to collect data from multiple data owners to make machine learning predictions due to the lack of data security.Data is forced to be stored independently between companies,creating“data silos”.With the goal of safeguarding data privacy and security,the federated learning framework greatly expands the amount of training data,effectively improving the shortcomings of traditional machine learning and deep learning,and bringing AI algorithms closer to our reality.In the context of the current international data security issues,federated learning is developing rapidly and has gradually moved from the theoretical to the applied level.The paper first introduces the federated learning framework,analyzes its advantages,reviews the results of federated learning applications in industries such as communication and healthcare,then analyzes the pitfalls of federated learning and discusses the security issues that should be considered in applications,and finally looks into the future of federated learning and the application layer.

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.

Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis

The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications.The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control.There is little research on the association of user privacy information,so it is not easy to design personalized privacy protection strategy,but also increase the complexity of user privacy settings.Therefore,this paper concentrates on the association of user privacy information taking big data analysis tools,so as to provide data support for personalized privacy protection strategy design.

Location privacy protection of maritime mobile terminals

Mobile Edge Computing(MEC)can support various high-reliability and low-delay applications in Maritime Networks(MNs).However,security risks in computing task offloading exist.In this study,the location privacy leakage risk of Maritime Mobile Terminals(MMTs)is quantified during task offloading and relevant Location Privacy Protection(LPP)schemes of MMT are considered under two kinds of task offloading scenarios.In single-MMT and single-time offloading scenario,a dynamic cache and spatial cloaking-based LPP(DS-CLP)algorithm is proposed;and under the multi-MMTs and multi-time offloading scenario,a pseudonym and alterable silent period-based LPP(PA-SLP)strategy is proposed.Simulation results show that the DS-CLP can save the response time and communication cost compared with traditional algorithms while protecting the MMT location privacy.Meanwhile,extending the alterable silent period,increasing the number of MMTs in the maritime area or improving the pseudonym update probability can enhance the LPP effect of MMTs in PA-SLP.Furthermore,the study results can be effectively applied to MNs with poor communication environments and relatively insufficient computing resources.

Information Privacy, Data Surveillance and Security——How Australian Privacy Law Fully Plays Its Role in the Age of Big Data

Privacy and the protection of privacy is a common topic studied by many scholars. From the very beginning of human culture, people have personal privacy, which is not willing for them to be unveiled by others. With the development of information technology, especially the internet, knowledge and information are dealt by internet users in conscious or unconscious way, and personal information has been rapidly and quickly distributed and disseminated all over the world. Personal data can be collected by hackers or interlinks from the website, internet not only provides people an era with internet links, but also an age with information collections, a big data age. With the background of big data, this essay tries to put forward the correlative relationship between the protection of information privacy and the privacy law in Australia. It ??rst has an overview of the concepts of information privacy and data surveillance under the background of big data, then highlights the importance of data security in the age of big data;with a literature review on the development of Australian privacy acts, it further claims that privacy acts or regulations by the federal or states provided strong support for the protection of personal data. Then relationship between the protection information privacy and the need of judicial guarantee is further studied for thorough methods or regimes in data protection. With these points studied, this essay aims to highlight the importance of data protection and information privacy. On the other hand, it aims to provide awareness for readers the vital role privacy laws can play in the protection of people’s personal information and emphases the importance of a continuous evolution for privacy law system in the age of big data.

Introduction of Environmental Protection Concept in Textile Major Education

The textile industry is a pillar industry of the national economy,and it is also a polluting industry.Green environmental protection has become the development trend of the textile industry,which requires the joint efforts of the government,enterprises and practitioners.Strengthening the environmental protection education of textile students has important significance for the implementation of sustainable development strategy of textile industry.Tertiary education is a very good platform for the implementation of environmental protection education for textile students,and it is also a critical period for students to strengthen the concept of environmental protection education.Students’environmental protection awareness may take measures to cultivate such as integrating environmental protection courses into major training programs,practice teaching of environmental protection,applying for training programs of college students’innovation and entrepreneurship,participating in research projects,etc.