Multi-Source Data Privacy Protection Method Based on Homomorphic Encryption and Blockchain

Multi-Source data plays an important role in the evolution of media convergence.Its fusion processing enables the further mining of data and utilization of data value and broadens the path for the sharing and dissemination of media data.However,it also faces serious problems in terms of protecting user and data privacy.Many privacy protectionmethods have been proposed to solve the problemof privacy leakage during the process of data sharing,but they suffer fromtwo flaws:1)the lack of algorithmic frameworks for specific scenarios such as dynamic datasets in the media domain;2)the inability to solve the problem of the high computational complexity of ciphertext in multi-source data privacy protection,resulting in long encryption and decryption times.In this paper,we propose a multi-source data privacy protection method based on homomorphic encryption and blockchain technology,which solves the privacy protection problem ofmulti-source heterogeneous data in the dissemination ofmedia and reduces ciphertext processing time.We deployed the proposedmethod on theHyperledger platformfor testing and compared it with the privacy protection schemes based on k-anonymity and differential privacy.The experimental results showthat the key generation,encryption,and decryption times of the proposedmethod are lower than those in data privacy protection methods based on k-anonymity technology and differential privacy technology.This significantly reduces the processing time ofmulti-source data,which gives it potential for use in many applications.

Residential Energy Consumption Forecasting Based on Federated Reinforcement Learning with Data Privacy Protection

Most studies have conducted experiments on predicting energy consumption by integrating data formodel training.However, the process of centralizing data can cause problems of data leakage.Meanwhile,many laws and regulationson data security and privacy have been enacted, making it difficult to centralize data, which can lead to a datasilo problem. Thus, to train the model while maintaining user privacy, we adopt a federated learning framework.However, in all classical federated learning frameworks secure aggregation, the Federated Averaging (FedAvg)method is used to directly weight the model parameters on average, which may have an adverse effect on te model.Therefore, we propose the Federated Reinforcement Learning (FedRL) model, which consists of multiple userscollaboratively training the model. Each household trains a local model on local data. These local data neverleave the local area, and only the encrypted parameters are uploaded to the central server to participate in thesecure aggregation of the global model. We improve FedAvg by incorporating a Q-learning algorithm to assignweights to each locally uploaded local model. And the model has improved predictive performance. We validatethe performance of the FedRL model by testing it on a real-world dataset and compare the experimental results withother models. The performance of our proposed method in most of the evaluation metrics is improved comparedto both the centralized and distributed models.

To Whom Do Data Belong?——Data Ownership and Protection in the Context of Web-Crawlers

Platform data has already become an important asset for web-based companies,but this sort of data frequently includes large amounts of personal information.Platform data can be seen as belonging to an individual,belonging to a platform,belonging to some combinations of the two,or can be seen as a form of Internet-based public data.Analysis of legal clauses and doctrines as well as analysis based in legitimacy and consequentialism both fail to completely delineate data ownership.One potential reason for this is that there are many types of platform data,and that each type is highly dependent on circumstances.The determination of rights in regard to platform data should be done in a way which revolves around a contextual regulatory framework,one in which the rules of reason is applied on a case-by-case basis and in which gradual changes are done in a bottom-up manner,and not one which seeks to establish a universal set of data regulations.In actual judgments,factors such as the nature of the platform and the nature of the data crawling behavior should be comprehensively considered while ensuring a balance of data circulation and data protection.

Cyber Security-Protecting Personal Data

Many organizations have datasets which contain a high volume of personal data on individuals,e.g.,health data.Even without a name or address,persons can be identified based on the details(variables)on the dataset.This is an important issue for big data holders such as public sector organizations(e.g.,Public Health Organizations)and social media companies.This paper looks at how individuals can be identified from big data using a mathematical approach and how to apply this mathematical solution to prevent accidental disclosure of a person’s details.The mathematical concept is known as the“Identity Correlation Approach”(ICA)and demonstrates how an individual can be identified without a name or address using a unique set of characteristics(variables).Secondly,having identified the individual person,it shows how a solution can be put in place to prevent accidental disclosure of the personal details.Thirdly,how to store data such that accidental leaks of the datasets do not lead to the disclosure of the personal details to unauthorized users.

Development of data acquisition and over-current protection systems for a suppressor-grid current with a neutral-beam ion source

Neutral beam injection is one of the effective auxiliary heating methods in magnetic-confinementfusion experiments. In order to acquire the suppressor-grid current signal and avoid the grid being damaged by overheating, a data acquisition and over-current protection system based on the PXI（PCI e Xtensions for Instrumentation） platform has been developed. The system consists of a current sensor, data acquisition module and over-current protection module. In the data acquisition module,the acquired data of one shot will be transferred in isolation and saved in a data-storage server in a txt file. It can also be recalled using NBWave for future analysis. The over-current protection module contains two modes： remote and local. This gives it the function of setting a threshold voltage remotely and locally, and the forbidden time of over-current protection also can be set by a host PC in remote mode. Experimental results demonstrate that the data acquisition and overcurrent protection system has the advantages of setting forbidden time and isolation transmission.

The COVID-19 and the“European Solution”of Data-based Approach to Governance:Public Security or Data Protection?

To cope with the challenges of CoViD-19,europe has adopted relevant measures of a data-based approach to governance,on which scholars have huge differences,and the related researches are conducive to further discussion on the differences.By sorting out the challenges posed by the pandemic to public security and data protection in europe,we can summarize the“european Solution”of the data-based approach to governance,including legislation,instruments,supervision,international cooperation,and continuity.The“Solution”has curbed the spread of the pandemic to a certain extent.However,due to the influence of the traditional values of the EU,the“Solution”is too idealistic in the balance between public security and data protection,which intensifies the dilemma and causes many problems,such as ambiguous legislation,inadequate effectiveness and security of instruments,an arduous endeavor in inter national cooperation,and imperfect regulations on digital green certificates.Therefore,in a major public health crisis,there is still a long way to go in exploring a balance between public security and data protection.

On the Right to the Protection of Personal Data as a Constitutional Right

The right to the protection of personal data is an important human right in the era of big data and a constitutional right based on the national protection obligation and the theory of human dignity,making it of special significance for the realization of citizenship in a digital society.It can be seen from an examination of the constitutional texts of various countries in the world that the right to the protection of personal data as a constitutional right has rich normative connotations,and the key legal link to realize this right lies in the national legislature actively fulfilling its obligation to shape and specify the protection of personal data in accordance with the entrustment of the constitutional norms.Given the constitutional principles of fundamental rights protection,i.e.,realizing the constitutional status of the right to the protection of personal data as a basic right by means of institutional guarantees,the legislature should first adhere to the constitutionality principle of data protection legislation.Second,a multi-level data protection legal system centered on the right to the protection of personal data should be established.Finally,the institutional guarantee mechanism for the protection of personal data should be continuously improved through constitutional interpretation.

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.

Robust Deep Image Watermarking:A Survey

In the era of internet proliferation,safeguarding digital media copyright and integrity,especially for images,is imperative.Digital watermarking stands out as a pivotal solution for image security.With the advent of deep learning,watermarking has seen significant advancements.Our review focuses on the innovative deep watermarking approaches that employ neural networks to identify robust embedding spaces,resilient to various attacks.These methods,characterized by a streamlined encoder-decoder architecture,have shown enhanced performance through the incorporation of novel training modules.This article offers an in-depth analysis of deep watermarking’s core technologies,current status,and prospective trajectories,evaluating recent scholarly contributions across diverse frameworks.It concludes with an overview of the technical hurdles and prospects,providing essential insights for ongoing and future research endeavors in digital image watermarking.

A Literature Review: Potential Effects That Health Apps on Mobile Devices May Have on Patient Privacy and Confidentiality

Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selecting eighty-eight articles published over the past fifteen years. The study assessed data gathering and storage practices, regulatory adherence, legal structures, consent procedures, user education, and strategies to mitigate risks. Results: The findings reveal significant advancements in technologies designed to safeguard privacy and facilitate the widespread use of mHealth apps. However, persistent ethical issues related to privacy remain largely unchanged despite these technological strides.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

The Intersection of Privacy by Design and Behavioral Economics: Nudging Users towards Privacy-Friendly Choices

This paper conducts a comprehensive review of existing research on Privacy by Design (PbD) and behavioral economics, explores the intersection of Privacy by Design (PbD) and behavioral economics, and how designers can leverage “nudges” to encourage users towards privacy-friendly choices. We analyze the limitations of rational choice in the context of privacy decision-making and identify key opportunities for integrating behavioral economics into PbD. We propose a user-centered design framework for integrating behavioral economics into PbD, which includes strategies for simplifying complex choices, making privacy visible, providing feedback and control, and testing and iterating. Our analysis highlights the need for a more nuanced understanding of user behavior and decision-making in the context of privacy, and demonstrates the potential of behavioral economics to inform the design of more effective PbD solutions.

Competencies in Computer Security and Resolution of Technological Problems in Higher Education Students

Starting from the importance of preserving our information and protecting our devices against attacks on their vulnerabilities, this article aims to establish the level of knowledge in computer security and problem-solving of students at a university in northwest Mexico. This research has a quantitative approach where the European Framework of Digital Competencies for Citizenship was used as a reference to identify and establish the level of the competencies that were evaluated. The IKANOS Test was used as a data collection tool. The results show that students know the importance of keeping their devices safe and how valuable the information found on them is. On the other hand, the results also show a considerable percentage of students who do not have the knowledge and are at a basic level of knowledge to solve technical problems with their devices.

浅析基于持续数据保护技术下的智慧校园建设

智慧校园是利用信息化技术来辅助传统校园进行教育管理的一种新模式。本文从我国高校智慧校园建设中数据保护的现状出发,结合持续数据保护技术运用,融入基于多维链表IO日志记录算法、卷镜像中断后快速增量初始化方法、高可靠多粒度变尺度自适应容错技术、可视化集中管控防御技术等提示数据安全机制,对智慧校园建设提出了改进策略,具有一定推广价值。

An Enhanced Security System Using Blockchain Technology for Strong FMC Relationship

Blockchain technology is a shared database of logs of all consumer transactions which are registered on all machines on a network.Both transactions in the system are carried out by consensus processes and to preserve confidentiality all thefiles contained cannot be changed.Blockchain technology is the fundamental software behind digital currencies like Bitcoin,which is common in the marketplace.Cloud computing is a method of using a network of external machines to store,monitor,and process information,rather than using the local computer or a local personal computer.The software is currently facing multiple problems including lack of data protection,data instability,and reliability.This paper aims to give the highest security for multiple user environments in cloud for storing and accessing the data in blocks.The users who are legitimate are only allowed for storing and accessing the data as like a secured block chain approach.As like the Blockchain which does not require a centralized system for transactions,the proposed system is also independent on centralized network interface.The decentralized system is developed in such a way to avoid counterfeiting.The system enables the fabricator to spend less or null resources to perform the validations for its direct operated stores.This ensures the product fabricator to avoid the circulation of its duplicate products.The customer as an end-user is also ensured to have only the genuine products from the fabricator.The Fabricator(F),Merchant(M)and consumer(C)forms an interconnected triangular structure without allowing any counterfeiting agents in their secured cloud chain.The pro-posed approach provides the stability in the security system of the cloud using the chaining mechanism within different blocks at each node.It takes roughly 4.7,6.2,and 7.5 ms,respectively,to register each node in the proposed system for 5,10,and 15 nodes.The overall registration time for each scenario is 11.9,26.2,and 53.1 ms,despite the fact that each node’s registration time was greatest for 10 nodes.By looking at the data,it’s clear that the number of nodes is a func-tion of time.

U.S.and International Legal Perspectives Affecting Cybersecurity Corporate Governance

International and U.S.corporations must be well advised regarding specific regulations and laws that affect cybersecurity decisions because the Board of Directors must perform due diligence to avoid regulatory negligence and lawsuit liability.Depending on the standards and the regulations that do define reasonable care,the corporate director is faced with the challenge of determining how and what cybersecurity laws apply.Then,directors can institute best cybersecurity management practices.This paper provides guidance regarding the application of the law in the areas of cyber security for the international corporations interacting with the European General Data Protection Regulations(GDPR),the California Consumer Privacy Act(CCPA),and recent Federal Trade Commission(FTC)administrative agency rulings.Reading this paper is worth your time because it will inform you of the legal challenges that international and domestic corporations face in making decisions about spending capital to manage cybersecurity and at the same time perform due diligence.In other words,if there is a cybersecurity breach,this paper will provide insights into what law must be followed by the corporation enabling the best management decisions assuring adequate response,compliance,thereby avoiding unnecessary liability risk.The paper also provides reflections about whether the GDPR serves as a better legal comprehensive regulatory model rather than the recently enacted laws in the U.S.

International Cybersecurity Breach Detection Risk, Prosecution and Resolution

The U.S.and the international business community is in a crisis regarding ransomware attacks and cybersecurity policing/regulation.Based on recent events,state sponsored cyber hackers have made it their mission to hold the information security world hostage extorting money for a returning of data systems to normal functioning.This paper examines the challenges for the global business community regarding the scope of the attacks,the current state of the law in the U.S.intended to provide current information to the international business community,illustrate the challenges for regulators and the courts,illustrate the recent progress of the criminal investigatory aspects of apprehending cybercriminals,report on the non-delegable duties of decision makers in the international community doing business in the U.S.,and demonstrate the potential solutions to this evolving international crisis.It is worth your time to read this paper for the following reasons:1.Understanding the risks and the scope of the problem moving forward with doing business in the U.S.;2.communicating recent developments fostering cooperation and contributing to mediating cybersecurity events for international corporations;and 3.providing information on the current state of the law by the U.S.Supreme Court pointing out the relevant and the consequential outcomes of the legal system leading to potential smart solutions for planning business decisions.

Detecting Phishing Using a Multi-Layered Social Engineering Framework

As businesses develop and expand with a significant volume of data,data protection and privacy become increasingly important.Research has shown a tremendous increase in phishing activities during and after COVID-19.This research aimed to improve the existing approaches to detecting phishing activities on the internet.We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs.In the algorithm,we considered technical dimensions of phishing attack prevention and mitigation on the internet.In our approach,we merge,Phishtank,Blacklist,Blocklist,and Whitelist to form our framework.A web application system and browser extension were developed to implement the algorithm.The multi-layer phish detector evaluated ten thousandURLs gathered randomly from the internet(five thousand phishing and five thousand legitimate URLs).The system was estimated to detect levels of accuracy,true-positive and false-positive values.The system level accuracy was recorded to be 98.16%.Approximately 49.6%of the websites were detected as illegitimate,whilst 49.8%were seen as legitimate.

An attribute-based access control scheme using blockchain technology for IoT data protection

With the wide application of the Internet of Things(IoT),storing large amounts of IoT data and protecting data privacy has become a meaningful issue.In general,the access control mechanism is used to prevent illegal users from accessing private data.However,traditional data access control schemes face some non-ignorable problems,such as only supporting coarse-grained access control,the risk of centralization,and high trust issues.In this paper,an attribute-based data access control scheme using blockchain technology is proposed.To address these problems,attribute-based encryption(ABE)has become a promising solution for encrypted data access control.Firstly,we utilize blockchain technology to construct a decentralized access control scheme,which can grant data access with transparency and traceability.Furthermore,our scheme also guarantees the privacy of policies and attributes on the blockchain network.Secondly,we optimize an ABE scheme,which makes the size of system parameters smaller and improves the efficiency of algorithms.These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments.Thirdly,to prohibit attribute impersonation and attribute replay attacks,we design a challenge-response mechanism to verify the ownership of attributes.Finally,we evaluate the security and performance of the scheme.And comparisons with other related schemes show the advantages of our proposed scheme.Compared to existing schemes,our scheme has more comprehensive advantages,such as supporting a large universe,full security,expressive policy,and policy hiding.