A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Due to the presence of a large amount of personal sensitive information in social networks,privacy preservation issues in social networks have attracted the attention of many scholars.Inspired by the self-nonself discrimination paradigmin the biological immune system,the negative representation of information indicates features such as simplicity and efficiency,which is very suitable for preserving social network privacy.Therefore,we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks,called AttNetNRI.Specifically,a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept private.Moreover,a negative database-based method is proposed to hide node attributes,so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes,which is crucial to the analysis of social networks.To evaluate the performance of the AttNetNRI,empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social networks.The experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding parts.The experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

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 Impact of Information Technology on Service Quality,Satisfaction,and Customer Relationship Management(Case Study:IT Organization Individuals)

Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.

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.

A Method to Improve the Accuracy of Personal Information Detection

It is necessary to confirm the personal data factors and the rules of verification before conducting personal data detection. So that the detection method can be written in the subsequent implementation of the automatic detection tool. This paper will conduct experiments on common personal data factor rules, including domestic personal identity numbers and credit card numbers with checksums. We use ChatGPT to test the accuracy of identifying personal information like ID card identification numbers or credit card numbers. And then use personal data correlation to reduce the time for personal data identification. Although the number of personal information factors found has decreased, it has had a better effect on the actual manual personal data identification. The result shows that it saves about 45% of the calculation time, and the execution efficiency of the accuracy is also improved with the original method by about 22%, which is about 2.2 times higher than the general method. Therefore, the method proposed in this paper can accurately and effectively find out the leftover personal information in the enterprise. .

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.

Customer Information Disclosure and Analyst Forecasts : Empirical Evidence from Analysts' Perspective

Based on the company's disclosure of key customer information,the impact of corporate customer concentration on analyst forecast was studied,and we further studied the impact of detailed customer names on analyst forecasts. It is found that:(i) customer concentration significantly affects the accuracy of analyst forecasts. The higher the customer concentration is,the lower the accuracy of analyst forecasts is;(ii) Voluntary disclosure of customer names can provide incremental information to analysts and mitigate the negative impact of customer concentration on the accuracy of analyst forests;(iii) further research has found that the incremental information brought by the state-owned enterprises' disclosure of the customer names to analysts is more obvious; disclosure of customer names by companies with high environmental uncertainty is more likely to be of concern to analysts; and star analysts have a higher ability to interpret customer names than non-star analysts.

The college students' response to customized information services based on Library2.0 technologies at universities in Nanjing

Through a questionnaire survey of students’ response from 6 universities in Nanjing, this paper aims to determine their varying degrees of satisfaction about the customized information service based on Library2.0 technologies. In so doing, the authors carefully examined the data collected from the returned questionnaires about such key issues as the students’ perceptions about the customized information service via a Library2.0platform, self-initiated use experience of such a mechanism, their achieved information searching results vis-à-vis their expectations, etc. In addition, the authors also made a comparative study between information providers(i.e. librarians) and information consumers(i.e. students) at Chinese and American academic libraries.

Ad Blockers & Online Privacy: A Comparative Analysis of Privacy Enhancing Technologies (PET)

Online tracking mechanisms employed by internet companies for user profiling and targeted advertising raise major privacy concerns. Despite efforts to defend against these mechanisms, they continue to evolve, rendering many existing defences ineffective. This study performs a large-scale measurement of online tracking mechanisms across a large pool of websites using the OpenWPM (Open Web Privacy Measurement) platform. It systematically evaluates the effectiveness of several ad blockers and underlying Privacy Enhancing Technologies (PET) that are primarily used to mitigate different tracking techniques. By quantifying the strengths and limitations of these tools against modern tracking methods, the findings highlight gaps in existing privacy protections. Actionable recommendations are provided to enhance user privacy defences, guide tool developers and inform policymakers on addressing invasive online tracking practices.

Fuzzy Privacy Decision for Context-Aware Access Personal Information

A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, it can produce fuzzy privacy decision as the change of personal information sensitivity and personal information receiver trust. The uncertain privacy decision model was proposed about personal information disclosure based on the change of personal information receiver trust and personal information sensitivity. A fuzzy privacy decision information system was designed according to this model. Personal privacy control policies can be extracted from this information system by using rough set theory. It also solves the problem about learning privacy control policies of personal information disclosure.

Customization and Performance of Service-Oriented Manufacturing Information System: The Mediating Effect of Information System Flexibility

The purpose of this paper is to provide empirical evidence for the validity of the relationship between service-oriented manufacturing information system (SMIS) customization and performance from three aspects: data flexibility, process flexibility and system flexibility. We select some questionnaires from the third round of High-performance manufacturing (HPM) data to construct the construct, verify the reliability and validity of the construct, extract principal components, and analyze the mediating effect by using multiple chain linear regression and structural equation model. The results show that SMIS customization has a significant impact on its performance, and this effect works through its flexibility. More specifically, it is the multiple chain mediation effect composed of data flexibility, process flexibility and system flexibility. The importance of SMIS customization and flexibility to the organization is made clear, which helps practitioners understand the internal mechanism that affects SMIS performance, so as to use limited resources to improve system performance.

Whispered Tuning: Data Privacy Preservation in Fine-Tuning LLMs through Differential Privacy

The proliferation of Large Language Models (LLMs) across various sectors underscored the urgency of addressing potential privacy breaches. Vulnerabilities, such as prompt injection attacks and other adversarial tactics, could make these models inadvertently disclose their training data. Such disclosures could compromise personal identifiable information, posing significant privacy risks. In this paper, we proposed a novel multi-faceted approach called Whispered Tuning to address privacy leaks in large language models (LLMs). We integrated a PII redaction model, differential privacy techniques, and an output filter into the LLM fine-tuning process to enhance confidentiality. Additionally, we introduced novel ideas like the Epsilon Dial for adjustable privacy budgeting for differentiated Training Phases per data handler role. Through empirical validation, including attacks on non-private models, we demonstrated the robustness of our proposed solution SecureNLP in safeguarding privacy without compromising utility. This pioneering methodology significantly fortified LLMs against privacy infringements, enabling responsible adoption across sectors.

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.

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.

Management of Address Information to Improve Quality of Customer Contact

Customer relationship management systems are gaining importance in today's business environment since customer satisfaction is crucial to the success of an enterprise, and especially so in e-business environment where customers can find substitute suppliers quite easily. In CRM, the quality of customer information is very important, and the address information even more so. It is because the address information plays a major role for customer contact channel and for timely and effective marketing service. Furthermore, it gives the basic source of geographic information for the offline delivery, the terminal activity of the e-commerce. In this study, we analyze various standards and proposals for the address information, and propose data models for the management of the information focusing on address components, and proto-type systems for management and service.

An Information-Aware Privacy-Preserving Accelerometer Data Sharing

In the age of big data,plenty of valuable data have been shared to enhance scientific innovation,which,however,may disclose unexpected privacy leakage.Although numerous privacy preservation techniques have been proposed to conceal sensitive information,it is usually at the cost of the application utility reduction.In this paper,we present a data sharing scheme,which balances the application utility and privacy leakage for specific data sharing.To illustrate our scheme,smartphones’acceleration data have been adopted as an illustrative example.Experimental study has shown that sampling frequency play dominant roles in reducing privacy leakage with much less reduction on utility.

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.