Personal information is a vital productive commodity in the digital economy, and its processing has seen unparalleled transformations in both breadth and depth. This article proposes to enhance the legal remedies for personal information rights in contemporary China. Research has revealed multiple practical challenges in China’s judicial practices, such as hesitance to prosecute owing to an absence of substantial legal foundation, improper distribution of the burden of proof, and inadequate integration of criminal-civil judicial safeguards for personal information. This paper advocates for China to elucidate the definition of personal information rights via legislation, enable the litigation of personal information infringement cases, and establish explicit criteria for their acceptance into judicial proceedings. Furthermore, China must develop an appropriate structure for distributing the burden of evidence. It must also use discretionary judgment to properly tackle the problems related to evaluating damages in instances of personal information violations.

The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

This study aims to investigate the phenomenon of non-disclosure of personal information among male individuals, employing the Communication Privacy Management Theory as a guiding framework. The objectives of the study encompass identifying the specific types of personal information male students refrain from disclosing, examining the underlying reasons for their non-disclosure practices, and assessing the impact of non-disclosure on their interpersonal relationships. Qualitative research methods, primarily in-depth interviews, were employed to gather insights, with six male students from Sultan Idris Education University (UPSI) participating in the interviews. The findings reveal that male students at UPSI do engage in non-disclosure of personal information, albeit to a certain extent. Specifically, the findings discovered four types of personal information—secrets, traumas, dark history, and family matters—that these students commonly choose not to disclose. Notably, there are four categories of personal information they tend to withhold, namely secrets, traumas, dark history, and family matters. The reluctance to disclose stems from factors such as insecure attachment, a reluctance to worry about their parents, and strained relationships with their family members. Furthermore, the study highlights that non-disclosure of personal information has both negative and positive repercussions on the participants’ relationships with others. Moreover, the study underscores that non-disclosure of personal information can have both negative and positive effects on the participants’ relationships, shedding light on the complexities of navigating personal privacy choices in the university and job-seeking context. The study contributes valuable insights into the challenges of employability dilemmas faced by male university students concerning the management of personal information.

Divorce for female civil servants in Indonesia is more complex than for non-civil servants due to a pseudo-administrative process. This condition requires submitting a written application for divorce permission to their agency and proceeding through multiple lengthy stages. During this process, women must verbally disclose sensitive personal details to state authorities. Failure to obtain written permission or to report the divorce within a specific period can result in disciplinary action. This paper examines how female civil servants protect their privacy while seeking divorce permission, focusing on managing personal information, controlling divorce-related details at work, and handling the information turbulence that arises. The researcher collected data from 12 female civil servants at Indonesia’s Directorate General of Taxes (DGT) who had applied for divorce permission. The findings reveal the subjective experiences and strategies women civil servants use to manage sensitive personal issues. The quasi-administrative nature of the divorce permit process introduces complexities that extend beyond formal procedures. Regulations governing the submission of divorce permits, overseen by government agencies, often add to the burden these women face, neglecting their privacy and psychological well-being. Impartial individuals and gender preferences in the verification team can exacerbate distress. Therefore, revising the divorce permit regulations to enhance privacy and sensitivity is crucial. The study recommends early information about the process and communication training for maintaining privacy.

An unprecedented demand for accurate information and action moved the industry toward RegTech where computing, big data, and social and mobile technologies could help achieve the demand. With the introduction and adoption of RegTech, regulatory changes were introduced in some countries. Enhanced regulatory changes to ease the barriers to market entry, data protection, and payment systems were also introduced to ensure a smooth transition into RegTech. However, regulatory changes fell short of comprehensiveness to address all the issues related to RegTech’s operation. This article is an attempt to devise a Privacy Model for RegTech so industries and regulators can protect the interests of various stakeholders. This model comprises four variables, and each variable consists of many items. The four variables are data protection, accountability, transparency, and organizational design. It is expected that the adoption of this Privacy Model will help industries and regulators embrace standards while being innovative in the development and use of RegTech.

In today’s digital education landscape, safeguarding the privacy and security of educational data, particularly the distribution of grades, is paramount. This research presents the “secure grade distribution scheme (SGDS)”, a comprehensive solution designed to address critical aspects of key management, encryption, secure communication, and data privacy. The scheme’s heart lies in its careful key management strategy, offering a structured approach to key generation, rotation, and secure storage. Hardware security modules (HSMs) are central to fortifying encryption keys and ensuring the highest security standards. The advanced encryption standard (AES) is employed to encrypt graded data, guaranteeing the confidentiality and integrity of information during transmission and storage. The scheme integrates the Diffie-Hellman key exchange protocol to establish secure communication, enabling users to securely exchange encryption keys without vulnerability to eavesdropping or interception. Secure communication channels further fortify graded data protection, ensuring data integrity in transit. The research findings underscore the SGDS’s efficacy in achieving the goals of secure grade distribution and data privacy. The scheme provides a holistic approach to safeguarding educational data, ensuring the confidentiality of sensitive information, and protecting against unauthorized access. Future research opportunities may centre on enhancing the scheme’s robustness and scalability in diverse educational settings.