Online Security Research Articles

Utilizing Crowdsourcing to Incorporate the Voice of the Family When Developing a Diabetes Distress Intervention

OBJECTIVE Diabetes distress (DD) is the negative emotional toll of living with or caring for type 1 diabetes, encompassing the pervasiveness of its daily demands. We recently developed Remedy to Diabetes Distress (R2D2), a screen-to-treat intervention for families of school-aged children with type 1 diabetes. This article reports on the use of crowdsourcing methods to design the intervention and capture the voice of parent stakeholders. RESEARCH DESIGN AND METHODS We recruited 41 parents of 8- to 12-year-olds with type 1 diabetes. In a secure online social network, we posted study questions to participants, who could respond to our questions and view and comment on other participants’ responses (i.e., participants could interact as a “crowd”). An iterative approach allowed our questions to move from broad to specific, enabling parent input on treatment content. RESULTS Using a conceptual model of DD, we examined responses and applied codes to distill qualitative categories. We established substantial agreement on identified categories, with fidelity at κ = 0.615. In addition to providing broad feedback (e.g., on preferred language for common phrases used in type 1 diabetes interventions), parents also provided feedback on specific treatment components and the overall tone of the intervention. Parents highlighted benefit-finding and positive talk/self-talk as pertinent for incorporation into treatment. CONCLUSION This study illustrates the use of crowdsourcing methods to capture the voices of parents of school-aged children with type 1 diabetes when designing a DD intervention. The next phase of R2D2 will be a small pre-trial to evaluate the feasibility and acceptability of the intervention, followed by a proof-of-concept randomized controlled trial (RCT), during which family voices will continue to be incorporated.

Evaluating AES Security: Correlation Power Analysis Attack Implementation using the Switching Distance Power Model

Cryptographic circuits play a critical role in safeguarding confidential information and ensuring secure communication, contributing to the resilience of digital infrastructure under SDG 9 (Industry, Innovation, and Infrastructure). These circuits store encryption keys for the Advanced Encryption Standard (AES) algorithm, including AES-128, AES-192, and AES-256, which are widely used in applications such as online banking and secure messaging platforms. This paper examines the effectiveness of Correlation Power Analysis (CPA), a side-channel attack technique that exploits power consumption patterns in cryptographic circuits, to highlight the challenges of implementing secure encryption systems. The study illustrates the CPA attack procedure against AES implemented on the SASEBO-GII FPGA platform. Experimental results reveal that while the CPA attack based on the Hamming Weight (HW) power consumption model fails to extract the encryption key, the Switching Distance (SD) power consumption model successfully recovers the entire key with a 100% success rate using approximately 4000 power traces. These findings underscore the vulnerability of cryptographic circuits to advanced side-channel attacks and emphasize the need for robust countermeasures to ensure secure data protection, thereby advancing secure and sustainable digital environments under SDG 11 (Sustainable Cities and Communities).

Enhancing online exam security: encryption and authentication in Jordanian and international universities

In today's educational landscape, the online examination system has become crucial, particularly due to the challenges posed by the coronavirus disease 2019 (COVID-19) pandemic. Despite its advantages in expediting result dissemination and reducing resource consumption, online examinations face significant security threats like leakage, cheating, fraud, and hacking, which hinder their widespread adoption. This paper addresses these security concerns by proposing integrating advanced security algorithms and biometric devices. It presents a comprehensive literature review on existing online examination systems, focusing on their security mechanisms, and compares these findings with a proposed framework. Additionally, a questionnaire was administered across Jordanian governmental and private universities to explore strategies for safeguarding computerized tests through encryption and authentication methods. The results reveal that Jordanian institutions lack adequate security safeguards and procedural standards. Key recommendations include encrypting the question bank stored in databases and employing biometric identification techniques to enhance the security and effectiveness of student verification. The proposed framework aims to improve the overall security, speed, and secrecy of the online examination process, addressing the critical gaps identified in current systems. This research contributes to developing more secure and reliable online examination systems in higher education.

Prescripto

Abstract: The Prescripto is a digital platform that simplifies scheduling medical consultations. It allows patients to search for doctors by specialty, location, or availability and book appointments at their convenience. The system supports secure user authentication, real-time updates, and online payment integration for consultation fees. Doctors can manage their schedules, view patient details, and track appointments efficiently. Notifications and reminders enhance user experience by ensuring timely updates. By modernizing the appointment process, this system improves accessibility, reduces wait times, and enhances the overall efficiency of healthcare services

Engaging the private sector as part of HIV pre-exposure prophylaxis service delivery in Vietnam: a comparative analysis of uptake, persistence and HIV seroconversion from 2018 to 2023.

In Vietnam, PrEP was introduced in 2017 and scaled up from 2019. Private sector engagement (PSE) in PrEP service delivery was deployed as a strategy from the start to increase PrEP access. We assessed the effectiveness of this approach to inform ongoing efforts to accelerate epidemic control by 2030. We implemented a process evaluation with longitudinal design using retrospective programmatic data collected and uploaded onto a secure online system (HMED) from 23 public and 17 private PrEP clinics in Hanoi, Ho Chi Minh City (HCMC), and Dong Nai. We measured the effectiveness of PrEP service delivery by PrEP initiation/reinitiation, uptake, persistence, discontinuation, and HIV seroconversion. We used the Kaplan-Meier time-to-event approach to estimate PrEP persistence and mixed-effects logistic regression analysis to assess factors associated with the PrEP persistence. From October 2017 to September 2023, 29,944 individuals initiated PrEP, and among these, 79.3% started PrEP at a private sector clinic while 20.7% initiated in a public sector clinic. The median duration of PrEP use persistence at private clinics was significantly longer than that at public clinics (268 days vs. 148 days, respectively). Mixed-effects logistic regression analysis results indicated a significant statistical association between PrEP persistence for at least three months and initiating PrEP at a private clinic [adjusted odds ratio [aOR] = 4.28; 95% confidence interval [CI]: 2.96-6.19], opting for TelePrEP (aOR = 3.42; 95% CI: 2.12-5.53), or being 20 years of age or older (aOR = 1.86; 95% CI: 1.62-2.13). HIV seroconversion was significantly lower among PrEP users at private clinics compared to public clinics (0.03 vs. 0.13 per 100 person-years, respectively; p < 0.01). Offering choice in PrEP service delivery options is essential to increase access and uptake. Private-sector PrEP providers play a pivotal role in increasing PrEP uptake and coverage in Vietnam, and will be critical to delivery of new long-acting options.

Anonymity on the darknet: the key to the security of financial institutions or a threat to society

With the progressive development of digital technologies, online security and anonymity are becoming important conditions in the virtual world, which is reflected in the darknet phenomenon. Cybercrime, being the main threat on the darknet, covers a wide range of illegal activities, including the distribution of stolen data. The motives of digital criminals vary, ranging from monetary gain to undermining trust in financial organizations and government agencies. Russia takes the leading position in ads for the sale of stolen databases, and the frequency of information leaks is only increasing. It is noted that the dark web is becoming not only a platform for illegal actions, but also a place to attract new specialists to hacker groups. Financial organisations are of great interest to them, as it is through them that large money flows. This fact creates favourable conditions for receiving significant ransoms for stolen information, and also makes the financial sector the second largest leader in losses from data breaches. Despite growing attention to the security of the domestic financial industry, it remains underfunded compared to global standards. The darknet is a complex phenomenon where anonymity can serve as both a defence of human rights and a threat to public safety. Users act without fear of being caught, punished, which leads to abuse. Regulation of the darknet is a serious task for the authorities and international organisations due to the constant improvement of digital criminals' technologies and significant differences in legislation. The article considers the essence of the darknet, its pros and cons, and concludes that anonymity in the darknet plays a key role. On the one hand, it is a tool to protect human rights and personal freedom, on the other hand, it is a threat to public safety. Therefore, the issues of privacy and cybercrime on the darknet will remain relevant for a long time due to the directly proportional relationship between the economic stability of countries and the living standards of their citizens.

Usage and awareness of nutritional screening tools by nurses caring for pediatric patients in Yozgat province

Aims: Malnutrition is a significant health issue in children and is closely related to prolonged hospital stays, increased complications, and mortality risk in hospitalized children. Effective use of nutritional screening tools is crucial for early detection of malnutrition. In this context, the active use of nutritional screening tools, the skill to use these tools, and the level of awareness about these tools among nurses who closely care for pediatric patients are vital factors that can potentially improve pediatric patients' health. Our study examines the usage and awareness of nutritional screening tools among nurses caring for pediatric patients in Yozgat province, a region with unique healthcare challenges and opportunities. Methods: The study was planned as a prospective, descriptive, and cross-sectional design. Ninety-four nurses caring for pediatric patients in Yozgat province and its districts were administered an online questionnaire of 22 questions, which was designed to assess their knowledge, skills, and attitudes towards nutritional screening tools. The questionnaire was distributed through a secure online platform and included both closed-ended and open-ended questions. Data were evaluated using descriptive statistics with SPSS version 27.0. Results: Of the participants, 78.7% were female and 21.3% were male. 60.6% of the participants were in the age range of 25-34 years, 62.8% had a bachelor's degree, 66% worked at state university hospitals, 30.9% had 6-10 years of professional experience, 74.5% were service nurses, and 39.4% had been involved with pediatric patients for 0-1 years. The most frequently cared age group was 3-6 years (19.9%) and 1-3 years (18.1%). 27.7% of the participants assessed nutrition risk status using visual assessment, 25.5% through anthropometric measurements, and 34% reported referring the physician and dietitian for intervention in risk detection. 47.9% indicated the presence of a screening scale in their institution, 57.1% used the form, 25.5% did not know the name of the screening scale, and 6.4% used the StrongKids scale. Conclusion: Our study determined that nurses caring for pediatric patients often consider the screening scale as a secondary option for identifying the nutrition risk status, predominantly performing visual and anthropometric evaluations, and did not demonstrate sufficient proficiency or importance regarding screening scales. Although the determination of risk status varies according to the scale used, the significance of screening scales in detecting malnutrition is substantial. Therefore, our study recommends that necessary training be provided to pediatric nurses to use these tools more effectively and that current practices be reviewed. This will not only enable better assessment of the nutritional status of pediatric patients but also instill hope for the implementation of steps to prevent malnutrition.

Outsmarting Phishers: A Comparative Analysis of Machine Learning Techniques

Phishing attacks threaten the security of the internet by stealing confidential data and money as well. As a way to prevent phishing, an extensive comparative study of the top most machine learning methods for phishing site detection was carried out. This research analyses the performance of ANN, RNN, XGBoost and Random Forest algorithms in the identification of phishing websites using the Kaggle dataset. These algorithms were selected due to their ability to uncover intricate associations and patterns from website information. The review examines the advantages and disadvantages each algorithm presents and compares them to each other based on accuracy efficient, precision, recall, F1 score, and computing efficiency. Through the comparison of these algorithms, the most effective algorithm for phishing detection is revealed, which can be useful to scholars and experts who focus on the improvement of on-line security. The research helps deposit the foundations for attacks prevention and facilitates the protection of online sensitive information. This study shows the effectiveness of using machine learning in the field of cybersecurity, especially with focus on the algorithms and how they can be optimized.

واقع تطبيقات الرقابة الأبويّة واستخدامها في فلسطين: محافظة الخليل أنموذجا

With the growing popularity of smart devices, a plethora of parental control applications have been developed to monitor children and protect them from online security risks. The study aims to identify the reality of parental control applications and their use in Hebron Governorate from parents' viewpoint. Using the descriptive approach, the researchers distributed a questionnaire to a sample of 500 people chosen at random from the 274,500 total study population. The findings revealed that parental control applications were used by 20.6% of the total study population, which is a relatively small percentage. A greater percentage of females than males preferred parental control, and that parents under the age of 25 had greater preferences than parents in other age groups about their children's use of smart devices. As the number of children grows, so does the preferences for parental control. The study recommended that parents' awareness be increased by holding seminars on parental control preferences and application features. The study further recommended that the relevant authorities educate children about the risks associated with smart devices and their various applications.

Predictors of the Likelihood of Continuous Usage of Online Shopping Post-COVID-19

Government’s response to the COVID-19 outbreak resulting in imposed socialdistancing measures, lockdowns and closing of economies triggered the acceleration of e-commerce growth globally. Driven by necessity consumers shifted from traditional to online shopping, but the main question of interest to practitioners and researchers is: Will this changed behaviour last post-COVID-19? We aim in this study to respond and contribute to the insufficient understanding of the factors that can predict the likelihood of continuous usage of online shopping post-COVID-19. To achieve this goal, we use survey data from 2.082 respondents, collected in North Macedonia during the period of social distancing measures (November 2020). We explore the associated predictors of the likelihood of online shopping continuity behaviour post-COVID-19, employing binary logit regression. We found that age, data protection and conventional motives are not significant predictors while gender, employment status, online shopping frequency, online shopping experience, payment security and commencement of online triggered by COVID-19 showed as statistically significant predictors of the likelihood of continuous online shopping post-COVID-19.

Self-monitoring of blood pressure following a stroke or transient ischaemic attack (TASMIN5S): a randomised controlled trial

BackgroundBlood pressure (BP) control following stroke is important but currently sub-optimal. This trial aimed to determine whether self-monitoring of hypertension with telemonitoring and a treatment escalation protocol, results in lower BP than usual care in people with previous stroke or transient ischaemic attack (TIA).MethodsUnblinded randomised controlled trial, comparing a BP telemonitoring-based intervention with control (usual care) for hypertension management in 12 primary care practices in England. People with previous stroke or TIA with clinic systolic BP 130–180 mmHg, taking ≤ 3 antihypertensive medications and on stable treatment for at least four weeks were randomised 1:1 using secure online system to intervention or control. The BP:Together intervention comprised self-monitoring of blood pressure with a digital behavioural intervention which supported telemonitoring of self-monitored BP with feedback to clinicians and patients regarding medication titration. The planned primary outcome was difference in clinic measured systolic BP 12 months from randomisation but was not available following early study termination due to withdrawal of funding during the COVID-19 pandemic. Instead, in addition to pre-randomised data, routinely recorded BP was extracted from electronic patient records both pre- and post-randomisation and presented descriptively only. An intention to treat approach was taken.ResultsFrom 650 postal invitations, 129 (20%) responded, of whom 95 people had been screened for eligibility prior to the pandemic (November 2019-March 2020) and 55 (58%) were randomised. Pre-randomisation routinely recorded mean BP was 145/78 mmHg in the control (n = 26) and 145/79 mmHg in the self-monitoring (n = 21) groups. Post-randomisation mean BP was 134/73 mmHg in the control (n = 19) and 130/75 mmHg in the self-monitoring (n = 25) groups. Participants randomised to self-monitoring used the intervention for ≥ 7 months in 25/27 (93%) of cases.ConclusionsRecruitment of people with stroke/TIA to a trial comparing a BP self-monitoring and digital behavioural intervention to usual care was feasible prior to the COVID-19 pandemic and the vast majority of those randomised to intervention used it while the trial was running. Routinely recorded blood pressure control improved in both groups. Digital interventions including self-monitoring are feasible for people with stroke/TIA and should be definitively evaluated in future trials.Trial registrationISRCTN57946500 06/09/2019 Prospective.

Digital Empowerment:Improving Dasawisma's Capabilities in Online Marketing and Sales Through the Marketplace

This community service activity aims to improve the capabilities of dasawisma women in RW 10, Ciracas Village, Ciracas District, East Jakarta in digital marketing and online sales through the marketplace platform. Through a series of practical trainings, participants have been given an in-depth understanding of digital marketing concepts, effective online marketing strategies, and the use of various features in the marketplace platform. In addition, legal aspects, online security, and network development are also the focus, providing a strong foundation for participants to run an online business sustainably. With the aim of empowering the local economy, this activity is expected to help dasawisma women take advantage of the potential of the local economy and increase their contribution to local economic development, as well as this activity helps the government technically in relation to the community directly. This activity was attended by 120 participants and as many as 85 have provided feedback from the material and experience that has been given. The training material was delivered in lectures and discussions. For the lecture session, it was delivered by presenting material about digital marketing through the marketplace and comparing it in a conventional way. Broadly speaking, participants are able to accept and understand the use of digital marketing technology through the marketplace. Furthermore, the results of the implementation of community service activities were evaluated using a SWOT analysis with results showing a significant increase in understanding of online security and marketing. With the results of the training that show for the better, the community, especially dasawisma women, is ready to develop businesses both managed independently and business groups managed under the auspices of local residents.

Attitude of University Students Towards Online Shopping; A Study of Undergraduates in Nnamdi Azikiwe University, Awka, Anambra State

The proliferation of the internet has revolutionized consumer behaviour, particularly among university students who are increasingly embracing online shopping for its convenience and accessibility. This study investigates the attitudes of undergraduates at Nnamdi Azikiwe University, Awka, Anambra State towards online shopping, with a focus on understanding the factors influencing their behaviors. The objectives include exploring the level of trust and perceived security in online shopping among students, and identifying socio-demographic variables such as age and gender that shape their attitudes and behaviors. Employing a descriptive survey design, data was collected from a representative sample of 386 undergraduate students using structured questionnaires. The study period spanned one academic semester to capture a comprehensive view across various faculties and departments. The findings reveal a robust acceptance of online shopping among the university students, underscored by a high level of trust and perceived security in online payment systems. Statistical analyses, including correlation and regression models, highlight significant positive relationships between attitudes towards online shopping, age, and gender. Age and gender emerge as pivotal predictors, explaining a substantial portion of the variance in attitudes towards online shopping. Specifically, gender demonstrates a stronger influence than age on shaping these attitudes. The study's implications extend to recommendations for enhancing online security measures and developing targeted marketing strategies tailored to the diverse socio demographic profiles of university students.

Digitization and information technologies in the professional activity of a lawyer in modern conditions

The article is devoted to the analysis of the application of new technical tools and complex approaches to the digitization of advocacy activities to meet the needs of clients in legal assistance, which allows to ensure a higher quality level of legal business. Digitization of the legal profession, remoteness in communication with colleagues and clients has caused a demand for improving the skills of lawyers in working with various information platforms among lawyers and representatives of the legal business. A lawyer is considered as a person who uses, consumes and further analyzes legal information for the protection of legal rights and interests of clients, not as an end consumer. Problems in the digital provision of legal aid in modern Ukraine under martial law conditions have been identified, such as: the impossibility of offline meetings with clients; generation of electronic evidence for the recording of crimes or offenses and confirmation of damage caused to legal entities or individuals, paper document circulation. Digitization of advocacy as the main way to overcome the problems of defense activity. The development of information technologies in recent times and modern realities have caused a rather rapid introduction of information technologies and services in the field of advocacy and other legal areas. Therefore, the process of digitization of the legal profession is perceived as a positive phenomenon, because it can ensure the level of effective protection of the rights and legitimate interests of legal entities and individuals living or staying on the territory of Ukraine under martial law. It has been established that the application of scientific and technical achievements requires the presence of certain knowledge, abilities and skills. It is substantiated that the lack of technical support can create an obstacle in the lawyer’s proper execution of client assignments. The need to provide lawyers with their own online security and cyber security of their clients, assistants and interns is emphasized in order to prevent situations of disclosing attorney secrets, harming other lawyers, such as the authority or reputation or the institution of advocacy in general. It is noted that one of the aspects of the problems of advocacy is the dilemma of using or not using licensed software.

GPT-4 shows potential for identifying social anxiety from clinical interview data

While the potential of Artificial Intelligence (AI)—particularly Natural Language Processing (NLP) models—for detecting symptoms of depression from text has been vastly researched, only a few studies examine such potential for the detection of social anxiety symptoms. We investigated the ability of the large language model (LLM) GPT-4 to correctly infer social anxiety symptom strength from transcripts obtained from semi-structured interviews. N = 51 adult participants were recruited from a convenience sample of the German population. Participants filled in a self-report questionnaire on social anxiety symptoms (SPIN) prior to being interviewed on a secure online teleconference platform. Transcripts from these interviews were then evaluated by GPT-4. GPT-4 predictions were highly correlated (r = 0.79) with scores obtained on the social anxiety self-report measure. Following the cut-off conventions for this population, an F1 accuracy score of 0.84 could be obtained. Future research should examine whether these findings hold true in larger and more diverse datasets.

Harnessing AI and Two Factor Authentication for Enhanced Fraud Detection: How to craft Dynamic Friction in Account Takeover Fraud Detection

As cyber threats become increasingly sophisticated, traditional security measures have proven insufficient in combating these sophisticated Account Takeover fraud attacks as using Artificial Intelligence (AI) in fraud detection has gained prominence. This represents a significant threat to online security, leading to financial losses and reputational damage for both individuals and organizations. Two-Factor Authentication (2FA) emerges as a critical tool in bolstering the effectiveness of AI in account takeover fraud detection. This white paper explores the role of Two-Factor Authentication (2FA) in enhancing account security and provides a comprehensive guide on its implementation to dynamically add friction based on the risk. Keywords: Artificial Intelligence, CyberSecurity, Account Takeover, Digital Fraud Detection, Account Recovery, Incident Response, Machine Learning, Technology Modernization, Digital Transformation, IT Modernization, Information Security, Multi-Factor Authentication (MFA), Threat Intelligence, Data Protection, Encryption, Continuous Monitoring, Incident Response, Compliance, Secure Coding Practices

Menstrual Abnormalities Strongly Associated with Proximity to COVID-19 Vaccinated Individuals

In Spring 2021, MyCycleStorySM launched a secure online survey to which 92.3% of 6049 respondents self-reported menstrual irregularities occurring after the rollout of the COVID-19 injectables. Each respondent served as her own control because prior to the rollout of COVID-19 vaccination, the vast majority had regular menstrual cycles. A subgroup of 3390 respondents were only indirectly exposed to COVID-19 vaccines or the SARS-CoV-2 virus. This subgroup reported 1) being unvaccinated for COVID-19; 2) having had no COVID-19 symptoms; and 3) no positive test for COVID-19, yet a substantial majority of these women, who were only indirectly exposed to COVID-19 injectables or COVID-19 infections still had many of the same menstrual abnormalities as the 2659 women who were directly exposed to a COVID-19 injection (798), or had COVID-19 symptoms (1347), or tested positive for COVID-19 (514). Generalized linear mixed modeling was used to examine the association (not assuming causation) between abnormal menses experienced after the COVID-19 vaccine rollout by respondents who were only indirectly exposed by some degree of proximity to persons. Chi-Square, Student’s t, Kruskal-Wallis or ANOVA tests were used to assess the statistical significance of the similarities of menstrual irregularities reported by the directly exposed and indirectly exposed groups. The mean age of the entire cohort was 37.8 ± 0.1 years. The percentage of the indirectly exposed participants who reported being within 6 feet of a COVID-19 vaccinated person was 85.5%. Of these, 71.7% had irregular menstrual symptoms within one week and 50.1% had irregular menstrual symptoms within ≤3 days after exposure. When comparing daily proximity to a vaccinated person, the categories of “daily within 6 feet outside the household” versus “seldom/sometimes/daily outside 6 feet” had the highest relative risk at 1.34 (p&lt;0.01) for heavier menstrual bleeding, early menses at more than 7 days early with a relative risk at 1.28 (p=0.03), and extended bleeding for more than 7 days with relative risk at 1.26 (p=0.04). Indirect exposure to COVID-19 vaccinated persons was significantly associated with the likelihood of the onset of menstrual irregularities. This study provides additional data to complement a growing body of evidence raising concerns regarding the safety of mRNA vaccines.

Enhancing Email Security: A Real‐Time Machine Learning‐Based Spam Detection System

ABSTRACTSpam emails pose a persistent threat to online security and productivity. To combat this menace, we propose a robust machine learning‐based spam email detection system, leveraging algorithms like Naive Bayes, Support Vector Machine (SVM), and Random Forest (RF). Our system integrates Python's Natural Language Processing (NLP) library and cloud sourcing to achieve unparalleled accuracy and adaptability. Advanced feature extraction techniques, including Term Frequency‐Inverse Document Frequency (TF‐IDF) and N‐grams, enable comprehensive analysis of email content. Real‐time scanning and detection capabilities ensure immediate protection, while continuous learning allows the system to evolve and counter emerging spam tactics. Our system demonstrates exceptional performance, achieving accuracy rates of up to 97.58% with SVM. Comparative analysis of 11 machine learning algorithms reveals notable performance variations. By minimizing false positives and negatives, our system provides reliable protection against unwanted and harmful emails. This research contributes to the development of effective spam detection solutions, offering insights into optimal algorithms, time complexity‐accuracy trade‐offs, and scalable system design. Our system has significant implications for enhancing email security, safeguarding users from security breaches, and mitigating the economic impacts of spam.

Optimized Multi-Level Security for Content Contribution and Retrieval in Online Social Networks using a Content Visualization Mechanism

Online social networks have become an integral part of modern communication, providing platforms for users to share personal information, media, and opinions. However, these platforms face significant challenges in preserving user privacy while ensuring efficient data retrieval and maintaining data integrity. Existing privacy preservation methods, such as PPK-MEANS, CFCAF, and CLDPP, are limited in their ability to handle the growing complexity and scale of user data, often leading to inefficiencies such as high Content Retrieval Time (CRT), increased Information Loss (IL), and compromised data accuracy. These inefficiencies are crucial to address, as they can degrade the user experience by causing delays, compromising data integrity, and limiting system scalability. High CRT frustrates users, while increased IL reduces data accuracy, undermining trust and system reliability. The primary issue addressed in this study is the need for an advanced privacy-preserving mechanism that can provide multilevel security while maintaining optimal system performance. To overcome these limitations, the Layered Secure Online Collaborative Verification (LSOCV) algorithm is proposed, designed to offer a scalable solution with tiered privacy controls based on user requirements. LSOCV enhances Privacy Retrieval Accuracy (PRA), significantly reduces CRT, and minimizes IL. The experimental results show that LSOCV achieved a PRA of 91.97%, reduced CRT to 7ms, and decreased IL by up to 8% for 500KB files, outperforming existing approaches. This method provides robust privacy protection and efficient data handling on social networks, with the potential for future application in big data environments, such as Hadoop, to ensure scalable, secure, and efficient privacy-preserving solutions.

SRFACS: A secure and robust framework for anonymous communication systems.

Anonymous communication is crucial for preserving user privacy in various applications, such as anonymous browsing, secure online payments, and electronic voting. However, current systems face significant challenges related to robustness, fault tolerance, and efficient communication management. This paper introduces SRFACS (Secure and Robust Framework for Anonymous Communication Systems), designed to address these issues by integrating advanced cryptographic techniques with a structured communication framework. Traditional anonymous communication systems usually lack sufficient fault tolerance, making them vulnerable to node failures, especially in asynchronous environments. In order to overcome these limitations and ensure that the system can keep running in the event of node failure (especially in an asynchronous environment), SRFACS integrates an improved asynchronous Byzantine Fault Tolerant (ABFT) protocol. We use this protocol to expand the traditional single communication node into a structured node group, and handle up to (n - 1)/3 faulty nodes in these groups, so as to enhance fault tolerance and maintain continuous operation. To efficiently manage inter-group communication, SRFACS utilizes leader nodes to coordinate and streamline the communication processes. To mitigate the risks associated with leader failures, we have implemented an efficient leader change protocol that promptly replaces defective leaders, ensuring uninterrupted system performance. Additionally, to prevent erroneous leader actions from compromising the system, we have introduced an advanced multi-signature scheme. This approach secures communication by requiring multiple signatures for verification processes. Furthermore, we have implemented a reputation incentive mechanism to encourage nodes to maintain optimal performance and avoid malicious behavior. This mechanism evaluates nodes according to their past activities and reliability to achieve dynamic updates of SRFACS node groups. We have conducted rigorous security analyses and component performance evaluations of SRFACS, further confirming its potential as a promising secure communication solution.