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Journal articles on the topic 'Personally-Identifiable information protection'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Liu, Deliang. "The Protection of Personally Identifiable Information." SCRIPT-ed 4, no. 4 (2007): 389–406. http://dx.doi.org/10.2966/scrip.040407.389.

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2

Fugkeaw, Somchart, and Pattavee Sanchol. "Enabling Efficient Personally Identifiable Information Detection with Automatic Consent Discovery." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 17, no. 2 (2023): 245–54. http://dx.doi.org/10.37936/ecti-cit.2023172.252270.

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Personal data leakage prevention has now become a critical issue for implementing data management and sharing in many industries. Several data privacy regulations such as General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPPA), California Consumer Privacy Act (CCPA), and Thailand's Personal Data Protection Act (PDPA) have been issued to enforce organizations to collect, process, and transfer personally identifiable information (PII) securely. In this paper, we propose a design and development of PII RapidDiscover, an efficient Thai and English PII

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Mainetti, Luca, and Andrea Elia. "Detecting Personally Identifiable Information Through Natural Language Processing: A Step Forward." Applied System Innovation 8, no. 2 (2025): 55. https://doi.org/10.3390/asi8020055.

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The protection of personally identifiable information (PII) is being increasingly demanded by customers and governments via data protection regulations. Private and public organizations store and exchange through the Internet a large amount of data that include the personal information of users, employees, and customers. While discovering PII from a large unstructured text corpus is still challenging, a lot of research work has focused on identifying methods and tools for the detection of PII in real-time scenarios and the ability to discover data exfiltration attacks. In those research attemp

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Goutham, Bilakanti. "Secure Data Masking for Healthcare Data Protection." International Journal of Leading Research Publication 2, no. 6 (2021): 1–13. https://doi.org/10.5281/zenodo.15196759.

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The increasing use of cloud computing and artificial intelligence (AI) in the health care industry requires stringent security measures to keep patient information safe. In this paper, the use of data masking technology to secure Protected Health Information (PHI) and Personally Identifiable Information (PII) in a way that complies with regulatory requirements like HIPAA and GDPR is discussed. By using AWS Cloud services and AI-based anonymization, healthcare organizations can combat the threats of data breaches and unauthorized access. AI-based anonymization supports magnifying privacy throug

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Yang, Soyun. "Processing Health Information in Dental Records in the Context of Patient Data Privacy." Journal of The Korean Dental Association 62, no. 2 (2024): 76–93. http://dx.doi.org/10.22974/jkda.2024.62.2.001.

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This article aims to discuss the legal limitations in processing personally identifiable health information contained in dental records. Dental records usually contain images such as panoramic radiographs, from which the patient’s anatomical information on the oral and maxillofacial region can be recognized. Recent development in data processing technology sug-gests the possibility of enhanced chances of human identification from this information.To illustrate current privacy regulations related to the processing of information in dental records, relevant clauses in current laws including the

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Robinson, Robinson, and Blossom U. Idigbo. "A Digital Forensic Investigation of the Presence of Personally Identifiable Information (PII) in Refurbished Hard Drives." Journal of Cybersecurity and Information Management 15, no. 2 (2025): 244–59. https://doi.org/10.54216/jcim.150219.

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The last decade has seen a massive explosion of data, with a lot of Personally Identifiable Information (PII) flooding devices and the cyberspace. This has necessitated the growing call and global awareness for data protection, to ensure the responsible use of data, protect the privacy of data subjects, and prevent crimes such as identity theft and cybercrime. This paper investigated the presence of residual data and Personally Identifiable Information (PII) in refurbished hard drives bought from a retail shop. The study leveraged digital forensic tools to perform data recovery on refurbished

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Onik, Md Mehedi Hassan, Chul-Soo Kim, Nam-Yong Lee, and Jinhong Yang. "Privacy-aware blockchain for personal data sharing and tracking." Open Computer Science 9, no. 1 (2019): 80–91. http://dx.doi.org/10.1515/comp-2019-0005.

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AbstractSecure data distribution is critical for data accountability. Surveillance caused privacy breaching incidents have already questioned existing personal data collection techniques. Organizations assemble a huge amount of personally identifiable information (PII) for data-driven market analysis and prediction. However, the limitation of data tracking tools restricts the detection of exact data breaching points. Blockchain technology, an ‘immutable’ distributed ledger, can be leveraged to establish a transparent data auditing platform. However, Art. 42 and Art. 25 of general data protecti

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Posey, Clay, Uzma Raja, Robert E. Crossler, and A. J. Burns. "Taking stock of organisations’ protection of privacy: categorising and assessing threats to personally identifiable information in the USA." European Journal of Information Systems 26, no. 6 (2017): 585–604. http://dx.doi.org/10.1057/s41303-017-0065-y.

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9

Rubel, Md Tauhid Hossain, A. K. M. Emran, Razia Sultana Borna, Rony Saha, and Mahmudul Hasan. "Ai-Driven Big Data Transformation And Personally Identifiable Information Security In Financial Data: A Systematic Review." Non human journal 1, no. 01 (2024): 114–28. http://dx.doi.org/10.70008/jmldeds.v1i01.47.

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This systematic review explores the impact of adopting artificial intelligence (AI) to analyze and transform big data in financial and economic contexts, with a specific focus on the privacy and security of personally identifiable information (PII). By examining 37 articles spanning the latest advancements in AI-driven big data technologies, the review identifies both opportunities and challenges in safeguarding PII during financial data transformation. Key findings reveal that while AI enhances data processing capabilities—enabling faster insights and predictive accuracy in economic trends—PI

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Bomba, David, and George Hallit. "Will the new Australian Health Privacy Law provide adequate protection?" Australian Health Review 25, no. 3 (2002): 141. http://dx.doi.org/10.1071/ah020141a.

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Amendments to the original Privacy Act (1988) come at a key point in time, as a national medical record system looms on the Australian horizon. Changes to The Privacy Act have the potential to define a level of information privacy prior to the implementation of such a system. We have therefore collected expert opinions on the ability of the Health Privacy Guidelines(enacted in December 2001 under The Privacy Act and hereafter more specifically known as Health Privacy Legislation) to ensure the privacy and security of patient information. We conclude that the legislation is flawed in its capaci

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Mavridis, Ioannis. "Deploying Privacy Improved RBAC in Web Information Systems." International Journal of Information Technologies and Systems Approach 4, no. 2 (2011): 70–87. http://dx.doi.org/10.4018/jitsa.2011070105.

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Access control technology holds a central role in achieving trustworthy management of personally identifiable information in modern information systems. In this article, a privacy-sensitive model that extends Role-Based Access Control (RBAC) to provide privacy protection through fine-grained and just-in-time access control in Web information systems is proposed. Moreover, easy and effective mapping of corresponding components is recognized as an important factor for succeeding in matching security and privacy objectives. Such a process is proposed to be accomplished by capturing and modeling p

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Marri, Rahul, Sriram Varanasi, Satwik Varma Kalidindi Chaitanya, and Sai Krishna Marri. "Enhancing Security in Geographic Information Systems: Anonymization and Differential Privacy Techniques for Protecting Sensitive Geospatial Data." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 5, no. 1 (2024): 469–82. http://dx.doi.org/10.60087/jaigs.v5i1.240.

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As Geographic Information Systems (GIS) increasingly facilitate the analysis and sharing of geospatial data, the protection of sensitive information becomes paramount. This research explores the implementation of anonymization and differential privacy techniques to enhance security in GIS. Anonymization methods effectively remove or obscure personally identifiable information from geospatial datasets, while differential privacy introduces a mathematical framework that allows for the sharing of aggregate data without compromising individual privacy. This study evaluates the strengths and weakne

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Ellis, Donna A. "A case history in architectural acoustics: Security, acoustics, the protection of personally identifiable information (PII), and accessibility for the disabled." Journal of the Acoustical Society of America 136, no. 4 (2014): 2182. http://dx.doi.org/10.1121/1.4899907.

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14

Cruz, Bruno Silveira, and Murillo de Oliveira Dias. "Does digital privacy really exist? When the consumer is the product." Asian Journal of Economics and Business Management 1, no. 1 (2022): 39–43. http://dx.doi.org/10.53402/ajebm.v1i1.53.

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In 2015, the scandal on Facebook and Cambridge Analytica Ltd, a British political consulting firm - subsidiary of the SCL Group, shook the international public opinion on digital privacy. The subject has attracted scholarly attention, after 87 million mostly Facebook users worldwide, had their personal information under suspicion of data misappropriation, for political influence. In spite of the Cambridge Analytica investigations conducted, a puzzling question remains: does digital privacy really exist? This article investigated the event and the role of the companies involved. Key findings po

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Huang, Weiwang, and Ming Hsun Hsieh. "The application of artificial intelligence and machine learning in civil law protection of privacy rights." Edelweiss Applied Science and Technology 9, no. 1 (2025): 564–94. https://doi.org/10.55214/25768484.v9i1.4184.

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Machine learning has emerged as a core technology in domains such as big data, the Internet of Things (IoT), and cloud computing. The training of machine learning models typically requires extensive datasets, often gathered through crowdsourcing methods. These datasets frequently contain significant amounts of private information, including personally identifiable information (e.g., phone numbers, identification numbers) and sensitive data (e.g., financial, medical, and health records). The efficient and cost-effective protection of such data represents a pressing challenge. This article intro

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Olabanji, Samuel Oladiipo, Oluseun Babatunde Oladoyinbo, Christopher Uzoma Asonze, Tunbosun Oyewale Oladoyinbo, Samson Abidemi Ajayi, and Oluwaseun Oladeji Olaniyi. "Effect of Adopting AI to Explore Big Data on Personally Identifiable Information (PII) for Financial and Economic Data Transformation." Asian Journal of Economics, Business and Accounting 24, no. 4 (2024): 106–25. http://dx.doi.org/10.9734/ajeba/2024/v24i41268.

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The integration of Artificial Intelligence (AI) into big data analytics represents a pivotal shift in the management of Personally Identifiable Information (PII) within the financial sector. This study was prompted by the increasing reliance on AI for handling sensitive financial data and the consequent rise in data security concerns, exemplified by the 2019 Capital One data breach which compromised the PII of over 100 million individuals, highlighting the vulnerabilities inherent in digital data storage and management systems. Aiming to critically evaluate the effects of adopting AI in explor

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Georgiadou, Yola, Rolf de By, and Ourania Kounadi. "Location Privacy in the Wake of the GDPR." ISPRS International Journal of Geo-Information 8, no. 3 (2019): 157. http://dx.doi.org/10.3390/ijgi8030157.

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The General Data Protection Regulation (GDPR) protects the personal data of natural persons and at the same time allows the free movement of such data within the European Union (EU). Hailed as majestic by admirers and dismissed as protectionist by critics, the Regulation is expected to have a profound impact around the world, including in the African Union (AU). For European–African consortia conducting research that may affect the privacy of African citizens, the question is `how to protect personal data of data subjects while at the same time ensuring a just distribution of the benefits of a

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N, Prabu Sankar, and D.Usha. "A REVIEW ON BIG DATA PRIVACY AND SECURITY IN HEALTH CARE." International Journal of Engineering Research and Sustainable Technologies (IJERST) 1, no. 1 (2023): 38–49. https://doi.org/10.63458/ijerst.v1i1.61.

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Due to the proliferation of the Internet, IoT, and Cloud Computing, there is now an abundance of virtual data in every industry, field of study, and government agency. Big data has quickly become a topic of intense interest, garnering media coverage and commentary from all over the world. Data privacy and security in Big Data is a pressing concern. The 5Vs of big data—size, velocity, value, veracity, and variety—lower the bar for adequate protection. This paper aimed to draw attention to security and privacy issues and challenges associated with Big Data in healthcare, the resolution of which

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Ukwueze, Festus. "Strengthening the Legal Framework for Personal Data Protection in Nigeria." Nigerian Juridical Review 16 (June 28, 2022): 124–42. http://dx.doi.org/10.56284/tnjr.v16i1.16.

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Advancement in Information Communication Technology (ICT) has brought to the fore the need for the protection of individuals’ personal data. In today’s digital age, the personal data of individuals are routinely collected and stored in databases of both private and public establishments. Such personally identifiable information can easily be analyzed with fascinating accuracy, rapidly transmitted, and put to unimaginable uses. This situation has placed the regulation of personal data collection and uses on the front burner in many nations. The weak or total absence of regulation of personal da

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20

Han, Yiping, and Xinqian Lu. "Is Data Anonymization an Effective Way to Protect Privacy or Not." International Journal of Computer Science and Information Technology 4, no. 3 (2024): 152–56. https://doi.org/10.62051/ijcsit.v4n3.15.

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This paper examines whether data anonymization is an effective method for protecting personal privacy. With the rapid development of the Internet and artificial intelligence, data has become a key driver of modern societal development, but it also raises ethical and technological challenges regarding privacy protection. Data anonymization protects sensitive data by encrypting it and removing personally identifiable information, aiming to reduce the likelihood of identifying individuals within a dataset. The article analyzes the benefits of data anonymization, including the protection of person

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Nihari Paladugu. "Privacy-Aware Graph Embeddings for Anti-Money Laundering Pipelines." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1223–31. https://doi.org/10.30574/wjaets.2025.15.3.0995.

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This article introduces a novel approach to anti-money laundering (AML) that combines graph neural networks (GNNs) with homomorphic encryption (HE) to detect suspicious financial patterns while preserving personally identifiable information (PII). Current AML systems face significant challenges in cross-border financial networks due to privacy regulations and data protection concerns. The proposed architecture enables financial institutions to analyze encrypted transaction graphs using privacy-preserving GNN inference, generating intermediate embeddings that retain predictive value without exp

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22

Villarán, Carlos, and Marta Beltrán. "User-Centric Privacy for Identity Federations Based on a Recommendation System." Electronics 11, no. 8 (2022): 1238. http://dx.doi.org/10.3390/electronics11081238.

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Specifications such as SAML, OAuth, OpenID Connect and Mobile Connect are essential for solving identification, authentication and authorisation in contexts such as mobile apps, social networks, e-commerce, cloud computing or the Internet of Things. However, end-users relying on identity providers to access resources, applications or services lose control over the Personally Identifiable Information (PII) they share with the different providers composing identity federations. This work proposes a user-centric approach based on a recommendation system to support users in making privacy decision

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Thetbanthad, Parinya, Benjaporn Sathanarugsawait, and Prasong Praneetpolgrang. "Automated Redaction of Personally Identifiable Information on Drug Labels Using Optical Character Recognition and Large Language Models for Compliance with Thailand’s Personal Data Protection Act." Applied Sciences 15, no. 9 (2025): 4923. https://doi.org/10.3390/app15094923.

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The rapid proliferation of artificial intelligence (AI) across various industries presents both opportunities and challenges, particularly concerning personal data privacy. With the enforcement of regulations like Thailand’s Personal Data Protection Act (PDPA), organizations face increasing pressure to protect sensitive information found in diverse data sources, including product and shipping labels. These labels, often processed by AI systems for logistics and inventory management, frequently contain Personally Identifiable Information (PII). This paper introduces a novel AI-driven system for

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Mićović, Marko, Uroš Radenković, and Pavle Vuletić. "Network Layer Privacy Protection Using Format-Preserving Encryption." Electronics 12, no. 23 (2023): 4800. http://dx.doi.org/10.3390/electronics12234800.

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Format-Preserving Encryption (FPE) algorithms are symmetric cryptographic algorithms that encrypt an arbitrary-length plaintext into a ciphertext of the same size. Standardisation bodies recognised the first FPE algorithms (FEA-1, FEA-2, FF1 and FF3-1) in the last decade, and they have not been used for network layer privacy protection so far. However, their ability to encrypt arbitrary-length plaintext makes them suitable for encrypting selected packet header fields and replacing their original value with ciphertext of the same size without storing excessive information on the network element

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Rashid, Husain, Komakula Manoj, Khan Rabia, and Tyagi Rajesh. "Healthcare institutions security posture: An open-source security architecture practical implementation." i-manager's Journal on Digital Forensics & Cyber Security 3, no. 1 (2025): 26. https://doi.org/10.26634/jdf.3.1.21552.

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The healthcare industry is a critical sector that demands robust cybersecurity measures to protect sensitive data and infrastructure. With the rapid evolution of cyber threats, attack vectors, and adversarial strategies, organizations and governments face significant challenges in ensuring data security. While extensive research exists on cybersecurity threats, breaches, and the efficacy of open-source security tools, their practical implementation in real-world healthcare settings particularly where financial constraints exist remain underexplored. This study proposes an Open Security Operati

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Vasudevan, Asokan. "Cyber Security: A Customer Perspective on Emerging Technologies." International Journal of Management and Marketing Intelligence 1, no. 4 (2024): 1–7. https://doi.org/10.64251/ijmmi.62.

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Cybersecurity is important since it prevents both theft and damage to several types of information. This comprises delicate information, personally identifiable details, Personal Health Information (PHI), personal data, information related to property rights, and data management used by the government and industry. In the recent years, the cybersecurity has become significant trouble in business sectors worldwide that depend on digitization and faster transactions. Many devices are internet-connected, requiring security precautions to secure them from cyber-attacks. Moreover, the individuals w

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Adebola Folorunso, Viqaruddin Mohammed, Ifeoluwa Wada, and Bunmi Samuel. "The impact of ISO security standards on enhancing cybersecurity posture in organizations." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2582–95. http://dx.doi.org/10.30574/wjarr.2024.24.1.3169.

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The increasing frequency and sophistication of cyber threats have made organizations need to adopt robust cybersecurity frameworks. ISO security standards, particularly the ISO/IEC 27000 series, play a critical role in enhancing organizations' cybersecurity posture worldwide. These standards provide a systematic approach to managing sensitive information, ensuring its confidentiality, integrity, and availability. ISO/IEC 27001, which focuses on establishing an Information Security Management System (ISMS), is widely recognized for its ability to help organizations identify, manage, and mitigat

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Koo, Jahoon, Giluk Kang, and Young-Gab Kim. "Security and Privacy in Big Data Life Cycle: A Survey and Open Challenges." Sustainability 12, no. 24 (2020): 10571. http://dx.doi.org/10.3390/su122410571.

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The use of big data in various fields has led to a rapid increase in a wide variety of data resources, and various data analysis technologies such as standardized data mining and statistical analysis techniques are accelerating the continuous expansion of the big data market. An important characteristic of big data is that data from various sources have life cycles from collection to destruction, and new information can be derived through analysis, combination, and utilization. However, each phase of the life cycle presents data security and reliability issues, making the protection of persona

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Mokale, Mahesh. "Data Anonymization Techniques for Enhanced User Privacy in Telecommunications." International Journal of Multidisciplinary Research and Growth Evaluation. 5, no. 2 (2024): 1017–22. https://doi.org/10.54660/.ijmrge.2024.5.2.1017-1022.

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In the rapidly evolving telecommunications industry, safeguarding user privacy has become paramount. The increasing reliance on data-driven technologies has led to the collection and storage of vast amounts of user information, including call records, location data, and internet usage patterns. Telecommunications companies leverage this data to optimize network performance, enhance customer experiences, and develop innovative services. However, the widespread availability of personal data also raises serious concerns about privacy breaches, unauthorized data access, and potential misuse by mal

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Adebola, Folorunso, Mohammed Viqaruddin, Wada Ifeoluwa, and Samuel Bunmi. "The impact of ISO security standards on enhancing cybersecurity posture in organizations." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2582–95. https://doi.org/10.5281/zenodo.15063305.

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The increasing frequency and sophistication of cyber threats have made organizations need to adopt robust cybersecurity frameworks. ISO security standards, particularly the ISO/IEC 27000 series, play a critical role in enhancing organizations' cybersecurity posture worldwide. These standards provide a systematic approach to managing sensitive information, ensuring its confidentiality, integrity, and availability. ISO/IEC 27001, which focuses on establishing an Information Security Management System (ISMS), is widely recognized for its ability to help organizations identify, manage, and mitigat

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Varun, Chivukula. "Use of Federated Learning for Optimizing Ad Delivery Platforms without Exchanging User PII." International Journal on Science and Technology 13, no. 3 (2022): 1–5. https://doi.org/10.5281/zenodo.14613805.

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The ever-expanding digital advertising ecosystem relies heavily on advanced machine learning (ML) models to predict user behavior, personalize content, and optimize ad delivery. However, traditional centralized ML workflows that aggregate and process large amounts of Personally Identifiable Information (PII) are increasingly incompatible with growing regulatory constraints such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Federated Learning (FL) provides a revolutionary approach by enabling decentralized model training across distributed data

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Aghili, Roozbeh, Heng Li, and Foutse Khomh. "Protecting Privacy in Software Logs: What Should Be Anonymized?" Proceedings of the ACM on Software Engineering 2, FSE (2025): 1317–38. https://doi.org/10.1145/3715779.

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Software logs, generated during the runtime of software systems, are essential for various development and analysis activities, such as anomaly detection and failure diagnosis. However, the presence of sensitive information in these logs poses significant privacy concerns, particularly regarding Personally Identifiable Information (PII) and quasi-identifiers that could lead to re-identification risks. While general data privacy has been extensively studied, the specific domain of privacy in software logs remains underexplored, with inconsistent definitions of sensitivity and a lack of standard

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Burhanuddin, M. A. "Assessing the Vulnerability of Quantum Cryptography Systems to Emerging Cyber Threats." SHIFRA 2023 (April 1, 2023): 26–33. http://dx.doi.org/10.70470/shifra/2023/004.

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Using quantum mechanical thinking, quantum cryptography provides security that has never been possible in communications. Even when transferred or stored in quantum secure environments, sensitive data processed by systems including names, credit card information, and email addresses desperately needs privacy and security protection ban The problem is not only to protect quantum communication from themselves, but any private data that can be so transferred between these devices It is also to protect. This work addresses the issue of effectively anonymizing sensitive data in quantum cryptographi

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Shaikh, Owais. "Detection and Classification of Personally Identifiable Information in Images Using Artificial Intelligence." Journal of Current Trends in Computer Science Research 3, no. 4 (2024): 01–04. http://dx.doi.org/10.33140/jctcsr.03.04.05.

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Personally, Identifiable Information (PII) is any content that is sensitive that needs to be treated as secure and private. When data pieces such as a person's name, address, Social Security number, phone number, email address, and so on may be used to identify a specific individual, they are deemed PII. As organizations grow, so does their volume of data. This makes identifying and protecting such sensitive resources at a scale quite complex. In this project, we demonstrate where and how PII can be discovered and how we developed a working prototype of a tool that can easily detect PII images

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Vishwasrao Salunkhe, Abhishek Tangudu, Chandrasekhara Mokkapati, Prof.(Dr.) Punit Goel, and Anshika Aggarwal. "Advanced Encryption Techniques in Healthcare IoT: Securing Patient Data in Connected Medical Devices." Modern Dynamics: Mathematical Progressions 1, no. 2 (2024): 224–47. http://dx.doi.org/10.36676/mdmp.v1.i2.22.

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As a result of the fast development of Internet of Things (IoT) technology, the healthcare sector has undergone a transformation. This transformation has been brought about by the deployment of linked medical devices that provide immediate monitoring and data collecting. Despite the fact that these innovations promise to bring about considerable gains in patient care and operational efficiency, they also bring about major security issues, especially with regard to the protection of personally identifiable information about patients. Within the context of the Internet of Things (IoT) ecosystem

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Naidu, Adarsh. "Synthetic Data Generation for Privacy Preservation in Financial Technologies." International Journal of Multidisciplinary Research and Growth Evaluation 1, no. 1 (2020): 139–42. https://doi.org/10.54660/.ijmrge.2020.1.1.139-142.

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This research examines the utilization of Generative Adversarial Networks (GANs) to produce synthetic financial data that ensures privacy while adhering to stringent regulatory frameworks, such as the General Data Protection Regulation (GDPR) (European Union, 2016) [4] and the California Consumer Privacy Act (CCPA). Financial institutions handle extensive sensitive data, necessitating stringent privacy safeguards. Conventional anonymization techniques frequently reduce data utility, thereby limiting their effectiveness for machine learning, research, and analysis. Conversely, GANs offer an inn

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Naidu, Adarsh. "Synthetic Data Generation for Privacy Preservation in Financial Technologies." International Journal of Multidisciplinary Research and Growth Evaluation 1, no. 2 (2020): 64–67. https://doi.org/10.54660/.ijmrge.2020.1.2.64-67.

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This research examines the utilization of Generative Adversarial Networks (GANs) to produce synthetic financial data that ensures privacy while adhering to stringent regulatory frameworks, such as the General Data Protection Regulation (GDPR) (European Union, 2016) [4] and the California Consumer Privacy Act (CCPA). Financial institutions handle extensive sensitive data, necessitating stringent privacy safeguards. Conventional anonymization techniques frequently reduce data utility, thereby limiting their effectiveness for machine learning, research, and analysis. Conversely, GANs offer an inn

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Lu, Hengtong, Yan Zhang, Qingfeng Tang, and Pengwei Zhan. "Uncovering the App Cloud Access Risks under Recommended IAM Security Practices." Proceedings on Privacy Enhancing Technologies 2025, no. 4 (2025): 763–76. https://doi.org/10.56553/popets-2025-0156.

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The rapid development of mobile applications and cloud computing has led to the widespread adoption of cloud service platforms for mobile backend services. However, improper use of cloud credentials has frequently resulted in the leakage of application data on cloud servers. Despite security recommendations from cloud service providers, vulnerabilities persist. To assess the effectiveness of these measures, we propose a detection system to identify cloud credential leaks in mobile applications, including hard-coded credentials and those stored on servers. We analyzed 21,724 applications from G

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Fiaz, Faisal, Syed Muhammad Sajjad, Zafar Iqbal, Muhammad Yousaf, and Zia Muhammad. "MetaSSI: A Framework for Personal Data Protection, Enhanced Cybersecurity and Privacy in Metaverse Virtual Reality Platforms." Future Internet 16, no. 5 (2024): 176. http://dx.doi.org/10.3390/fi16050176.

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The Metaverse brings together components of parallel processing computing platforms, the digital development of physical systems, cutting-edge machine learning, and virtual identity to uncover a fully digitalized environment with equal properties to the real world. It possesses more rigorous requirements for connection, including safe access and data privacy, which are necessary with the advent of Metaverse technology. Traditional, centralized, and network-centered solutions fail to provide a resilient identity management solution. There are multifaceted security and privacy issues that hinder

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Oluwatoyin Ajoke Fayayola, Oluwabukunmi Latifat Olorunfemi, and Philip Olaseni Shoetan. "DATA PRIVACY AND SECURITY IN IT: A REVIEW OF TECHNIQUES AND CHALLENGES." Computer Science & IT Research Journal 5, no. 3 (2024): 606–15. http://dx.doi.org/10.51594/csitrj.v5i3.909.

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In today's interconnected digital world, data privacy and security have emerged as paramount concerns for individuals, organizations, and governments alike. This review provides a comprehensive review of techniques and challenges surrounding data privacy and security in information technology (IT) systems. The review begins by outlining the significance of data privacy and security in IT, emphasizing the proliferation of sensitive information stored and transmitted across various digital platforms. With the exponential growth of data collection, storage, and processing, ensuring the confidenti

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Amama, Ushang Desmond, Faizolla Talgatuly, Ayinoluwa F. Kolawole, and Onakoya Oluwatobi. "Data Engineering and Privacy Challenges in Loyalty Card Programs: Insights from Retail, Banking, and Hospitality." Asian Journal of Advanced Research and Reports 18, no. 11 (2024): 340–57. http://dx.doi.org/10.9734/ajarr/2024/v18i11800.

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This paper explores the data engineering practices surrounding loyalty card programs in the retail, banking, travel, and hospitality industries. It examines how businesses use personal and transactional data to enhance customer retention and gain competitive advantages. The research highlights industry-specific practices, regulatory frameworks (such as GDPR and CCPA), and the security measures adopted to protect Personally Identifiable Information (PII). Key insights into how data is leveraged for targeted marketing and the persistent vulnerabilities in data protection systems are also discuss

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Kelly, Miriam, Eoghan Furey, and Kevin Curran. "How to Achieve Compliance with GDPR Article 17 in a Hybrid Cloud Environment." Sci 2, no. 2 (2020): 22. http://dx.doi.org/10.3390/sci2020022.

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On 25 May 2018, the General Data Protection Regulation (GDPR)Article 17, the Right to Erasure (‘Right to be Forgotten’) came into force making it vital for organisations to identify, locate and delete all Personally Identifiable Information (PII) where a valid request is received from a data subject to erase their PII and the contractual period has expired. This must be done without undue delay and the organisation must be able to demonstrate reasonable measures were taken. Failure to comply may incur significant fines, not to mention impact to reputation. Many organisations do not understand

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Kelly, Miriam, Eoghan Furey, and Kevin Curran. "How to Achieve Compliance with GDPR Article 17 in a Hybrid Cloud Environment." Sci 3, no. 1 (2021): 3. http://dx.doi.org/10.3390/sci3010003.

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On 25 May 2018, the General Data Protection Regulation (GDPR) Article 17, the Right to Erasure (“Right to be Forgotten”) came into force, making it vital for organisations to identify, locate and delete all Personally Identifiable Information (PII) where a valid request is received from a data subject to erase their PII and the contractual period has expired. This must be done without undue delay and the organisation must be able to demonstrate that reasonable measures were taken. Failure to comply may incur significant fines, not to mention impact to reputation. Many organisations do not unde

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Reyes, Irwin, Primal Wijesekera, Joel Reardon, et al. "“Won’t Somebody Think of the Children?” Examining COPPA Compliance at Scale." Proceedings on Privacy Enhancing Technologies 2018, no. 3 (2018): 63–83. http://dx.doi.org/10.1515/popets-2018-0021.

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Abstract We present a scalable dynamic analysis framework that allows for the automatic evaluation of the privacy behaviors of Android apps. We use our system to analyze mobile apps’ compliance with the Children’s Online Privacy Protection Act (COPPA), one of the few stringent privacy laws in the U.S. Based on our automated analysis of 5,855 of the most popular free children’s apps, we found that a majority are potentially in violation of COPPA, mainly due to their use of thirdparty SDKs. While many of these SDKs offer configuration options to respect COPPA by disabling tracking and behavioral

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Sun, Yuanyi, Sencun Zhu, and Yu Chen. "ZoomP3: Privacy-Preserving Publishing of Online Video Conference Recordings." Proceedings on Privacy Enhancing Technologies 2022, no. 3 (2022): 630–49. http://dx.doi.org/10.56553/popets-2022-0089.

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The COVID-19 epidemic has made online video conferencing extremely popular throughout the world, with many schools, companies and government sectors using video conferencing applications (e.g., Zoom, Google Meet) in a daily basis. These applications also provide local or cloud recording services, which allow the replay or sharing of video conference recordings (VCRs) in a later time. Such convenience, however, can easily cause infringement of privacy as meeting participants’ personally identifiable information (e.g., face, name, voice) may be exposed to the public without their awareness or co

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Shakor, Ali M. "When Wireless Technologies Faces COVID-19: via Apps using to Combat the Pandemic and Save the Economy." Tikrit Journal of Engineering Sciences 29, no. 2 (2022): 41–50. http://dx.doi.org/10.25130/tjes.29.2.6.

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As the number of smartphone users grows, the smartphone's function in healthcare has evolved from a device that is used to arrange doctor appointments via the internet rather than the traditional approach. Mobile apps are a convenient way to track and collect data in order to combat the spread of COVID-19. To ensure that the right to privacy and civil liberties are maintained, we report on our investigation of 50 COVID -19- related apps, including their access to and use of personally identifiable information. Reservations are made at the doctor over the Internet, and an appointment is arrange

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Konka Kishan. "Medical Data Security using Deep Learning based Key Generation, Quantum Key Exchange and Modified AES." Journal of Information Systems Engineering and Management 10, no. 4s (2025): 353–64. https://doi.org/10.52783/jisem.v10i4s.528.

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Medical data security refers to the protection and safeguarding of sensitive patient data in the healthcare domain. It encompasses various measures and protocols designed to ensure the confidentiality, integrity, and availability of medical information. This includes not only medical imaging data but also electronic health records (EHRs), medical test results, patient demographics, and other personally identifiable information (PII). Medical data security is of utmost importance due to several reasons like patient privacy, preventing unauthorized access or disclosure of personal health informa

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Gorokhova, Tetiana, and Maksym Lazarenko. "Human rights in the era of digital economy development: prospects and challenges." REPORTER OF THE PRIAZOVSKYI STATE TECHNICAL UNIVERSITY Section: Economic sciences, no. 1(38) (May 25, 2023): 69–74. http://dx.doi.org/10.31498/2225-6725.1(38).2023.281116.

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With the emergence and rapid development of the digital economy, new challenges to the protection of human rights arise. Digital technologies, artificial intelligence, big data, and other innovations offer many opportunities for the development of society, but they also threaten fundamental human rights and freedoms. One of the biggest challenges is the collection and processing of personal data. In the digital economy, large amounts of personally identifiable information are stored and used by companies and governments. Organisations and governments are making efforts to improve cybersecurity

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SANDEEP PAMARTHI. "AI Meets Anonymity: How named entity recognition is redefining data privacy." World Journal of Advanced Research and Reviews 22, no. 1 (2024): 2045–53. https://doi.org/10.30574/wjarr.2024.22.1.1270.

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In the era of exponential data growth, individuals and organizations increasingly grapple with the tension between extracting value from data and preserving the privacy of individuals represented within it. From customer reviews and support logs to medical records and financial statements, personal information permeates virtually every dataset. Data anonymization—the process of removing or obfuscating personally identifiable information (PII)—has emerged as a critical response to this challenge. Historically, anonymization was a straightforward process: remove names, mask identifiers, and repl

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Yamcharoen, P., O. S. Folorunsho, A. Bayewu, and T. P. Ojo. "Impact of Digitalizing Healthcare Business Operations on Cybersecurity Landscape." Advances in Multidisciplinary and scientific Research Journal Publication 8, no. 4 (2022): 27–34. http://dx.doi.org/10.22624/aims/bhi/v8n4p3.

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The technological evolution and digitalization of business operations contributed to healthcare organizations' constantly changing cybersecurity landscape. It is compulsory and mandated by the covered entities to fully comply with the industry regulatory standards, procedures, laws, and guidelines. The compliance officer must pay attention to the change in the business operations and the laws governing the organization's business operation. Developing an automated cybersecurity team that will track the change in the cybersecurity landscape of healthcare businesses as the business operations mo

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