Personally Identifiable Information Research Articles

Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation.

BackgroundAs one of the several effective solutions for personal privacy protection, a global unique identifier (GUID) is linked with hash codes that are generated from combinations of personally identifiable information (PII) by a one-way hash algorithm. On the GUID server, no PII is permitted to be stored, and only GUID and hash codes are allowed. The quality of PII entry is critical to the GUID system.ObjectiveThe goal of our study was to explore a method of checking questionable entry of PII in this context without using or sending any portion of PII while registering a subject.MethodsAccording to the principle of GUID system, all possible combination patterns of PII fields were analyzed and used to generate hash codes, which were stored on the GUID server. Based on the matching rules of the GUID system, an error-checking algorithm was developed using set theory to check PII entry errors. We selected 200,000 simulated individuals with randomly-planted errors to evaluate the proposed algorithm. These errors were placed in the required PII fields or optional PII fields. The performance of the proposed algorithm was also tested in the registering system of study subjects.ResultsThere are 127,700 error-planted subjects, of which 114,464 (89.64%) can still be identified as the previous one and remaining 13,236 (10.36%, 13,236/127,700) are discriminated as new subjects. As expected, 100% of nonidentified subjects had errors within the required PII fields. The possibility that a subject is identified is related to the count and the type of incorrect PII field. For all identified subjects, their errors can be found by the proposed algorithm. The scope of questionable PII fields is also associated with the count and the type of the incorrect PII field. The best situation is to precisely find the exact incorrect PII fields, and the worst situation is to shrink the questionable scope only to a set of 13 PII fields. In the application, the proposed algorithm can give a hint of questionable PII entry and perform as an effective tool.ConclusionsThe GUID system has high error tolerance and may correctly identify and associate a subject even with few PII field errors. Correct data entry, especially required PII fields, is critical to avoiding false splits. In the context of one-way hash transformation, the questionable input of PII may be identified by applying set theory operators based on the hash codes. The count and the type of incorrect PII fields play an important role in identifying a subject and locating questionable PII fields.

Behind Enemy Lines

A client of a security services firm has received an email from the dark web demanding a ransom or it will start selling data it has stolen from the client. The client as asked for the firm’s assistance in paying the ransom. How should the company proceed? It was late on a Friday afternoon. The ReliaQuest Security Operations Center was busy as usual, but nothing was out of the ordinary. ReliaQuest Chief Technology Officer, Joe Partlow, was in his office working on a new technology innovation when his cell phone rang. It was the Chief Information Security Officer (CISO) for ABC Company, one of ReliaQuest’s clients–a company with millions of customers across the United States. ABC Company’s CISO had a crisis on his hands. He had just gotten word from his public relations staff that a journalist had called asking for a comment about a supposed leak of millions of customer records containing personally identifiable information (PTT) that could potentially be used to steal identities. Apparently, the data was listed “for sale” on the “dark web” portion of the Internet by an anonymous hacker. The CISO wanted ReliaQuest’s help figuring out whether the data had, in fact, been stolen. If so, who stole it, and how? And what could be done now to re-procure the data lost? The journalist had given the company a 24-hour window before he said he would post a story. There was also the question of whether the supposed data leak was legitimate at all. ABC Company’s security team had not been able to verify that any of their systems had been breached, and there seemed to be no way to inspect the supposed stolen data without purchasing it from the anonymous hacker–something the company was not comfortable doing on its own. The situation was urgent. The prospect of alleged customer data floating around the dark web was deeply troubling to the CISO and to Joe, yet he knew that finding the underlying cause of the situation could require members of the ReliaQuest team to use tactics outside the scope of work formally agreed upon by ReliaQuest and ABC Company. Joe also knew that if the breach was real, any tactics to identify and secure the data that ReliaQuest used could be subject to discovery in a criminal case. Moreover, Joe worried that if the breach was real and had somehow happened while under ReliaQuest’s watch, the incident could create a public relations crisis not only for ABC Company, but also for ReliaQuest. Joe was at a high stakes crossroad for making a decision and time was of the essence. ReliaQuest prided itself on team members’ willingness to do whatever it took to make security possible for customers. Nonetheless, Joe needed to decide: How far should ReliaQuest go to verify the breach? How would they find the underlying cause of the breach? How would they recover stolen data? And who should he consult with both within and outside of ReliaQuest to solve the problem while protecting stakeholders?

ReliaQuest: Behind Enemy Lines

It was late on a Friday afternoon. The ReliaQuest Security Operations Center was busy as usual, but nothing was out of the ordinary. ReliaQuest Chief Technology Officer, Joe Partlow, was in his office working on a new technology innovation when his cell phone rang. It was the Chief Information Security Officer (CISO) for ABC Company, one of ReliaQuest’s clients–a company with millions of customers across the United States. ABC Company’s CISO had a crisis on his hands. He had just gotten word from his public relations staff that a journalist had called asking for a comment about a supposed leak of millions of customer records containing personally identifiable information (PTT) that could potentially be used to steal identities. Apparently, the data was listed “for sale” on the “dark web” portion of the Internet by an anonymous hacker. The CISO wanted ReliaQuest’s help figuring out whether the data had, in fact, been stolen. If so, who stole it, and how? And what could be done now to re-procure the data lost? The journalist had given the company a 24-hour window before he said he would post a story. There was also the question of whether the supposed data leak was legitimate at all. ABC Company’s security team had not been able to verify that any of their systems had been breached, and there seemed to be no way to inspect the supposed stolen data without purchasing it from the anonymous hacker–something the company was not comfortable doing on its own. The situation was urgent. The prospect of alleged customer data floating around the dark web was deeply troubling to the CISO and to Joe, yet he knew that finding the underlying cause of the situation could require members of the ReliaQuest team to use tactics outside the scope of work formally agreed upon by ReliaQuest and ABC Company. Joe also knew that if the breach was real, any tactics to identify and secure the data that ReliaQuest used could be subject to discovery in a criminal case. Moreover, Joe worried that if the breach was real and had somehow happened while under ReliaQuest’s watch, the incident could create a public relations crisis not only for ABC Company, but also for ReliaQuest. Joe was at a high stakes crossroad for making a decision and time was of the essence. ReliaQuest prided itself on team members’ willingness to do whatever it took to make security possible for customers. Nonetheless, Joe needed to decide: How far should ReliaQuest go to verify the breach? How would they find the underlying cause of the breach? How would they recover stolen data? And who should he consult with both within and outside of ReliaQuest to solve the problem while protecting stakeholders?

Privacy Protection of Tagged Multimedia Content in Online Social Networks

Tagging services in online social networks (OSNs) allow users to connect online resources based on their characteristics in addition to their uniform resource locators (URLs). The semantic interoperability creates authorisation conflicts when accessing the tagged shared content; as a result, privacy requirements cannot be fully satisfied. In this paper, we investigate the privacy implications of unauthorised audience discrepancies in tagged multimedia content that are due to the different privacy restrictions that users apply to their personal identifiable information (PII). By examining all the possible visibility combinations in a two-level social relationship scale for different anonymised real user profiles, according to the offered choices that are provided by the privacy mechanisms in OSNs, we identified the cases where there exist audience discrepancies that can cause privacy breaches. Our findings indicate that the current privacy mechanisms of OSN users' tagged multimedia content are insufficient, as they cannot fully match the users' privacy intentions.

Design of Mutually Authenticated Key Agreement Protocol Resistant to Impersonation Attacks for Multi-Server Environment

Three-factor mutually authenticated key agreement protocols for multi-server environments have gained momentum in recent times due to advancements in wireless technologies and associated constraints. Several authors have put forward various authentication protocols for multi-server environment during the past decade. Wang et al. recently proposed a biometric-based authentication with key agreement protocol for multi-server environment and claimed that their protocol is efficient and resistant to prominent security attacks. The careful investigation of this paper shows that Wang et al. protocol’s users are sharing personal identifiable information with the application servers during the registration and authentication process. This nature of disclosing credentials leads to severe threats particularly insider attacks, user impersonation attacks, and server impersonation attacks. As a remedy of the aforementioned problems, this paper proposes a novel biometric-based mutually authenticated key agreement protocols for multi-server architecture based on elliptic curve cryptography. We prove that the proposed protocol achieves secure mutual authentication property using the broadly used Burrows–Abadi–Needham logic. The formal security of the proposed protocol is verified using the widely accepted automated validation of Internet security protocols and applications tool to show that our protocol can withstand active and passive attacks including the replay and man-in-the-middle attacks. The proposed protocol is robust and efficient compared with the existing related protocols.

Forensic Taxonomy of Android Social Apps.

An Android social app taxonomy incorporating artifacts that are of forensic interest will enable users and forensic investigators to identify the personally identifiable information (PII) stored by the apps. In this study, 30 popular Android social apps were examined. Artifacts of forensic interest (e.g., contacts lists, chronology of messages, and timestamp of an added contact) were recovered. In addition, images were located, and Facebook token strings used to tie account identities and gain access to information entered into Facebook by a user were identified. Based on the findings, a two-dimensional taxonomy of the forensic artifacts of the social apps is proposed. A comparative summary of existing forensic taxonomies of different categories of Android apps, designed to facilitate timely collection and analysis of evidentiary materials from Android devices, is presented.

Privacy Preserved Data Publishing Techniques for Tabular Data

Almost all countries have imposed strict laws on the disclosure of Personally Identifiable Information(PII). However PII need to be published for many purposes like research. In such cases, we apply different types of methods like anonymization, encryption etc. This paper discuss about the different methods of anonymization of tabular microdata. The most popular method of data anonymization of tabular data is k-anonymity. However, it suffers from many attacks and hence l-diversity was proposed. The l-diversity anonymization also possessed various limitations and hence t-closeness was proposed. This paper summarize these anonymization techniques and their limitations.

Peace and Art: A report on a one-off art workshop with underprivileged children and young people in Kampala, Uganda

This article is about a one-off art making workshop with children and young people in Kampala, Uganda. It is based on the theme of the United Nations (UN) Peace Day “Right to Peace”. This is in the context of the enduring political, economic and social instabilities in this region. The setting is a half-way house for unsettled children and young people who are homeless, often orphaned as a result of political unrest and who are likely to have experienced multiple trauma. The ‘home’ situation has a religious base. In addition to food, clothing and shelter, the ‘home’ provides a mentoring programme to the children and young people who live there, based on biblical teachings. This article reports on the workshop group process, the discussions and the creative activity based on the theme. The findings of the workshop and their relevance to the lives of the children and young people in the shelter are discussed. All names are pseudonyms and all personal identifiable information has been changed. Keywords: street children; trauma; basic needs; peace; art; religious symbols

On the efficiency of user identification: a system-based approach

In the Internet era, users’ fundamental privacy and anonymity rights have received significant research and regulatory attention. This is not only a result of the exponential growth of data that users generate when accomplishing their daily task by means of computing devices with advanced capabilities, but also because of inherent data properties that allow them to be linked with a real or soft identity. Service providers exploit these facts for user monitoring and identification, albeit impacting users’ anonymity, based mainly on personal identifiable information or on sensors that generate unique data to provide personalized services. In this paper, we report on the feasibility of user identification using general system features like memory, CPU and network data, as provided by the underlying operating system. We provide a general framework based on supervised machine learning algorithms both for distinguishing users and informing them about their anonymity exposure. We conduct a series of experiments to collect trial datasets for users’ engagement on a shared computing platform. We evaluate various well-known classifiers in terms of their effectiveness in distinguishing users, and we perform a sensitivity analysis of their configuration setup to discover optimal settings under diverse conditions. Furthermore, we examine the bounds of sampling data to eliminate the chances of user identification and thus promote anonymity. Overall results show that under certain configurations users’ anonymity can be preserved, while in other cases users’ identification can be inferred with high accuracy, without relying on personal identifiable information.

De-identification for privacy protection in multimedia content: A survey

Privacy is one of the most important social and political issues in our information society, characterized by a growing range of enabling and supporting technologies and services. Amongst these are communications, multimedia, biometrics, big data, cloud computing, data mining, internet, social networks, and audio–video surveillance. Each of these can potentially provide the means for privacy intrusion. De-identification is one of the main approaches to privacy protection in multimedia contents (text, still images, audio and video sequences and their combinations). It is a process for concealing or removing personal identifiers, or replacing them by surrogate personal identifiers in personal information in order to prevent the disclosure and use of data for purposes unrelated to the purpose for which the information was originally obtained. Based on the proposed taxonomy inspired by the Safe Harbour approach, the personal identifiers, i.e., the personal identifiable information, are classified as non-biometric, physiological and behavioural biometric, and soft biometric identifiers. In order to protect the privacy of an individual, all of the above identifiers will have to be de-identified in multimedia content. This paper presents a review of the concepts of privacy and the linkage among privacy, privacy protection, and the methods and technologies designed specifically for privacy protection in multimedia contents. The study provides an overview of de-identification approaches for non-biometric identifiers (text, hairstyle, dressing style, license plates), as well as for the physiological (face, fingerprint, iris, ear), behavioural (voice, gait, gesture) and soft-biometric (body silhouette, gender, age, race, tattoo) identifiers in multimedia documents.

Development and Evaluation of a New Technological Way of Engaging Patients and Enhancing Understanding of Drug Tolerability in Early Clinical Development: PROACT.

IntroductionDuring early clinical testing of a new medication, it is critical to understand and characterise patient tolerability. However, in early clinical studies, it is difficult for patients to contribute directly to the sponsors’ understanding of a new compound. Patient reported opinions about clinical tolerability (PROACT) provides a new, simple and innovative way in which patients can collaborate using an application downloaded to a mobile computer or smartphone.MethodsPROACT was designed with special consideration given to patient confidentiality, patient engagement and data security. A pilot study was conducted to investigate patient uptake of PROACT and to characterize clinical trial information it captured. Patients recruited to Phase I oncology trials at a UK center were eligible to participate but were required to have a tablet computer or smartphone. Patients used PROACT to upload audio/video messages that became available instantly to their clinical team, who were able to reply to the patient within PROACT. The patient’s message was also analyzed, personally-identifiable information removed and anonymized information then made available to the sponsor in an analytics module for decision-making. In parallel, a patient focus group was engaged to provide feedback on communication needs during early clinical trials and the PROACT concept.ResultsOf the 16 patients informed of PROACT, 8 had a smart device and consented to take part. Use of PROACT varied and all messages volunteered were relevant and informative for drug development. Topics disclosed included tolerability impacts, study design, and drug formulation. Alignment with the clinical study data provided a richer understanding of tolerability and treatment consequences. This information was available to be shared among the clinical team and the sponsor, to improve patient support and experience. Patient forum feedback endorsed the concept and provided further information to enhance the application.ConclusionOverall, PROACT achieved proof of concept in this small pilot study and delivered a secure end-to-end system that protected patient privacy and provided preliminary insight into patient experiences beyond the usual clinical trial data set. The use of mobile devices to interact actively with participants in clinical trials may be a new way of engaging and empowering patients. Further validation of this technology in larger patient cohorts is ongoing.FundingAstraZeneca.

Locking up passwords – for good

It's clear that bulk identity thefts – that is, the mass stealing of passwords or other personally identifiable information (PII) – are among the most harmful types of cyber-attack faced by businesses. They're a huge problem, not only in terms of the damage each attack causes, but also the volume of attacks overall. A cursory glance over the business headlines for the past few years announces huge password or PII thefts from organisations ranging from Sony PlayStation to eBay and Facebook to JP Morgan. We were barely a week into 2016 when it was revealed that email passwords for up to 320,000 users had been stolen from Time Warner. Bulk identity thefts are among the most harmful types of cyber-attack faced by businesses today and part of the problem is that businesses, security firms and cyber-criminals all share the same playing field. Thinking beyond standard computing architectures is the only solution to the ongoing arms race between hackers and security vendors. In a battle against cyber-criminality, in which businesses are always playing catch-up, this is a way of getting on the front foot and beginning to operate in a world beyond the attackers' reach, says Dr Will Harwood of Silicon:SAFE.

Corresponding Security Level with the Risk Factors of Personally Identifiable Information through the Analytic Hierarchy Process

Since Taiwan government has announced the New Version of Personal Information Protection Act , People began to pay attention to their personal information and privacy. Many industries significantly increased their responsibilities and faced more serious challenges. In order to cope with the requirements of the new law, BS10012 specification can help enterprises to reduce impact of personal data protection law. Enterprises need to rethink policy objectives, and make risk assessment of personally identifiable information (PII). This study using analytic hierarchy process (AHP) to identify the security level of PII. Corresponding security level with the risk factors of personal information, so that find the suitable countermeasure to protect users PII. Rarely see research about risk assessment of PII by using AHP, therefore the feasibility of the application of AHP in this regard is worthwhile to explore.

Picking the right path to mobile biometric authentication

Many online and mobile apps are used to manage highly valuable data, such as financial transactions, personally identifiable information (PII) or intellectual property. It is vital therefore to secure access to these apps through strong authentication. Yet the current widespread reliance on usernames and passwords presents a growing significant burden on users and businesses – delivering a poor user experience, inadequate security, spiralling costs, and lower revenues and profits. Biometric authentication presents a strategic way to overcome these deficiencies, which combines an improved user experience and higher security.

Is the Juice Worth the Squeeze? Costs and Benefits of Multiple Human Annotators for Clinical Text De-identification.

Clinical text contains valuable information but must be de-identified before it can be used for secondary purposes. Accurate annotation of personally identifiable information (PII) is essential to the development of automated de-identification systems and to manual redaction of PII. Yet the accuracy of annotations may vary considerably across individual annotators and annotation is costly. As such, the marginal benefit of incorporating additional annotators has not been well characterized. This study models the costs and benefits of incorporating increasing numbers of independent human annotators to identify the instances of PII in a corpus. We used a corpus with gold standard annotations to evaluate the performance of teams of annotators of increasing size. Four annotators independently identified PII in a 100-document corpus consisting of randomly selected clinical notes from Family Practice clinics in a large integrated health care system. These annotations were pooled and validated to generate a gold standard corpus for evaluation. Recall rates for all PII types ranged from 0.90 to 0.98 for individual annotators to 0.998 to 1.0 for teams of three, when meas-ured against the gold standard. Median cost per PII instance discovered during corpus annotation ranged from $ 0.71 for an individual annotator to $ 377 for annotations discovered only by a fourth annotator. Incorporating a second annotator into a PII annotation process reduces unredacted PII and improves the quality of annotations to 0.99 recall, yielding clear benefit at reasonable cost; the cost advantages of annotation teams larger than two diminish rapidly.

Fighting ID theft

Identity is now a commodity. As personally-identifiable information circulates increasingly online, thieves are hell-bent on stealing it. Credit card information, names, addresses, and dates of birth are just some of the data points that can trade for money online - and help to trash their owners' credit scores, or worse. ID theft is a growing problem that accounts for just under half of all frauds in the UK. The article discusses the technologies that can be put in place to prevent it.

A comprehensive concept map for adequate protection and effective management of personal information in networked Chinese services

Purpose – This paper aims to develop a comprehensive concept map to guide adequate protection and effective management of personal information in the provision of networked services in China through comprehensively considering the multi-disciplinary perspective of personal information protection and management with respect to their multi-dimensional applications, multi-directional controls and multi-contextual analysis in today’s networked environments. There are different perspectives on what personal information protection and management is about, why and how personal information should be protected and managed in the literature. Little, however, is known about the relationships between these multiple perspectives and their implications to personal information protection and management in the real-world practice. Design/methodology/approach – A multi-methods approach is adopted in the study, including a comprehensive review of the related literature, a content analysis of the relevant laws, polices, standards, a multi-cases study of the relevant network services providers and an online survey of the Chinese citizens who are the end-users of the networked services to adequately achieve the objective of this study. The concept map building technique is used as a tool for conducting the meta-synthesis of the findings from multiple data resources in the development of a comprehensive concept map for personal information protection and management. Findings – This study rationalizes the importance of the identification of personal information for adequate protection and effective management. It identifies five perspectives on personal information protection and management, namely, law, economics, sociology, information technology and information resources management for their applications at the organizational level. Five types of personal information are identified in the study for protection and management, namely, identifiable personal information, personal identity information, personal moral right information, personal civil right and interest information and personal business and transaction information. An integrated approach consisting of risk control, security control and users control is proposed for personal information protection and management in the provision of networked services in China. The study shows that not enough attention has been paid to the personal information protection and management from multi-disciplinary perspectives with respect to their multi-dimensional applications, multi-directional controls and multi-contextual analysis in the literature. There is a lack of understanding of what, why and how personal information is protected and managed in real-world practices in China. Practical implications – The investigation of the issues of personal information protection and management with respect to the relevant laws, polices, standards, networked services and organizations can lead to a better understanding of what, why and how personal information is protected and managed in real-world practices in China. The development of a comprehensive concept map for personal information protection and management can be used as an effective guideline for the formulation and implementation of appropriate strategies and policies in individual organizations for providing their stakeholders with quality-networked services in today’s highly connected network environment in China. Originality/value – The paper is the first step of a comprehensive study on the protection and management of personal information for the provision of networked services in China. It provides a solid foundation for further research with respect to the personal information protection and management. It is the first of this kind of studies to answer the questions of what types of personal information needed to be protected, why and how they should be protected in conformity with laws, regulations, polices, standards and the needs of networked services and business activities of organizations.

Are You Sure You Want to Contact Us? Quantifying the Leakage of PII via Website Contact Forms

Abstract The majority of commercial websites provide users the ability to contact them via dedicated contact pages. In these pages, users are typically requested to provide their names, email addresses, and reason for contacting the website. This effectively makes contact pages a gateway from being anonymous or pseudonymous, i.e., identified via stateful and stateless identifiers, to being eponymous. As such, the environment where users provide their personally identifiable information (PII) has to be trusted and free from intentional and unintentional information leaks. In this paper, we report on the first large-scale study of PII leakage via contact pages of the 100,000 most popular sites of the web. We develop a reliable methodology for identifying and interacting with contact forms as well as techniques that allow us to discover the leakage of PII towards thirdparties, even when that information is obfuscated. Using these methods, we witness the leakage of PII towards third-parties in a wide range of ways, including the leakage through third-party form submissions, third-party scripts that collect PII information from a first-party page, and unintended leakage through a browser’s Referer header. To recover the lost control of users over their PII, we design and develop Formlock, a browser extension that warns the user when contact forms are using PII-leaking practices, and provides the ability to comprehensively lock-down a form so that a user’s details cannot be, neither accidentally, nor intentionally, leaked to third parties

User Privacy Framework for Web-of-Objects based Smart Home Services

This paper presents user privacy framework for web-of-objects based smart home services to control the release of personally identifiable information (PII) in smart home environment. The ubiquity of smart home enables smart home users and third parties to access home devices and data from any location at any time. The ubiquitous and pervasiveness improves the user comfort level, but also makes user PIIs highly prone to leakage. We propose Smart Home Web of Object User Privacy (SWOPR) architecture to protect and control the release of user PIIs according to the user consent. We suggest an architecture that integrates the RESTful framework, ISO/IEC-29101, and XACML/Ontology; the integration is not supported in existing systems. The SWOPR introduces Smart Home Web of Objects Privacy Controller (SWOPC) and Privacy Processor (SWOPP) nodes. SWOPC controls the process of collection of PIIs from users to the release of his PIIs to others. SWOPP provides PIIs processing functions such as anonymization and encryption under the control of SWOPC. The proposed privacy framework architecture is simple, lightweight and has high performance. We also present service scenarios to acquire the user PIIs, consents and release of PIIs to others.

Privacy preserving probabilistic record linkage (P3RL): a novel method for linking existing health-related data and maintaining participant confidentiality.

BackgroundRecord linkage of existing individual health care data is an efficient way to answer important epidemiological research questions. Reuse of individual health-related data faces several problems: Either a unique personal identifier, like social security number, is not available or non-unique person identifiable information, like names, are privacy protected and cannot be accessed. A solution to protect privacy in probabilistic record linkages is to encrypt these sensitive information. Unfortunately, encrypted hash codes of two names differ completely if the plain names differ only by a single character. Therefore, standard encryption methods cannot be applied. To overcome these challenges, we developed the Privacy Preserving Probabilistic Record Linkage (P3RL) method.MethodsIn this Privacy Preserving Probabilistic Record Linkage method we apply a three-party protocol, with two sites collecting individual data and an independent trusted linkage center as the third partner. Our method consists of three main steps: pre-processing, encryption and probabilistic record linkage. Data pre-processing and encryption are done at the sites by local personnel. To guarantee similar quality and format of variables and identical encryption procedure at each site, the linkage center generates semi-automated pre-processing and encryption templates. To retrieve information (i.e. data structure) for the creation of templates without ever accessing plain person identifiable information, we introduced a novel method of data masking. Sensitive string variables are encrypted using Bloom filters, which enables calculation of similarity coefficients. For date variables, we developed special encryption procedures to handle the most common date errors. The linkage center performs probabilistic record linkage with encrypted person identifiable information and plain non-sensitive variables.ResultsIn this paper we describe step by step how to link existing health-related data using encryption methods to preserve privacy of persons in the study.ConclusionPrivacy Preserving Probabilistic Record linkage expands record linkage facilities in settings where a unique identifier is unavailable and/or regulations restrict access to the non-unique person identifiable information needed to link existing health-related data sets. Automated pre-processing and encryption fully protect sensitive information ensuring participant confidentiality. This method is suitable not just for epidemiological research but also for any setting with similar challenges.