As this article is being drafted, the SARS-CoV-2/COVID-19 pandemic is causing harm and disruption across the world. Many countries aimed at supporting their contact tracers with the use of digital contact tracing apps in order to manage and control the spread of the virus. Their idea is the automatic registration of meetings between smartphone owners for the quicker processing of infection chains. To date, there are many contact tracing apps that have already been launched and used in 2020. There has been a lot of speculations about the privacy and security aspects of these apps and their potential violation of data protection principles. Therefore, the developers of these apps are constantly criticized because of undermining users’ privacy, neglecting essential privacy and security requirements, and developing apps under time pressure without considering privacy- and security-by-design. In this study, we analyze the privacy and security performance of 28 contact tracing apps available on Android platform from various perspectives, including their code’s privileges, promises made in their privacy policies, and static and dynamic performances. Our methodology is based on the collection of various types of data concerning these 28 apps, namely permission requests, privacy policy texts, run-time resource accesses, and existing security vulnerabilities. Based on the analysis of these data, we quantify and assess the impact of these apps on users’ privacy. We aimed at providing a quick and systematic inspection of the earliest contact tracing apps that have been deployed on multiple continents. Our findings have revealed that the developers of these apps need to take more cautionary steps to ensure code quality and to address security and privacy vulnerabilities. They should more consciously follow legal requirements with respect to apps’ permission declarations, privacy principles, and privacy policy contents.

This paper presents results from a privacy analysis of COVID-19 contact tracing apps developed within the EU. Though these apps have been termed advantageous, concerns regarding privacy have become an issue that has led to their slow adoption. In this empirical study, we perform both static and dynamic analysis to judge apps’ privacy-preserving behavior together with the analysis of the privacy and data protection goals to deduce their transparency and intervenability. From the results, we discover that while the apps aim to be privacy-preserving, not all adhere to this as we observe one tracks users’ location, while the other violates the principle of least privilege, data minimisation and transparency, which puts the users’ at risk by invading their privacy.

Healthcare organisations have become a key target for attackers as evidenced by the global increase in cyberattacks. These cyberattacks are attributed to various attackers who differ in motivations and skills, with the common motivation being financial gain due to the rich personal data contained in patients' health records. But what would happen if the motivation changed? What would happen if the motivation is driven by targeting key people, mass exploitation or taking lives? What would happen if a strategic cyberattack knocks out a society’s critical infrastructure? This article investigates the possibility of targeting e-Health in the context of cyberwar. It assesses the privacy in healthcare and compares the consequences and impact of conventional cyber-attacks within the healthcare sector, against the consequences and impact of cyberwar on the same. The outcome indicates that e-Health in the context cyberwar could result to active reconnaissance of patient records, which could lead to the targeting of key and influential people through Personally Identifiable Information (PII), mass exploitation, and personal attacks derived from Personal Health Information (PHI), which could result to irreversible damage or death.

What harms and consequences do patients experience after a medical data breach? This article aims at the improvement of privacy impact analysis for data breaches that involve personal medical data. The article has two major findings. First, scientific literature does not mention consequences and harms to the data subjects when discussing data breaches in the healthcare sector. For conceptualizing actual documented harm, we had to search court rulings and popular press articles instead. We present the findings of our search for empirically founded harms in the first part of the article. Second, we present a modified PRIAM assessment method with the goal of better assessment of harms and consequences of such data breaches for the patient/employee data subject in healthcare. We split the risk assessment into parallel categories of assessment rather than calculating a single risk score. In addition, we quantify the original PRIAM categories into a calculus for risk assessment. The article presents our modified PRIAM which is the result of these modifications. Our overall contribution is the collection of actual harms and consequences of e-health data breaches that complement the overly theoretical discussion in publications. With our operationalization of PRIAM and by providing a catalog of real harms examples, we focus privacy impact assessment on actual harms to persons.

Assessing privacy risks and incorporating privacy measures from the onset requires a comprehensive understanding of potential impacts on data subjects. Privacy Impact Assessments (PIAs) offer a systematic methodology for such purposes, which are closely related to Data Protection Impact Assessments (DPIAs), particularly outlined in Article 35 of the General Data Protection Regulation (GDPR). The core of a PIA is a Privacy Risk Assessment (PRA). PRAs can be integrated as part of full-fledged PIAs or independently developed to support PIA processes. Although these methodologies have been identified as essential enablers of privacy by design, their effectiveness has been criticized because of the lack of evidence of their rigorous and systematic evaluation. Hence, we conducted a Systematic Literature Review (SLR) to identify published PIA and PRA methodologies and assess how and to what extent they have been scientifically validated or evaluated. We found that these methodologies are rarely evaluated for their performance in practice, and most of them have only been validated in limited studies. Most validation evidence is found with PRA methodologies. Of the evaluated methodologies, PIAs were the most evaluated, where case studies were the predominant evaluation method. These evaluated methodologies can be easily transferred to an industrial setting or used by practitioners, as they provide evidence of their use in practice. In addition, the findings in this study can be used to inform researchers of the current state-of-the-art, and practitioners can understand the benefits and current limitations of the methodologies and adopt evidence-based practices. 

Privacy Impact Assessments (PIAs), also known as Data Protection Impact Assessments (DPIAs) under the EU GDPR, and Privacy Risk Assessments (PRAs) have emerged as prominent privacy engineering methodologies, aiding developers and data controllers to systematically identify privacy risk sources and assign appropriate controls. As part of such methodologies, the concept of privacy harms has been proposed as a valuable, well-structured taxonomy that contributes to the rationalization and justification of assessment decisions made by practitioners. Although some PRA methodologies have integrated privacy harms, the evidence that such inclusions improve the assessors' decision-making remains incipient. This study aims to understand whether adhering to and integrating privacy harm concepts can enhance PRA outcomes by investigating PIA/DPIA and PRA practitioner's perspectives on practical operationalization aspects. A qualitative approach based on semi-structured interviews, including a workable PRA exercise, was used to elicit the practitioner's opinions and experiences concerning the use of privacy harms, with the data interpretation process following a reflexive thematic analysis. In total, 17 privacy practitioners were interviewed, allowing for an extensive range of positive (e.g., informative and educational) and negative opinions (e.g., misleading and too broad) on the practical inclusion and operationalization of privacy harms in PRA methodologies and the conceptualization of privacy harms when conducting assessments. The results indicate a lack of a standardized concept of privacy harm, as differing definitions have been provided. Participants also highlighted that privacy harms are highly context-dependent and vary based on the data subject and hence could result in difficulty quantifying. Nevertheless, privacy harms are a critical addition to PIA/DPIA and PRA methodologies, supporting more rationalized and justifiable decisions when ascertaining risk and severity levels and implementing mitigating controls to prevent the materialization of harm. Yet, some prioritization of harm categories is advisable so that time and resources for assessment are efficiently allocated.