Privacy Analytics (Canada)

Humanitarian organisations often operate in emergency contexts where strict compliance with data protection laws, such as the General Data Protection Regulation (GDPR), can pose significant practical challenges. This paper explores the need for a differentiated data protection regime tailored to the realities of humanitarian crises, balancing efficiency and the fundamental rights of data subjects. By analysing key European Court of Justice cases, including Schrems II (C-311/18), Nowak (C-434/16) and Pankki S (C-579/21), the paper highlights the importance of adapting core GDPR principles to crisis situations. It also examines the integration of human rights principles, emphasising the protection of dignity and autonomy during emergencies. Furthermore, it addresses regulatory challenges, proposing proactive engagement with authorities to ensure accountability and trust. Practical solutions are proposed such as simplified Data Protection Impact Assessments (DPIAs), the use of pseudonymisation, data minimisation and standardised Memorandums of Understanding (MOUs) to replace complex contractual requirements. These measures aim to ensure compliance while enabling rapid and effective responses in emergencies. The paper concludes by calling for the development of a flexible regulatory framework that integrates data protection into the operational needs of humanitarian organisations without compromising ethical and legal standards.

Objective: To describe a case of a novel mutation with dental and maxillofacial expression in a family with Aarskog syndrome and to conduct a literature review to determine the importance of a multidisciplinary approach in the pathology. Methods: The authors described a family of a father and mother and 7 children (5 sons affected). The first child is evaluated for multiple mandibular osteolytic lesions and dental malocclusion with eruption disorders. The patient presents facial features of Aarskog syndrome, such as hypertelorism and eyelid ptosis with epicanthal folds, but also an unusual sign of numerous comedones distributed over the body. A literature review on dental and maxillofacial signs in Aarskog syndrome was conducted on Scopus and Pubmed with specific keywords. Results: Osteolytic lesions are described as orthokeratotic keratocysts with giant cellular, foreign body type, calcifications, and bone spicules. A recurrence occurred 2 years after surgery of keratocysts. Ten articles were selected for the description of dental and maxillofacial features associated with Aarskog syndrome. Discussion: Literature has paid little attention to different phenotypic characterizations in the maxillofacial region of patients with Aarskog syndrome. It is important to determine an early diagnosis to provide the best treatments for patients. The family described has some peculiarities: (1) a new nucleotide variation, (2) the sample size, (3) features as multiple comedones of the body, and keratocysts of the jaws are never described in the literature. Conclusion: Clinical and radiological maxillofacial signs, often not evaluated in Aarskog syndrome, should be considered early to obtain an optimal treatment.

What does the criminal conviction of Uber's former CISO mean for the information security sector? The case highlights the need for CISOs to ensure that they have a clear line to the board, and a robust plan for how to deal with security incidents ahead of time.

Despite their importance, misunderstandings about Data Protection Impact Assessments (DPIAs) are a common stumbling block for many businesses. So what do you need to know about them?

It is common practice for data providers to include text descriptions for each column when publishing datasets in the form of data dictionaries. While these documents are useful in helping an end-user properly interpret the meaning of a column in a dataset, existing data dictionaries typically are not machine-readable and do not follow a common specification standard. We introduce the Semantic Data Dictionary, a specification that formalizes the assignment of a semantic representation of data, enabling standardization and harmonization across diverse datasets. In this paper, we present our Semantic Data Dictionary work in the context of our work with biomedical data; however, the approach can and has been used in a wide range of domains. The rendition of data in this form helps promote improved discovery, interoperability, reuse, traceability, and reproducibility. We present the associated research and describe how the Semantic Data Dictionary can help address existing limitations in the related literature. We discuss our approach, present an example by annotating portions of the publicly available National Health and Nutrition Examination Survey dataset, present modeling challenges, and describe the use of this approach in sponsored research, including our work on a large NIH-funded exposure and health data portal and in the RPI-IBM collaborative Health Empowerment by Analytics, Learning, and Semantics project. We evaluate this work in comparison with traditional data dictionaries, mapping languages, and data integration tools.

Clinical corpora can be deidentified using a combination of machine-learned automated taggers and hiding in plain sight (HIPS) resynthesis. The latter replaces detected personally identifiable information (PII) with random surrogates, allowing leaked PII to blend in or "hide in plain sight." We evaluated the extent to which a malicious attacker could expose leaked PII in such a corpus. We modeled a scenario where an institution (the defender) externally shared an 800-note corpus of actual outpatient clinical encounter notes from a large, integrated health care delivery system in Washington State. These notes were deidentified by a machine-learned PII tagger and HIPS resynthesis. A malicious attacker obtained and performed a parrot attack intending to expose leaked PII in this corpus. Specifically, the attacker mimicked the defender's process by manually annotating all PII-like content in half of the released corpus, training a PII tagger on these data, and using the trained model to tag the remaining encounter notes. The attacker hypothesized that untagged identifiers would be leaked PII, discoverable by manual review. We evaluated the attacker's success using measures of leak-detection rate and accuracy. The attacker correctly hypothesized that 211 (68%) of 310 actual PII leaks in the corpus were leaks, and wrongly hypothesized that 191 resynthesized PII instances were also leaks. One-third of actual leaks remained undetected. A malicious parrot attack to reveal leaked PII in clinical text deidentified by machine-learned HIPS resynthesis can attenuate but not eliminate the protective effect of HIPS deidentification.

This paper analyses the challenges of blockchain technology in terms of General Data Protection Regulation compliance. It focuses on the great promise of transparency in blockchain systems, its tamper-proof nature and the question of ‘Who will be the data controller in blockchain transactions?’ In blockchain systems, data is distributed across all the nodes’ (who created the blocks) computers at different locations. This makes it difficult to amend the data in the blocks as all the nodes’ participation and approval are needed. While this feature provides transparency and resilience, it is a major challenge on exercising the rights of rectification or deletion. Blockchain systems can be created as private and public, and particularly in public blockchain systems, it can be challenging to allocate and determine the liability of the parties and determine the data controller. We look into the challenges in these areas in a nutshell and very briefly mention how blockchain can benefit from the privacy by design concept.

In an industry as opaque as the surveillance technology industry, any effort to put in place safeguards to prevent human rights abuses using these technologies should be recognised and encouraged. But what happens when those systems fail?
 For surveillance technology companies, deciding where not to sell in a world full of eager government clients has important ethical and financial implications. The surveillance industry favours a country-agnostic framework that hews to sanctions and export laws. Advocacy and media groups argue to extend the no-sell zone beyond sanctioned governments to ‘authoritarian’ ones.
 Yet legal compliance is not the only factor influencing surveillance companies’ choices, this article argues. Based on original investigation, this article examines the social responsibility policies of communications surveillance technology vendors and the legal, reputational and normative concerns these demonstrate.
 The article explores the use of country rankings related to ‘authoritarianism’ and ‘good governance’ by examining the inner workings of a specific company in crisis, Procera Networks. As the cases featured demonstrate, closer attention to be paid processes of corporate responsibility norm-making within companies.

Nationale de l'Informatique et des Libertés (CNIL) ordered Google to remove links to websites containing information on French data subjects from all Google domains, not just from country-specific domains