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On the Evaluation of Privacy Impact Assessment and Privacy Risk Assessment Methodologies: A Systematic Literature Review

IEEE Access
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 ...
Samuel Wairimu, Leonardo Horn Iwaya, Lothar Fritsch, Stefan Lindskog   +3 more
doaj   +1 more source

Decentralizing Privacy: Using Blockchain to Protect Personal Data

2015 IEEE Security and Privacy Workshops, 2015
The recent increase in reported incidents of surveillance and security breaches compromising users' privacy call into question the current model, in which third-parties collect and control massive amounts of personal data.
Guy Zyskind, Oz Nathan, A. Pentland
semanticscholar   +1 more source

Germline variants in CDKN2A wild‐type melanoma prone families

Molecular Oncology, EarlyView.
Among melanoma‐prone families, wild‐type for CDKN2A and CDK4, some have pathogenic variants in genes not usually linked to melanoma. Furthermore, rare XP‐related variants and variants in MC1R are enriched in such families. Germline pathogenic variants in CDKN2A are well established as an underlying cause of familial malignant melanoma. While pathogenic
Gjertrud T. Iversen, Marie Loeng, Amalie Lund Holth, Per E. Lønning, Jürgen Geisler, Stian Knappskog   +5 more
wiley   +1 more source

DATA SUBJECT ACCESS REQUEST: WHAT INDONESIA CAN LEARN AND OPERATIONALISE IN 2024?

Journal of Central Banking Law and Institutions, 2023
The enactment of the Indonesian Personal Data Protection (PDP) Law is in line with the nation’s position as the most promising digital economy in Southeast Asia.
Muhammad Deckri Algamar, Noriswadi Ismail   +1 more
doaj   +1 more source

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

, 2019
In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy ...
A Wasef, C Dwork, H Shin, L Sweeney, N Sadeh, SL Warner, Y Koren, YA Montjoye De, Z Huo   +8 more
core   +1 more source

MET and NF2 alterations confer primary and early resistance to first‐line alectinib treatment in ALK‐positive non‐small‐cell lung cancer

Molecular Oncology, EarlyView.
Alectinib resistance in ALK+ NSCLC depends on treatment sequence and EML4‐ALK variants. Variant 1 exhibited off‐target resistance after first‐line treatment, while variant 3 and later lines favored on‐target mutations. Early resistance involved off‐target alterations, like MET and NF2, while on‐target mutations emerged with prolonged therapy.
Jie Hu, Ning Ding, Xiaobo Xu, Yedan Chen, Yong Zhang, Jingwen Liu, Jiebai Zhou, Hairong Bao, Donghui Zhang, Yijun Song, Yang Shao, Yuanlin Song   +11 more
wiley   +1 more source

It’s getting personal: The ethical and educational implications of personalised learning technology

Journal of Philosophy in Schools, 2019
Personalised learning systems—systems that predict learning needs to tailor education to the unique learning needs of individual students—are gaining rapid popularity.
Iris Huis in ’t Veld, Michael Nagenborg   +1 more
doaj   +1 more source

Acknowledgment to Reviewers of Journal of Cybersecurity and Privacy in 2021

Journal of Cybersecurity and Privacy, 2022
Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Journal of Cybersecurity and Privacy Editorial Office
doaj   +1 more source

Machine Learning with Membership Privacy using Adversarial Regularization [PDF]

Conference on Computer and Communications Security, 2018
Machine learning models leak significant amount of information about their training sets, through their predictions. This is a serious privacy concern for the users of machine learning as a service.
Milad Nasr, R. Shokri, Amir Houmansadr
semanticscholar   +1 more source

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

FEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi, Xin Gao, Takashi Gojobori   +2 more
wiley   +1 more source