Zobrazeno 1 - 10
of 88
pro vyhledávání: '"P. Goldsteen"'
Analyzing time-series data that contains personal information, particularly in the medical field, presents serious privacy concerns. Sensitive health data from patients is often used to train machine learning models for diagnostics and ongoing care.
Externí odkaz:
http://arxiv.org/abs/2407.02870
Retrieval Augmented Generation (RAG) systems have shown great promise in natural language processing. However, their reliance on data stored in a retrieval database, which may contain proprietary or sensitive information, introduces new privacy conce
Externí odkaz:
http://arxiv.org/abs/2405.20446
Natural language processing models have experienced a significant upsurge in recent years, with numerous applications being built upon them. Many of these applications require fine-tuning generic base models on customized, proprietary datasets. This
Externí odkaz:
http://arxiv.org/abs/2403.08481
Artificial intelligence systems are prevalent in everyday life, with use cases in retail, manufacturing, health, and many other fields. With the rise in AI adoption, associated risks have been identified, including privacy risks to the people whose d
Externí odkaz:
http://arxiv.org/abs/2310.07219
Autor:
Clare A. Primiero, Brigid Betz-Stablein, Nathan Ascott, Brian D’Alessandro, Seraphin Gaborit, Paul Fricker, Abigail Goldsteen, Sandra González-Villà, Katie Lee, Sana Nazari, Hang Nguyen, Valsamis Ntouskos, Frederik Pahde, Balázs E. Pataki, Josep Quintana, Susana Puig, Gisele G. Rezze, Rafael Garcia, H. Peter Soyer, Josep Malvehy
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionArtificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However,
Externí odkaz:
https://doaj.org/article/4562b5e511fb41b3853d0002896d5e82
Publikováno v:
Frontiers in Digital Health, Vol 6 (2024)
This paper will discuss the European funded iToBoS project, tasked by the European Commission to develop an AI diagnostic platform for the early detection of skin melanoma. The paper will outline the project, provide an overview of the data being pro
Externí odkaz:
https://doaj.org/article/085bffe434c54625948390e98209148e
The EU General Data Protection Regulation (GDPR) mandates the principle of data minimization, which requires that only data necessary to fulfill a certain purpose be collected. However, it can often be difficult to determine the minimal amount of dat
Externí odkaz:
http://arxiv.org/abs/2008.04113
There is a known tension between the need to analyze personal data to drive business and privacy concerns. Many data protection regulations, including the EU General Data Protection Regulation (GDPR) and the California Consumer Protection Act (CCPA),
Externí odkaz:
http://arxiv.org/abs/2007.13086
Machine learning models often pose a threat to the privacy of individuals whose data is part of the training set. Several recent attacks have been able to infer sensitive information from trained models, including model inversion or attribute inferen
Externí odkaz:
http://arxiv.org/abs/2006.15877
Autor:
Goldsteen, Abigail, Douek, Tomer, Cohen, Yaniv, Gokhman, Igor, Keren-Ackerman, Ofir, Katsovich, Gadi, Weintraub, Grisha, Ben-Ari, Doron
Publikováno v:
1st International Workshop on Security and Privacy in Models and Data (TRIDENT 2019)
The European General Data Protection Regulation asserts data subjects' right to be forgotten, i.e., their right to request that all their personal data be deleted from an organizations' data stores. However, fulfilling such requests in large-scale sy
Externí odkaz:
http://arxiv.org/abs/1910.13784