Results 11 to 20 of about 2,010,621 (347)
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2018 This position paper observes how different technical and normative conceptions of privacy have evolved in parallel and describes the practical challenges that these divergent approaches pose. Notably, past technologies relied on intuitive, heuristic understandings of privacy that have since been shown not to satisfy expectations for privacy protection.
Kobbi Nissim, Alexandra Wood
openaire +3 more sources
New Program Abstractions for Privacy [PDF]
, 2020 Static program analysis, once seen primarily as a tool for optimising programs, is now increasingly important as a means to provide quality guarantees about programs. One measure of quality is the extent to which programs respect the privacy of user data.
C Dwork +5 more
core +1 more source
A Framework for Analyzing and Comparing Privacy States [PDF]
, 2014 This article develops a framework for analyzing and comparing privacy and privacy protections across (inter alia) time, place, and polity and for examining factors that affect privacy and privacy protection.
Biava, Ryan, Rubel, Alan
core +1 more source
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds [PDF]
, 2016 "Concentrated differential privacy" was recently introduced by Dwork and Rothblum as a relaxation of differential privacy, which permits sharper analyses of many privacy-preserving computations.
A Beimel +7 more
core +2 more sources
Threats, attacks and defenses to federated learning: issues, taxonomy and perspectives
Cybersecurity, 2022 Empirical attacks on Federated Learning (FL) systems indicate that FL is fraught with numerous attack surfaces throughout the FL execution. These attacks can not only cause models to fail in specific tasks, but also infer private information.
Pengrui Liu, Xiangrui Xu, Wei Wang
doaj +1 more source
LSGAN-AT: enhancing malware detector robustness against adversarial examples
Cybersecurity, 2021 Adversarial Malware Example (AME)-based adversarial training can effectively enhance the robustness of Machine Learning (ML)-based malware detectors against AME. AME quality is a key factor to the robustness enhancement.
Jianhua Wang +4 more
doaj +1 more source
Balancing smartness and privacy for the Ambient Intelligence [PDF]
, 2006 Ambient Intelligence (AmI) will introduce large privacy risks. Stored context histories are vulnerable for unauthorized disclosure, thus unlimited storing of privacy-sensitive context data is not desirable from the privacy viewpoint.
Anciaux, Nicolas +3 more
core +7 more sources
Jurisprudential and Legal Study of the Relationship between Surrogate Mother and the Child Born of Surrogacy [PDF]
پژوهشنامه حقوق اسلامی, 2013 Using surrogacy as one of the new ways of supporting fertility in away that the owner of the womb (surrogate mother) does not have anycreational relationship (through ovum) with the child, merely raisingthe fetus of another couple and giving birth to it,
Najadali Almasi +2 more
doaj +1 more source
Clinical Chemistry, 2018 Abstract BACKGROUND Genetic information is unique among all laboratory data because it not only informs the current health of the specific person tested but may also be predictive of the future health of the individual and, to varying degrees, all biological relatives.
Abraham P, Schwab +3 more
openaire +2 more sources
Adversarial attack and defense in reinforcement learning-from AI security view
Cybersecurity, 2019 Reinforcement learning is a core technology for modern artificial intelligence, and it has become a workhorse for AI applications ranging from Atrai Game to Connected and Automated Vehicle System (CAV).
Tong Chen +5 more
doaj +1 more source