Anonymization: The imperfect science of using data while preserving privacy
Information about us, our actions, and our preferences is created at scale through surveys or
scientific studies or as a result of our interaction with digital devices such as smartphones …
scientific studies or as a result of our interaction with digital devices such as smartphones …
Latest trends of security and privacy in recommender systems: a comprehensive review and future perspectives
With the widespread use of Internet of things (IoT), mobile phones, connected devices and
artificial intelligence (AI), recommender systems (RSs) have become a booming technology …
artificial intelligence (AI), recommender systems (RSs) have become a booming technology …
Prochlo: Strong privacy for analytics in the crowd
The large-scale monitoring of computer users' software activities has become commonplace,
eg, for application telemetry, error reporting, or demographic profiling. This paper describes …
eg, for application telemetry, error reporting, or demographic profiling. This paper describes …
Security and privacy challenges in smart cities
The construction of smart cities will bring about a higher quality of life to the masses through
digital interconnectivity, leading to increased efficiency and accessibility in cities. Smart …
digital interconnectivity, leading to increased efficiency and accessibility in cities. Smart …
Local differential privacy for deep learning
PCM Arachchige, P Bertok, I Khalil… - IEEE Internet of …, 2019 - ieeexplore.ieee.org
The Internet of Things (IoT) is transforming major industries, including but not limited to
healthcare, agriculture, finance, energy, and transportation. IoT platforms are continually …
healthcare, agriculture, finance, energy, and transportation. IoT platforms are continually …
Privacy in pharmacogenetics: An {End-to-End} case study of personalized warfarin dosing
We initiate the study of privacy in pharmacogenetics, wherein machine learning models are
used to guide medical treatments based on a patient's genotype and background …
used to guide medical treatments based on a patient's genotype and background …
Minimax optimal procedures for locally private estimation
Working under a model of privacy in which data remain private even from the statistician, we
study the tradeoff between privacy guarantees and the risk of the resulting statistical …
study the tradeoff between privacy guarantees and the risk of the resulting statistical …
A survey on trustworthy recommender systems
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …
deployed in almost every corner of the web and facilitate the human decision-making …
Tumblebit: An untrusted bitcoin-compatible anonymous payment hub
E Heilman, L Alshenibr, F Baldimtsi… - … and distributed system …, 2017 - open.bu.edu
This paper presents TumbleBit, a new unidirectional unlinkable payment hub that is fully
compatible with today s Bitcoin protocol. TumbleBit allows parties to make fast, anonymous …
compatible with today s Bitcoin protocol. TumbleBit allows parties to make fast, anonymous …
[PDF][PDF] Differentially private empirical risk minimization.
Privacy-preserving machine learning algorithms are crucial for the increasingly common
setting in which personal data, such as medical or financial records, are analyzed. We …
setting in which personal data, such as medical or financial records, are analyzed. We …