Aug. 17, 2022, 1:20 a.m. | Judith Sáinz-Pardo Díaz, Álvaro López García

cs.CR updates on arXiv.org arxiv.org

Openly sharing data with sensitive attributes and privacy restrictions is a
challenging task. In this document we present the implementation of pyCANON, a
Python library and command line interface (CLI) to check and assess the level
of anonymity of a dataset through some of the most common anonymization
techniques: k-anonymity, ($\alpha$,k)-anonymity, $\ell$-diversity, entropy
$\ell$-diversity, recursive (c,$\ell$)-diversity, basic $\beta$-likeness,
enhanced $\beta$-likeness, t-closeness and $\delta$-disclosure privacy. For the
case of more than one sensitive attributes, two approaches are proposed for
evaluating this …

anonymity library python python library

Information Security Engineers

@ D. E. Shaw Research | New York City

Technology Security Analyst

@ Halton Region | Oakville, Ontario, Canada

Senior Cyber Security Analyst

@ Valley Water | San Jose, CA

Senior Product Delivery Associate - Cybersecurity | CyberOps

@ JPMorgan Chase & Co. | NY, United States

Security Ops Infrastructure Engineer (Remote US):

@ RingCentral | Remote, USA

SOC Analyst-1

@ NTT DATA | Bengaluru, India