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Saturday, June 17 • 10:15am - 10:50am
Privacy in the Open Source: Homomorphic Encryption

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With over 5 trillion megabytes of data on the internet, data privacy is becoming increasingly important. Many people blindly accept website privacy policies, leading to the transfer of personal information to the public domain. However, some platforms offer data anonymization, which allows personal information to be encrypted while still enabling analysis and inferences. Homomorphic encryption enables the safe, secure, and private sharing of data in untrusted environments, such as public clouds or with external parties.

In this talk we will cover,
1. Introduction to HE and its significance in data security.
2. Comparative study of open source HE tools.
3. How HE can transform the way we view open-source data and enable multi-party sharing.
4. Intersection of AI and HE, and how it can enhance data privacy and security.

Attendees will leave the talk with a deeper understanding of HE, its potential applications, and the ways in which it can improve data security and privacy.

Speakers
avatar for Aakanksha Duggal

Aakanksha Duggal

Senior Data Scientist, Red Hat
Aakanksha Duggal is a Senior Data Scientist in the Emerging Technologies Group at Red Hat. She is a part of the Data Science team and works on developing open source software that uses AI and machine learning applications to solve engineering problems.


Saturday June 17, 2023 10:15am - 10:50am CEST
G202 | Talks
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