{"id":1655,"date":"2025-02-02T15:28:52","date_gmt":"2025-02-02T22:28:52","guid":{"rendered":"https:\/\/wpsites.ucalgary.ca\/jacobson-cpsc\/?p=1655"},"modified":"2025-02-02T15:28:56","modified_gmt":"2025-02-02T22:28:56","slug":"isec-611-group-8-garbled-circuits","status":"publish","type":"post","link":"https:\/\/wpsites.ucalgary.ca\/jacobson-cpsc\/2025\/02\/02\/isec-611-group-8-garbled-circuits\/","title":{"rendered":"ISEC 611 Group 8 – Garbled Circuits"},"content":{"rendered":"\n

Walkthrough <\/em><\/strong>: https:\/\/youtu.be\/7MXVV858loU<\/a><\/p>\n\n\n\n

Code Example Link<\/em><\/strong>: https:\/\/github.com\/HaydenMcNally\/ISEC-611\u00a0<\/p>\n\n\n\n

Introduction to Garbled Circuits (History and Overview)<\/strong>\u00a0<\/h2>\n\n\n\n

Garbled circuit is a computational technique which Andrew Yao introduced in an oral presentation in 1986, and the first written document was authored by Goldreich, Micali, and Widgerson in 1987. The term \u201cgarbled circuit\u201d was coined by Beaver, Micali, and Rogaway in 1990. The primary goal was to enable two parties to jointly compute a function using their private inputs while ensuring that neither party gains access to the other\u2019s input. This protocol is particularly useful in scenarios where trust is limited, and secure computation is required without reliance on a trusted third party. <\/p>\n\n\n\n

Yao\u2019s protocol was first demonstrated in the Millionaires\u2019 Problem, where two individuals determine who is wealthier without disclosing their actual wealth. The problem discusses two millionaires, Alice and Bob, who are interested in knowing which of them is richer without revealing their actual wealth. This problem is analogous to a more general problem where there are two numbers\u202fa\u202fand\u202fb,\u202fand the goal is to determine whether the inequality\u202fa\u2265b\u202fis true or false without revealing the actual values of\u202fa\u202fand\u202fb was the first example of secure computation [3].  <\/p>\n\n\n\n

The concept extends beyond this problem, enabling secure computations in various applications, such as privacy-preserving data mining, secure voting, confidential transactions, and privacy-focused AI computations.  <\/p>\n\n\n\n

What is Garbled Circuits?\u00a0<\/strong>\u00a0<\/h2>\n\n\n\n

Garbled circuits are a cryptographic protocol that allows two parties to securely compute a function over their private inputs without needing a trusted third party. This is achieved by representing the function as a Boolean circuit and using Oblivious Transfer to ensure input privacy [2]. <\/p>\n\n\n\n

In private data computation, one of the objectives is to compute data without the other party knowing the details of the data set.  <\/p>\n\n\n\n

Privacy preserving data mining (PPDM) deals with protecting the privacy of individual data or sensitive knowledge without sacrificing the utility of the data. People have become aware of the privacy intrusions on their personal data and are very reluctant to share their sensitive information [1]. Also, some regulations on how personal data is handled requires some computational techniques to protect the privacy of individual\/sensitive data.  <\/p>\n\n\n\n

Garbled circuit is a technique used in a multi-party Privacy Preserving Data Minning (PPDM). <\/p>\n\n\n\n

At its core, the Garbled Circuit protocol involves representing a function as a Boolean circuit, where each logical gate is encrypted in such a way that only the correct sequence of inputs can reveal the output. The process consists of three main phases: <\/p>\n\n\n\n