# Compiled Obfuscation for Data Structures in Encrypted Computing

## TL;DR

This paper extends obfuscation compilation techniques for encrypted computing to complex data structures like doubles, floats, arrays, structs, and unions, enhancing data security through maximal variation in arithmetic instructions.

## Contribution

It introduces a unified principle for compiler design that maximizes entropy in all writable instructions, improving security for complex data structures in encrypted computing.

## Key findings

- Extended obfuscation techniques to doubles, floats, arrays, structs, and unions.
- Achieved maximal entropy variation in arithmetic instructions for enhanced security.
- Provided quantitative security analysis for the extended methods.

## Abstract

Encrypted computing is an emerging technology based on a processor that `works encrypted', taking encrypted inputs to encrypted outputs while data remains in encrypted form throughout. It aims to secure user data against possible insider attacks by the operator and operating system (who do not know the user's encryption key and cannot access it in the processor). Formally `obfuscating' compilation for encrypted computing is such that on each recompilation of the source code, machine code of the same structure is emitted for which runtime traces also all have the same structure but each word beneath the encryption differs from nominal with maximal possible entropy across recompilations. That generates classic cryptographic semantic security for data, relative to the security of the encryption, but it guarantees only single words and an adversary has more than that on which to base decryption attempts. This paper extends the existing integer-based technology to doubles, floats, arrays, structs and unions as data structures, covering ANSI C. A single principle drives compiler design and improves the existing security theory to quantitative results: every arithmetic instruction that writes must vary to the maximal extent possible.