Improving Crypto: A Novel Smartphone Based Entropy Generator
ISEF · 2015
Overview
Governments, businesses, financial institutions and individuals have become reliant upon cryptography and encryption to protect their information. McAfee estimates that the cost of cybercrime to the global economy is approximately $375 to $575 billion in annual losses. Much of this is due to weak cryptography. Cryptography consists of four main parts: the encryption algorithm, the implementation, random numbers, and user input. Random number generation is currently the most vulnerable element of encryption which can easily be controlled by a cryptographer. There are two types of Random Number Generators (RNGs): Pseudorandom Number Generators (PRNG), which consist of a deterministic algorithm running on a computer, and True Random Number Generators (TRNG), which rely on hardware and physical phenomena to generate true random numbers. Since TRNGs are non-deterministic, they are considerably more secure than PRNGs. Unfortunately, the lack of easily accessible and free TRNGs prevents them from being used more widely. The goal of this project is to create a free, open source TRNG which runs on an Android phone and generates random numbers by gathering entropy from the phone's sensors, and subsequently hashes it to create a 512 bit digest of the entropy. Once this is created, it can be used by any program requiring high quality random numbers. The TRNG was tested with and passed the entire DieHarder test suite. Statistical analysis performed by DieHarder indicated that the generated numbers were random. Providing this application will greatly enhance the security of personal data and help reduce cybercrime.
Awards (1)
- Oracle Academy: Award of $5,000 for outstanding project in the systems software category. $5,000
Competition history
- ISEF 2015
Resources
Related projects
ISEF · 2026
Entropy Engine: Utilizing Non-Deterministic Electron Cascade Dynamics for Cryptographically Secure Password Generation
ISEF · 2014
Brownian Motion as a Source of Entropy for the Generation of Random Numbers
ISEF · 2019
Development of a Machine Learning Algorithm for Generating Random Numbers
ISEF · 2017
Novel Application of Collatz-like Sequences to Cryptographically Secure Pseudo-Random Number Generation
Closest projects by meaning, across every fair and year in the corpus.
Source: Regeneron International Science and Engineering Fair