Achieving true randomness in cybersecurity

In this Writer's Room blog, Andela community member and engineer Oyeniyi Adeboye explores the vital role of randomness in cybersecurity and the techniques used to achieve it.

As a Systems Software Engineer, my career has been devoted to understanding the intricacies of embedded systems, and systems in general. In today’s digital landscape, cybersecurity is of utmost importance. One often overlooked but critical aspect of this security is true randomness. Without it, the cryptographic keys and data that protect our digital lives could be at risk.



Pseudo-random number generation (PRNG) vs true random number generation (TRNG)

There are two major types of random numbers, pseudo random and true random. Pseudo random numbers use deterministic algorithms to generate random numbers, making them predictable if the seed is known. The random() function provided by the math function in a lot of programming languages uses a PRNG scheme. However, there are a lot of statistical tests that show how the outputted numbers are in fact not really random and follow a distribution.

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The code snippet above shows two such tests that can be done. When this code is run, the result is that the distribution does not change, no matter how many times it is run for a particular computer system.

TRNGs, in contrast, derive numbers from inherently unpredictable physical processes, ensuring true randomness.

PRNGs are favored for non-security applications where computational efficiency matters, like simulations and games. TRNGs are essential for cryptography, ensuring unpredictable keys and data protection in secure communication, banking, and government operations. Understanding this difference is crucial for choosing the right tool for specific security needs.

Methods of generating true randomness

In the quest for genuine randomness, various methods have emerged to ensure the unpredictability that’s essential for robust cybersecurity. Among these, hardware random number generators (HRNGs) stand out. HRNGs exploit the inherent randomness found in physical processes like electronic noise, radioactive decay, or even the unpredictable behavior of microscopic particles. These devices provide a steady stream of truly random numbers, making them ideal for cryptographic applications that demand the highest level of security. Additionally, other methods like harvesting atmospheric noise and employing quantum properties have also been explored to enhance the pool of true randomness available for cryptographic purposes. One honorable mention here are the lava lamps Cloudflare uses; they have a stack of lava lamps in their lobby and take a picture of the lava lamps at intervals, using the image to generate random numbers.

While achieving true randomness is crucial, it’s not without its challenges. One significant challenge is obtaining a sufficient entropy source, which is the foundation of randomness. Without a robust entropy source, even the best-designed HRNGs can be compromised. Entropy, often denoted as H, represents the level of randomness in a system. When the entropy is low, it indicates predictability and potential vulnerabilities. Therefore, ensuring a high and constant level of entropy is essential.

Physical attacks on HRNG hardware, tampering with entropy sources, and interference during generation are common threats. Statistical tests, such as the Chi-squared test, detect deviations from an ideal uniform distribution in generated numbers. As the need for strong cryptography rises, addressing these challenges to safeguard true randomness is crucial for secure data and communications.

Real-world applications of true randomness

The significance of true randomness in cybersecurity becomes even more evident when we delve into its real-world applications. For instance, consider its indispensable role in secure key generation for cryptographic systems. When true random numbers are employed, the generated cryptographic keys become impervious to adversaries attempting to crack encryption or gain unauthorized access. These keys serve as the digital fortresses protecting sensitive data, be it personal information, confidential corporate documents, or government secrets.

In the realm of digital signatures, true randomness is fundamental for verifying the authenticity of data and transactions. It ensures that digital signatures cannot be forged, enabling secure online contracts, electronic document authentication, and the integrity of digital records. In e-commerce, where financial transactions occur at lightning speed, true randomness is the shield that prevents financial fraud and secures the integrity of each transaction.

True randomness is also the basis of secure communication systems, especially in sensitive fields such as government, military, and medicine. The unpredictability of true random numbers is used to create unbreakable keys, ensuring that sensitive conversations and data transmissions are hidden from eavesdroppers. And as blockchain technology becomes more widespread, the need for true randomness becomes even more apparent. It ensures the security of cryptocurrencies and digital assets, prevents unauthorized access, and ensures the authenticity of blockchain transactions.

In essence, the real-world applications of true randomness are the invisible sentinels that stand guard over our most sensitive digital operations, providing an extra layer of security and integrity in an interconnected world fraught with cyber threats.

Best practices for using true randomness

As we venture deeper into the realm of true randomness in cybersecurity, it’s imperative to adhere to best practices that maximize the benefits, while minimizing risks. Maintaining a robust entropy source is crucial. Regular monitoring and testing of your entropy source to identify potential biases or weaknesses is a fundamental practice. Cryptographic standards, such as NIST SP 800-90B, offer guidance on testing entropy sources.

Additionally, cryptographic algorithms that harness true randomness should be well-vetted and adhere to industry standards to ensure their resilience against various attacks. Regularly updating and patching the hardware and software components of your random number generation systems is essential to protect against emerging threats.

Conclusion

In the world of cybersecurity, where data breaches and attacks are on the rise, achieving true randomness is a fundamental step in safeguarding sensitive information and digital operations. By implementing best practices and understanding the critical role of true randomness, we fortify our digital defenses in an increasingly interconnected world.

In the ever-evolving landscape of cybersecurity, the role of true randomness as a safeguard against digital threats cannot be overstated. From encryption and digital signatures to secure communication and blockchain technology, true randomness is the bedrock of security in the digital age. By understanding its significance and adopting best practices, we can fortify our digital defenses and ensure the confidentiality, integrity, and trustworthiness of our most sensitive data and transactions. As we move forward, embracing the power of true randomness remains paramount in our ongoing battle to protect the digital realm from those who seek to compromise our security.

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