In our fast-paced and constantly evolving digital landscape, information security is an imperative. As data flows across networks and digital boundaries, and is preyed upon by malicious intent, the need to protect sensitive information has never been greater.
Cryptography, the art and science of encrypting and decrypting information, plays a pivotal role in protecting data from unauthorized access, ensuring privacy, and maintaining the integrity of digital transactions.
Let’s take a dive into the traditional methods in cryptography:
Traditional cryptography has been an invaluable tool in history, serving as a means to secure sensitive information from prying eyes. At its core, cryptography aims to transform readable data (plaintext) into an unintelligible form (ciphertext) using mathematical algorithms and secret keys. The correct decryption key, held only by authorized parties can restore the ciphertext to its original plaintext form.
Traditionally, ciphers scramble messages to hide their meaning from eavesdroppers. The keys act like unique passwords, and can be changed in agreement with the receiver, making it difficult for outsiders to crack the code even if they know the general encryption technique. However, a ‘key’ weakness exists – both parties need to share this secret key securely before exchanging messages.
Some common techniques in traditional cryptography –
- Symmetric Cryptography: A single shared key is used for both encryption and decryption processes. Examples of widely-used symmetric algorithms include the Advanced Encryption Standard (AES) and the Data Encryption Standard (DES). Symmetric cryptography is known for its efficiency and speed, making it suitable for secure data transmission and bulk data encryption.
- Asymmetric Cryptography: Also known as public-key cryptography, this employs a pair of mathematically related keys – a public key for encryption and a private key for decryption. This approach allows for secure key distribution and enables essential applications like digital signatures and key exchange protocols. Notable asymmetric algorithms include the Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC).
- Hash Functions: Hash functions are one-way cryptographic algorithms that take an input of arbitrary length and produce a fixed-size output, known as a hash or digest. These functions are designed to be computationally infeasible to invert, making them useful for data integrity verification, password storage, and digital signatures. Common hash functions include SHA-256, SHA-3, and MD5 (now considered insecure for most applications).
Programmable Cryptography
While traditional cryptography has served us well, the rapidly evolving digital landscape and the ever-increasing sophistication of cyber threats have necessitated more versatile solutions. As new cryptanalytic techniques emerge, once-secure algorithms become vulnerable, and compliance requirements shift, the need for a dynamic and future-proof approach to cryptography becomes important.
This need has given rise to the concept of programmable cryptography, also known as cryptographic agility or crypto-agility.
Programmable cryptography is a paradigm that enables systems and applications to support multiple cryptographic algorithms, protocols, and key strengths seamlessly. It allows for the flexible and dynamic selection, configuration, and updating of cryptographic primitives and mechanisms without requiring significant changes to the underlying system architecture or code.
Imagine cryptography not as a set of pre-defined tools, but as a flexible framework allowing you to build custom security solutions.
Programmable cryptography achieves this through – High Level Abstraction, Composability and Expressiveness
The primary goals of programmable cryptography include:
- Future-proofing: As new cryptographic algorithms and protocols are developed, or existing ones become vulnerable, programmable cryptography enables systems to adapt and switch to more secure alternatives without extensive modifications, ensuring long-term security and compliance.
- Compliance, Interoperability: Different industries, organizations, or use cases may have varying cryptographic requirements or standards. Programmable cryptography allows systems to comply with diverse regulations and maintain interoperability by supporting multiple cryptographic mechanisms.
- Performance and Optimization: Different cryptographic algorithms may have varying performance characteristics depending on the use case. Programmable cryptography allows the selection of the most appropriate algorithm for a given scenario, optimizing for factors such as throughput, latency, or energy consumption.
The Difference
Traditional cryptography focuses on specific algorithms for encrypting, decrypting, etc. Programmable cryptography, on the other hand, utilizes high-level abstraction, in which desired security goals are defined – zero-knowledge, confidentiality, integrity – without delving into the cryptographic primitives. Other features which differentiate this form traditional methods are composability – allowing chaining, layering of cryptographic primitives – and expressiveness, which frees developers from the bounds of predefined set of operations.
Core of Programmable Cryptography
By abstracting cryptographic primitives and providing a unified interface, programmable cryptography allows developers to seamlessly integrate and configure various cryptographic algorithms and protocols within their applications, enabling adaptability and future-proofing.
Examples of cryptographic primitives are the random number generators, entropy sources, and basic memory or math operations which are required by the cryptographic algorithms. For example, the Pseudo-Random Number Generator (PRNG) functions that generate random numbers from some seed value are quite important to the security of your cryptography.
Popular primitives used in modern programmable cryptography are Symmetric Key Algorithms (AES), Assymetric Key (RSA, Elliptic Curve), Hash Functions(SHA256), RNGs.
Building upon these primitives, advanced techniques in programmable cryptography are developed – Homomorphic encryption, Zero-knowledge proofs, and Multi-party computation.
Let us look into the basics of these methods.
Homomorphic Encryption enables us to perform operations and calculations on encrypted data without the need of decrypting it. For example, consider a cloud service provider that needs to perform analytics on sensitive data stored by its clients. With homomorphic encryption, the clients can encrypt their data and send it to the cloud service, which can then perform the desired computations directly on the encrypted data, without ever having access to the plaintext. The results of these computations remain encrypted, ensuring data privacy and confidentiality.
Zero-Knowledge Proofs allow one party to prove to another party that a statement is true, wihtout revealing anything except the truth of the statement. Imagine a scenario where you want to prove that you have a valid ticket for an event without revealing the actual ticket details. With zero-knowledge proofs, you can construct a cryptographic proof that demonstrates the validity of your ticket without disclosing the ticket itself or any other sensitive information.
Multi-Party Computation (MPC), allows parties to collaborate on a computation without revealing their individual inputs to each other or to a third party. Imagine you and your friends want to compute the average score on a test, but no one wants to reveal their individual scores. With MPC, each person could provide their score in a secure, encrypted manner, and then all the inputs are processed together using a special protocol. At the end, everyone learns the average score, but no one’s individual score is revealed to the others.
Technical Underpinnings
Behind the scenes of programmable cryptography lies a world of intricate mathematics and ingenious algorithms, weaving together the tapestry of security and privacy that underpins our digital lives. While the concepts may seem abstract, their practical implications are far-reaching and profound.
Coming to the technical concepts of programmable cryptographic methods,
At the heart of homomorphic encryption lies the concept of mathematical structures like number theory and lattices. These structures provide the foundation for constructing encryption schemes that exhibit a unique property – homomorphic behavior. This simply means that the mathematical operations performed on the encrypted data (ciphertext) mirror the operations that would be done on the original data (plaintext), but without ever decrypting it.
Homomorphic encryption:
These come in various flavours, each offering a different level of computational capability. Partially Homomorphic Encryption (PHE) shines in tasks where either addition or multiplication is required, making it ideal for financial data analysis. Somewhat Homomorphic Encryption (SHE) ups the game by supporting both addition and multiplication, but with a limit on the number of operations due to its complexity. Finally, Fully Homomorphic Encryption (FHE) represents the ultimate goal, allowing unlimited arithmetic operations on encrypted data. However, FHE schemes are currently computationally expensive and not yet ready for prime time in most applications.
Mathematical Foundations of HE lie in Number theory – modular arithmetic and prime number properties for constructing HE schemes – and Lattices, which are geometric arrangements of points used in advanced FHE constructions.
Zero-Knowledge Proofs:
ZKP is a powerful cryptographic tool that allows one party (the prover) to convince another party (the verifier) that they possess certain knowledge, without revealing any additional information beyond the validity of the claim itself. It’s like having a magic handshake that confirms membership in a secret club without disclosing the club’s secret code.
Here’s how a simple ZKP protocol works :
1) Challenge: The verifier, akin to a skeptical bouncer, throws a random challenge at the prover.
2) Responding with Proof: The prover, armed with their secret knowledge, uses the challenge to generate a response that doesn’t reveal the secret itself.
3) Verification Dance: The verifier takes the prover’s response and the original challenge, running them through a verification process. If the process validates, the verifier is convinced, with high probability, that the prover holds the secret knowledge.
This back-and-forth exchange, with the verifier constantly throwing curveballs, ensures the prover can’t simply cheat by forging a response. The beauty lies in the fact that even after numerous rounds of challenge and response, the verifier learns nothing more than the truth of the claim being proven.
The basic ZKP concept branches out into various specialized protocols, each catering to different needs. Here are two prominent examples:
SNARKS(Succinct Non-Interactive Arguments of Knowledge): These offer a compact proof size and verification process, making them ideal for applications where efficiency is crucial.
Zk-SNARKs at their base depend on elliptic curves. These curves operate on the assumption that finding the discrete logarithm of a random elliptic curve element with respect to a publicly known base point is infeasible.
STARKS(Scalable Transparent Arguments of Knowledge): These prioritize transparency, allowing anyone to verify the correctness of the proof without needing to trust a specific setup. This comes at the cost of slightly larger proof sizes compared to SNARKs.
STARKS are based upon hash functions, which brings some resistance as it is.
ZK-Proofs find vast applications in the fields of Blockchain Scalability, Privacy, Digital Rights Management.
MPC operates through sophisticated cryptographic protocols. These protocols ensure the privacy of each participant’s data while enabling the collaborative computation.
Here’s a simplified glimpse into how these protocols might function:
- Secret Sharing: Each participant’s data is split into secret shares and distributed amongst all participants. No single participant possesses the complete data.
- Joint Computation: The participants follow the secure protocol, performing mathematical operations on their secret shares instead of their original data.
- Reconstructing the Result: Once the computation is complete, the secret shares of the final result are combined using a special technique to reveal the outcome without revealing any individual’s private data.
MPC brings enhanced privacy, trustless collaboration and secure data analysis of senstiive data.
Real World Applications of Programmable Cryptography
These advanced techniques are not merely theoretical constructs; they are already finding practical applications across various sectors, from finance and healthcare to the Internet of Things (IoT).
In the realm of finance and banking, programmable cryptography is enabling privacy-preserving analytics, where banks and financial institutions can leverage techniques like multi-party computation and homomorphic encryption to perform collective risk analysis, fraud detection, or regulatory compliance checks without exposing sensitive customer data to each other or third parties.
The healthcare industry is also in, empowering medical researchers to collaborate on sensitive patient data from multiple sources, enabling large-scale studies and analyses without compromising individual privacy. Patients can selectively share their encrypted medical records with healthcare providers or researchers, granting access to specific portions of data through advanced access control mechanisms and zero-knowledge proofs, without revealing unnecessary personal information.
The Internet of Things (IoT) is another domain where programmable cryptography is making its mark. With lightweight cryptography frameworks, IoT devices with limited computational resources and energy constraints can leverage cryptographic algorithms tailored to their specific requirements, ensuring secure communication and data protection while optimizing for performance and energy efficiency.
Beyond these sectors, programmable cryptography is poised to revolutionize digital identity management, enabling secure and privacy-preserving authentication mechanisms. Zero-knowledge proofs and advanced cryptographic protocols can allow individuals to prove their identity or attributes (e.g., age, citizenship) without revealing unnecessary personal information, enhancing privacy while maintaining verifiability.
The benefits of programmable cryptography are far-reaching and profound. It enhances privacy and data protection, enabling organizations and individuals to perform computations and analyses on sensitive data without compromising confidentiality. It improves security and future-proofing by supporting multiple cryptographic algorithms and protocols, allowing for seamless transitions to more secure alternatives as threats emerge or existing algorithms become vulnerable.
The Future
Programmable cryptography has an exciting and widely-used future in the making.
An interesting prospect is the development of fully homomorphic encryption (FHE) schemes with improved efficiency and practicality. While existing FHE schemes have demonstrated the ability to perform arbitrary computations on encrypted data, their computational complexity has been a significant barrier to widespread adoption. They are commercially unfeasible due to their slow computation and accuracy problems. Betterments are underway, such as lattice-based cryptography, to develop more efficient FHE schemes that can enable practical secure computation in real-world scenarios.
ZKP protocols are finding great interest in the Web3 realm. There has always been cncern of privacy and security due to frequent attacks on decentralized networks. ZKPs, with their principles of completeness, soundness and zero-knowledge, will help in verification of transactions without leakage of details.
As of now, the major focus has been on Zk-SNARKS, due to their earlier emergence with respect to STARKS. As a results the former has extensive resources in terms of libraries, projects and developers working on it, as well as significantly lower gas requirements.
STARKS have their own use cases, and they have supported by the ETHEREUM foundation, in hopes of further developement.
The field of secure multi-party computation (MPC) is also witnessing interest, with researchers exploring novel protocols and optimizations to improve efficiency, scalability, and fault tolerance. For digital assets, MPC has become a standard, as seen by its adoption in BNY Mellon and Revolut. Nippon Telegraph and Telephone is a leading patent filer in secure multi-party computing.
Furthermore, the advent of quantum computing poses both challenges and opportunities for programmable cryptography. While quantum algorithms like Shor’s algorithm have the potential to break widely used public-key cryptographic algorithms, such as RSA and ECC, the threat of quantum computing has spurred intensive research into quantum-resistant cryptographic algorithms. Lattice-based cryptography, code-based cryptography, and multivariate cryptography are among the promising candidates being explored as potential replacements for traditional public-key algorithms in a post-quantum world.
Moreover, the integration of programmable cryptography into emerging technologies like the Internet of Things (IoT) and blockchain could revolutionize the way we approach security and trust in decentralized systems. Secure and verifiable computation could enable trustless execution of smart contracts, while privacy-preserving authentication and data sharing could foster a new era of secure and privacy-respecting IoT applications.
However, as with any transformative technology, the journey ahead is not without its challenges. Scalability, usability, and the need for robust security proofs and formal verification will be crucial considerations as these technologies transition from academic research to real-world deployment. Additionally, the broader societal implications of programmable cryptography, including issues of governance, ethics, and the potential for misuse, will need to be carefully navigated.
For people interested in learning in depth on the methods of Programmable Cryptography, here is a guide:
In the realm of zero-knowledge proofs, libraries like Zcash’s bellman and Ethereum’s zk-SNARK implementation offer powerful tools for creating and verifying succinct non-interactive zero-knowledge proofs.
For secure multi-party computation (MPC), frameworks like MP-SPDZ (Multi-Party Secure Parallel Distributed Computation) and Obliv-C provide efficient implementations of MPC protocols, enabling developers to explore secure collaborative analytics, privacy-preserving machine learning, and other privacy-enhancing applications.
Beyond these specialized libraries, more frameworks like OpenFHE (Open Federated Homomorphic Encryption) and Lattigo offer a unified approach to programmable cryptography, integrating techniques such as homomorphic encryption, zero-knowledge proofs, and secure multi-party computation under a single umbrella.
For those seeking a more hands-on approach, educational resources like the MIT Open Courseware on Cryptography and Lattice-based Cryptography, provides great learning opportunities.
Further Reading on Programmable Cryptography:
Homomorphic Encryption – https://www.splunk.com/en_us/blog/learn/homomorphic-encryption.html
Zk-SNARKS vs STARKS – https://consensys.io/blog/zero-knowledge-proofs-starks-vs-snarks
MPC – https://eprint.iacr.org/2020/300.pdf
