Addressing the Quantum Threat: Post Quantum Cryptography in Blockchain


07 Jun 2023
Addressing the Quantum Threat: Post Quantum Cryptography in Blockchain

In today's increasingly digital world, the demand for secure and dependable cryptographic systems is at an all-time high. Blockchain technology has emerged as a revolutionary force in many industries, thanks to its decentralized and unchangeable characteristics. However, existing cryptographic algorithms face significant security threats from the advancing quantum computer technology. This article will discuss the significance of post-quantum cryptography in protecting blockchain networks against the impending quantum challenges.

Understanding the Quantum Threat

Quantum computers, employing quantum mechanics principles, promise unprecedented computational capabilities that may render existing cryptographic algorithms ineffective. Conventional encryption techniques, such as RSA and ECC (Elliptic Curve Cryptography), depend on the complexity of specific mathematical problems for security. Quantum computers, however, hold the potential to solve these problems exponentially faster, consequently dismantling the cryptographic foundation that supports blockchain networks.

Various risks are associated with quantum computers' impact on blockchain networks. The most prominent risk includes compromising the security of digital assets managed within blockchain systems. Transactions, smart contracts, and private keys that depend on cryptographic algorithms might become susceptible to quantum computer attacks. As quantum technology progresses, adversaries may decrypt encrypted information, tamper with transactions or counterfeit digital signatures – leading to severe financial and reputational damage for those relying on blockchain networks.

Additionally, blockchain's decentralized and transparent nature makes it particularly prone to quantum attacks. Given that blockchain transactions are publicly accessible, a quantum computer-equipped attacker could retroactively decrypt past transactions. This undermines the core principles of immutability and trust that underpin blockchain technology.

To address this urgent and critical challenge posed by the quantum threat, it's vital to take a proactive approach. Incorporating post-quantum cryptography into blockchain systems is crucial for maintaining long-term security and sustainability of these networks. By utilizing cryptographic algorithms that can withstand quantum computer attacks, blockchain networks can preserve data confidentiality, integrity, and the authenticity of transactions and digital assets. Even in light of quantum advancements.

The subsequent sections of this article will investigate the practicality of implementing post-quantum cryptography in blockchain systems. We will explore specific solutions, evaluate their performance implications, and emphasize the initiatives being taken towards standardization and compatibility. Through this examination, we seek to contribute to the comprehensive understanding and adoption of post-quantum cryptography as a vital defense against the quantum threat within the blockchain environment.

Foto: Eric Lukero/Google

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Exploring the Viability of Post-Quantum Cryptography in Blockchain

Implementing post-quantum cryptography within blockchain systems is a multifaceted effort demanding a thorough examination of numerous aspects. With the impending emergence of quantum computers, shifting to post-quantum cryptographic algorithms entails its own set of challenges. This section delves into the practicality of incorporating post-quantum cryptography into blockchain and scrutinizes the advancements in this domain.

Investigations and Progress in Algorithms

Intensive investigations are being undertaken by cryptographic researchers and organizations to explore post-quantum cryptographic algorithms that can withstand attacks from quantum computers. Lattice-based, code-based, and multivariate-based schemes are some examples that aim to preserve security even against quantum adversaries. Meticulous research and evaluations are performed to assess the mathematical underpinnings, security attributes, and practicality of these algorithms for actual implementation.

Concerns about Performance

A significant hurdle while adopting post-quantum cryptography in blockchain lies in the performance costs arising from these novel algorithms. Frequently, post-quantum cryptographic algorithms demand higher computational power and memory compared to conventional cryptographic algorithms. Such heightened computational requirements can influence blockchain networks' efficiency and scalability, possibly altering transaction throughput and consensus mechanisms. Nevertheless, ongoing investigations and optimization endeavors seek to address these performance issues, making post-quantum cryptography more practical for blockchain systems.

Integration with Current Blockchain Protocols

Modifications and revisions to existing protocols may be essential for integrating post-quantum cryptography into blockchain networks. Blockchain platforms like Ethereum proactively investigate incorporating post-quantum cryptographic algorithms through initiatives such as EIP-2938. The objectives include ensuring congruity and consensus among network users while establishing a trajectory towards quantum-resistant security.

The Role of Standardization and Interoperability

Standardization holds paramount importance when adopting and executing post-quantum cryptography within blockchain systems. Institutions like the National Institute of Standards and Technology have introduced competitions and evaluations to pinpoint and standardize post-quantum cryptographic algorithms. This standardization process confirms interoperability, cultivates trust, and facilitates widespread utilization of these algorithms across varied blockchain networks.

Test Implementations and Real-Life Evaluation

Multiple pilot projects and initiatives are launched to gauge the feasibility and practicability of p-q cryptography in actual blockchain settings. These implementations aid in pinpointing potential difficulties, performance consequences, and security considerations associated with merging post-quantum cryptography into existing blockchain infrastructures. The knowledge acquired from these pilot projects contributes to refining and enhancing post-quantum cryptographic algorithms for appropriateness within blockchain networks.

Evaluating Solutions for Post Quantum Cryptography Signature Verification

Hash-Based Signatures

Signature schemes based on hash functions, such as Lamport and Winternitz one-time signature schemes, provide post-quantum security due to the computational difficulty of hash functions. Although these schemes offer robust security assurances against quantum attacks, their large signature sizes make them less practical for bandwidth-restricted blockchain networks. Hash-based signatures are appropriate for situations where signature size is not a major concern, like in offline or low-bandwidth contexts.

Lattice-Based Signatures

BLISS and Dilithium schemes are examples of lattice-based signature schemes that leverage the difficulty of specific mathematical problems on lattices to ensure post-quantum security. These schemes have smaller signature sizes than hash-based signatures, rendering them more appropriate for resource-limited blockchain networks. Lattice-based signatures strike a good balance between security and efficiency; however, lattice operations' complexity can affect their performance.

Code-Based Signatures

Error-correcting codes are utilized in code-based signature schemes like McEliece and Niederreiter to provide quantum attack resistance. These schemes have small signature sizes and rapid signature generation capabilities, making them appealing for high-throughput blockchain systems. Nevertheless, code-based signatures may have larger public key sizes compared to other p-q cryptography signature schemes. This can influence storage requirements.

Multivariate-Based Signatures

Rainbow and HFE are multivariate-based signature schemes that rely on the difficulty of solving multivariate polynomial equation systems for post-quantum security. These schemes provide compact signature sizes and efficient signature verification, making them suitable for resource-limited blockchain networks. However, multivariate-based signatures can be prone to specific attacks, such as the Gröbner basis attack, necessitating cautious parameter selection and security analysis.

Hybrid Approaches

The integration of multiple post-quantum cryptography signature schemes characterizes hybrid approaches to capitalize on their respective benefits and address their shortcomings. A hybrid scheme can, for instance, merge a hash-based signature scheme for initial verification with a lattice-based or code-based signature scheme for additional validation. Hybrid approaches strive to deliver a sturdy and adaptable solution that harmonizes security, efficiency, and compatibility with existing cryptographic infrastructure.

When choosing a post-quantum cryptography signature verification solution for blockchain, it is critical to evaluate factors like security, signature size, computational efficiency, storage requirements, and protocol compatibility. The selection of a particular scheme will be determined by the blockchain network's specific demands and limitations.

It is important to note that it remains a developing field, with ongoing research and progress constantly enhancing signature schemes' efficiency and security. Keeping abreast of the latest developments and seeking advice from cryptographic experts is essential when making informed decisions regarding the adoption and implementation of it signature verification solutions in blockchain systems.

Blockchain developers and organizations can choose suitable post-quantum cryptography signature verification schemes by meticulously evaluating and comparing available options, ensuring robust defense against quantum attacks while maintaining optimal performance and scalability levels.

Moving Towards Standardization and Compatibility in Post-Quantum Cryptography:

The significance of standardization grows, enabling interoperability and compatibility among diverse blockchain networks. The adoption of post-quantum cryptographic algorithms and secure digital communication relies heavily on standardization. In this section, we will explore standardization's importance and the developments made thus far.

Standardization of Post-Quantum Cryptography by NIST

  • The National Institute of Standards and Technology (NIST) is at the forefront of standardizing post-quantum cryptography.
  • In 2017, NIST launched a public contest inviting submissions for post-quantum cryptography candidate algorithms across various categories, such as encryption, signature, and key exchange.
  • This contest seeks to pinpoint and select quantum-resistant algorithms that are efficient, robust, and can be widely implemented across various applications and sectors.
  • Currently in its final stages, the competition is narrowing down several algorithms for potential post-quantum cryptography standards.

Challenges in Interoperability and Compatibility:

  • Attaining compatibility and interoperability among different cryptographic algorithms and blockchain networks is a complicated feat.
  • Current blockchain systems often depend on specific cryptographic protocols and primitives that may not align with post-quantum algorithms.
  • A seamless shift demands thorough examination of backward compatibility, migration strategies, and consensus from participants.
  • Collaborative initiatives are essential for creating standards and protocols capable of smoothly integrating post-quantum cryptographic algorithms into existing blockchain networks.

Advantages of Standardization for Blockchain Networks:

  • The adoption of post-quantum cryptography by blockchain networks brings numerous benefits through standardization.
  • A common framework for cryptographic operations ensures interoperability, enabling secure communication among various blockchain platforms.
  • Algorithms undergoing standardization are rigorously assessed by the cryptography community, instilling confidence in their reliability and security.
  • Additionally, standardized frameworks simplify the integration of new cryptographic technologies and future enhancements.

Expanding Post-Quantum Cryptography to Additional Blockchain Networks:

The implementation of post-quantum cryptography spans beyond any single blockchain network or protocol. To guarantee long-term security and robustness of their systems, multiple blockchain platforms investigate ways to integrate post-quantum cryptographic algorithms as the quantum threat emerges. In this section, we will examine ongoing efforts to introduce post-quantum cryptography to other blockchain networks.

Ethereum and Post-Quantum Cryptography:

  • As one of the most prevalent blockchain platforms, Ethereum actively investigates the adoption of post-quantum cryptographic algorithms.
  • The Ethereum Foundation and its community engage in ongoing dialogue and partnerships with experts to evaluate the feasibility and appropriateness of various post-quantum algorithms for Ethereum's infrastructure.
  • Developing a roadmap for incorporating post-quantum cryptography that considers the potential impact on performance, scalability, and backward compatibility is the ultimate goal.

Other Blockchain Networks:

  • Outside of Ethereum, additional blockchain networks recognize the value of post-quantum cryptography.
  • Platforms like Hyperledger, Corda, and Polkadot proactively explore how quantum-resistant algorithms can be integrated into their protocols to counter emerging threats.
  • Collaborative work focuses on assessing and testing different post-quantum cryptographic solutions within real-world blockchain settings, taking into account factors such as performance, security, and infrastructure compatibility.

By expanding post-quantum cryptography to various blockchain networks, the goal is to construct a more secure and future-proof foundation for decentralized applications and digital asset transactions. Collaboration between standardization organizations, cryptographic experts, and blockchain platforms is vital in achieving


In conclusion, post-quantum cryptography offers a promising solution to address the quantum threat in blockchain. Efforts are underway to develop efficient and secure algorithms for post-quantum signature verification. Standardization and compatibility initiatives are crucial for seamless integration across different blockchain networks. The industry is actively working towards extending pq cryptography to ensure the security of blockchain transactions.

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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes


The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.


  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.


Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics


The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.


What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.