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Privacy-Enhancing Technologies in Cryptocurrencies: Mimblewimble, Zcash, and Monero

Karolina

05 Jun 2023
Privacy-Enhancing Technologies in Cryptocurrencies: Mimblewimble, Zcash, and Monero

In the realm of cryptocurrencies, where public ledgers document transactions, privacy is a primary concern. Consequently, privacy-enhancing technologies have surfaced to grant users heightened confidentiality and anonymity. This article delves into three notable privacy-enhancing technologies: Mimblewimble, Zcash, and Monero. Utilizing groundbreaking methods, these technologies defend user privacy and amplify the security of cryptocurrency transactions. Comprehending these technologies allows individuals and businesses to make educated choices regarding their cryptocurrency utilization while protecting their sensitive data.

Table of Contents

What are Privacy-Enhancing Technologies?

Privacy and Cryptocurrencies

In the context of cryptocurrencies, privacy is of paramount importance. The essence of cryptocurrencies like Bitcoin lies in their decentralized nature and the anonymity they can potentially offer. However, many popular cryptocurrencies aren't as private as one might think. For instance, Bitcoin transactions are publicly recorded on the blockchain, and while they are associated with pseudonymous addresses, various techniques can potentially link these addresses to the identities of individuals.

A key concern for many users is the potential for their transaction history to become publicly accessible, an issue that can lead to a variety of problems, such as exposure to targeted advertising, identity theft, or even more serious personal security threats. Therefore, enhancing privacy is a critical issue in the cryptocurrency world.

Understanding Privacy-Enhancing Technologies

Privacy-enhancing technologies (PETs) in the context of cryptocurrencies are tools, protocols, and technologies designed to protect users' personal information and ensure the privacy of their transactions. They aim to reduce or eliminate the risk of unauthorized access to data, ensuring that transactions remain confidential and that users' identities are protected.

PETs can be applied at different levels and in various ways within a cryptocurrency system. They can protect the content of transactions, obscure the identity of the parties involved, or even hide the fact that a transaction took place at all.

Different cryptocurrencies implement different types of PETs, each with its own benefits and trade-offs. For instance, some may offer stronger privacy guarantees but at the cost of increased computational resources, while others may offer a balance between privacy and efficiency. The key is to choose the right tool for the job, and that's where understanding the nuances of these technologies becomes essential.

In the following sections, we will explore three distinct privacy-enhancing technologies used in Mimblewimble, Zcash, and Monero, each offering unique mechanisms to ensure transaction privacy.

Mimblewimble: Privacy Through Transaction Aggregation

What is Mimblewimble?

Mimblewimble is a privacy and fungibility-focused blockchain protocol that was introduced to the cryptocurrency community in 2016. Named after a spell from the Harry Potter series, Mimblewimble enables the creation of cryptocurrencies that enhance privacy by using a different approach to transaction structure than most other blockchains.

Rather than recording individual transactions with distinct inputs and outputs, Mimblewimble aggregates transactions, effectively 'mixing' them together. This novel approach is achieved without compromising the integrity or security of transactions, making it a fascinating case study in privacy-enhancing technologies.

How Mimblewimble Enhances Privacy

Mimblewimble achieves its privacy enhancements through a few key mechanisms. These include:

  • Transaction aggregation: In a Mimblewimble-based blockchain, transactions are aggregated together before being added to a block. The aggregation process removes the separation between individual transactions, making it impossible to trace a particular transaction within a block.
  • No addresses: Mimblewimble doesn't use traditional cryptocurrency addresses. Instead, two parties communicate directly with each other to construct a transaction, which is then broadcast to the network. This approach prevents the linkage of transactions to particular addresses, enhancing privacy.
  • Confidential Transactions: Mimblewimble uses a cryptographic technique known as Confidential Transactions. This technique hides the amount of value being transferred in each transaction, further obfuscating the transaction details from outside observers.

Despite its privacy benefits, Mimblewimble also has its trade-offs. For instance, the absence of addresses means that Mimblewimble cannot support scripts or smart contracts in their traditional form. However, for users and applications seeking strong transaction privacy, Mimblewimble offers a compelling solution.

Zcash: Privacy Through zk-SNARKs

What is Zcash?

Zcash is a privacy-focused cryptocurrency that was launched in 2016. Built on a codebase similar to Bitcoin's, Zcash distinguishes itself by its innovative use of privacy-enhancing technologies, particularly a cryptographic concept known as zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge).

Zcash provides an option for users to choose between "transparent" transactions, which work similarly to Bitcoin, and "shielded" transactions, which offer enhanced privacy. This flexibility allows users to balance their needs for transparency and privacy as required.

How Zcash Enhances Privacy

Zcash's key privacy feature is its use of zk-SNARKs. These are proofs that allow one party to prove to another that a statement is true, without revealing any additional information beyond the truth of the statement itself. Here's how zk-SNARKs are used to enhance privacy in Zcash:

  • Shielded Transactions: In a shielded transaction, the sender, receiver, and transaction amount are all encrypted. Despite this encryption, the network can verify that the transaction is valid using zk-SNARKs, without gaining any information about the transaction's details.
  • Selective Disclosure: Zcash also allows for selective disclosure. This means that a user can choose to reveal some details about a transaction, such as the amount or the parties involved, to certain individuals or entities. This feature can be useful for auditing purposes or to comply with regulatory requirements.

Zcash, through its innovative use of zk-SNARKs, offers robust privacy options for users. However, it's worth noting that the privacy features of Zcash are optional and must be actively chosen by users. Additionally, creating shielded transactions requires more computational resources than transparent transactions, which can be a consideration for users. Nonetheless, for those requiring strong privacy protections, Zcash's use of zk-SNARKs provides a powerful tool.

Read our Ultimate Guide to Zero-Knowledge Proofs: zk-SNARKs vs zk-STARKs

Monero: Privacy Through Ring Signatures and Stealth Addresses

What is Monero?

Monero, launched in 2014, is a cryptocurrency that places a strong focus on privacy, decentralization, and fungibility. Unlike some cryptocurrencies where privacy is an optional feature, Monero is designed to provide privacy by default. Monero's blockchain is constructed in such a way that no observer can tell the source, amount, or destination of transactions.

Monero achieves this high level of privacy through the use of several innovative technologies. Those include ring signatures, ring confidential transactions, and stealth addresses.

How Monero Enhances Privacy

Monero's privacy enhancements can be attributed to a combination of unique features and technologies:

Ring Signatures: This technology is used to protect the sender's identity. A ring signature is a type of digital signature where a transaction is signed and verified by a group of potential signers, forming a "ring". This approach obscures the identity of the actual signer, making it virtually impossible to determine who the actual sender of a given transaction is.

Ring Confidential Transactions (RingCT): RingCT is an extension of the concept of ring signatures. In addition to hiding the sender's identity, RingCT also conceals the transaction amount, adding another layer of privacy to Monero transactions.

Stealth Addresses: Monero uses stealth addresses to protect the receiver's identity. When a transaction is made, a one-time address is created for the recipient. This address is not linked to the actual address of the recipient, thereby protecting their privacy.

Despite its strong privacy features, Monero also comes with its own set of trade-offs. For instance, due to its privacy mechanisms, the Monero blockchain is significantly larger than that of other cryptocurrencies, which can lead to issues related to storage and synchronization. Nevertheless, for those who value privacy above all else in their transactions, Monero offers one of the most comprehensive solutions in the cryptocurrency space.

Conclusion

To sum up, addressing privacy concerns related to cryptocurrencies is made possible through privacy-enhancing technologies like Mimblewimble, Zcash, and Monero. These technologies implement unique approaches to preserve user privacy and bolster transaction security. By focusing on transaction aggregation in Mimblewimble, employing zk-SNARKs for shielded transactions in Zcash, and utilizing ring signatures alongside stealth addresses in Monero, individuals and businesses can comprehend these technologies and make educated decisions to safeguard their sensitive data while interacting with cryptocurrencies.

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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

Follow us to stay updated!

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?
Table of Contents

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

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