Enhancing Blockchain Security through AI: ‘Lightning Cat’ Initiative

In the blockchain world, smart contracts are a critical component that powers everything from simple meme coins to complex decentralized finance (DeFi) platforms. However, these automated contracts are constantly at risk of cyberattacks, resulting in significant financial and reputational damage. One group of researchers advocates the use of artificial intelligence as the most effective defense against these vulnerabilities.

In this study, we introduce ‘Lightning Cat’, an innovative AI tool designed to proactively identify weaknesses in smart contracts. The tool, described in a research paper titled “A Deep Learning-Based Solution for Smart Contract Vulnerability Detection,” is a departure from traditional analysis tools. Similar to training bots in Solidity, the programming language used in smart contracts instead of English, deep learning is leveraged to accurately identify potential problems.

Lightning Cat’s efficiency is based on three advanced deep learning models: CodeBERT, LSTM, and CNN. Trained on a dataset containing thousands of vulnerable contracts, the model shows surprising capabilities. In particular, the CodeBERT model outperforms static detection tools with an f1 score of 93.53% and skillfully understands the syntax and semantics of code, serving as a reliable auditor for blockchain technology.

double edged sword

Despite its advantages, the Lightning Cat is not without its risks. Researchers acknowledge that while this is useful for strengthening smart contract security, it is a “double-edged sword” that could potentially be exploited by malicious entities to find and exploit bugs. To counter this, researchers emphasize the need for developers to engage in secure coding practices, regular code audits, and secure coding training. It also emphasizes the importance of adopting a responsible vulnerability disclosure policy, advising that discovered vulnerabilities should first be reported privately to the relevant parties.

Looking back at past events such as the 2016 DAO attack, which resulted in significant Ethereum theft due to a re-entrancy vulnerability, and the 2018 BEC smart contract fiasco due to an integer overflow, the importance of these AI-based security measures becomes clear. These events not only led to financial losses, but also had far-reaching implications, including a split in the Ethereum blockchain.

Lightning Cat’s role extends beyond simple detection. It serves as an important tool for developers to test and secure their creations before deployment. David Schwed, COO of Halborn, highlighted the potential of these tools in preventing DeFi attacks in an interview with Decrypt, noting that standard Web2 security oversight causes many breaches.

The initiative is part of a larger movement to integrate AI and blockchain technology to enhance software security. This includes the development of AI and blockchain-based decentralized software testing systems that combine the efficiency of deep learning with the transparency and trustworthiness of blockchain. Not only are these systems faster at detecting vulnerabilities, but they are also suitable for remote work scenarios. We present a holistic solution for secure code development and testing in a distributed framework by leveraging the InterPlanetary File System (IPFS) for effective data storage.

yPreservation prediction

No discussion of AI would be complete without mentioning one of the most promising projects in the field currently. yPredict, a blockchain-based initiative, is revolutionizing transaction analytics with its AI-based approach. This project stands out because it provides actionable insights derived from data with the goal of improving users’ trading choices. What makes it unique is the validation of all trading models from the yPredict DAO community.

The yPredict platform represents the forefront of trading research and analytics, leveraging artificial intelligence and machine learning to examine financial markets and extract valuable data. The result is a comprehensive set of forecasting tools designed to improve your trading methodology.

The project white paper highlights that predicting market trends is becoming increasingly difficult. Numerous platforms are now using sophisticated algorithms for cryptocurrency trading, which has a significant impact on the cryptocurrency price structure. This situation presents traders with the challenge of obtaining reliable information.

In these scenarios, traders often lack a statistical edge and rely on news and public sentiment. yPredict addresses this gap by providing traders with a variety of tools that provide analytical indicators and data-driven insights. The platform also introduces a new prediction market. In this market, financial data experts can market predictive models or trading signals, and traders can subscribe to utilize these tools. All of these transactions are facilitated using the platform’s proprietary digital token, YRED, creating a unique space for AI data experts and cryptocurrency traders alike.

The YPRED token is the core of the yPredict ecosystem. YPRED tokens, created on the Polygon network and compatible with Ethereum, have several uses.

• Free access to the yPredict analytics platform for YPRED token holders.
• YPRED tokens can be used to purchase subscriptions within the yPredict prediction market.
• An option for investors to earn attractive Annual Percentage Yield (APY) by staking YPRED tokens.
• A liquidity pool backed by 10% of platform profits ensures consistent investment returns.

Pre-sale Opportunity

yPredict pre-sale will begin in February 2023 and is currently in its final stages. Not surprisingly, it became one of the following: Best Cryptocurrency Presale Of the year. The platform has already raised nearly $1.5 million in just over two months.

You can participate in the yPredict presale here.

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