FIRST: FrontrunnIng Resilient Smart ConTracts
- URL: http://arxiv.org/abs/2204.00955v3
- Date: Wed, 24 Apr 2024 22:56:55 GMT
- Title: FIRST: FrontrunnIng Resilient Smart ConTracts
- Authors: Emrah Sariboz, Gaurav Panwar, Roopa Vishwanathan, Satyajayant Misra,
- Abstract summary: In some cases, the inherently transparent and unregulated nature of cryptocurrencies leads to verifiable attacks on users of these applications.
One such attack is frontrunning, where a malicious entity leverages the knowledge of currently unprocessed financial transactions.
We propose FIRST, a framework that prevents frontrunning attacks and is built using cryptographic protocols.
- Score: 3.5061201620029876
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Owing to the meteoric rise in the usage of cryptocurrencies, there has been a widespread adaptation of traditional financial applications such as lending, borrowing, margin trading, and more, to the cryptocurrency realm. In some cases, the inherently transparent and unregulated nature of cryptocurrencies leads to attacks on users of these applications. One such attack is frontrunning, where a malicious entity leverages the knowledge of currently unprocessed financial transactions submitted by users and attempts to get its own transaction(s) executed ahead of the unprocessed ones. The consequences of this can be financial loss, inaccurate transactions, and even exposure to more attacks. We propose FIRST, a framework that prevents frontrunning attacks, and is built using cryptographic protocols including verifiable delay functions and aggregate signatures. In our design, we have a federated setup for generating the public parameters of the VDF, thus removing the need for a single trusted setup. We formally analyze FIRST, prove its security using the Universal Composability framework and experimentally demonstrate the effectiveness of FIRST.
Related papers
- The Latency Price of Threshold Cryptosystem in Blockchains [52.359230560289745]
We study the interplay between threshold cryptography and a class of blockchains that use Byzantine-fault tolerant (BFT) consensus protocols.
Existing approaches for threshold cryptosystems introduce a latency overhead of at least one message delay for running the threshold cryptographic protocol.
We propose a mechanism to eliminate this overhead for blockchain-native threshold cryptosystems with tight thresholds.
arXiv Detail & Related papers (2024-07-16T20:53:04Z) - Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective [53.24281798458074]
Face Recognition Systems (FRS) have increasingly integrated into critical applications, including surveillance and user authentication.
Recent studies have revealed vulnerabilities in FRS to adversarial (e.g., adversarial patch attacks) and backdoor attacks (e.g., training data poisoning)
arXiv Detail & Related papers (2024-05-21T13:34:23Z) - LookAhead: Preventing DeFi Attacks via Unveiling Adversarial Contracts [15.071155232677643]
Decentralized Finance (DeFi) incidents have resulted in financial damages exceeding 3 billion US dollars.
Current detection tools face significant challenges in identifying attack activities effectively.
We propose a new direction for detecting DeFi attacks that focuses on identifying adversarial contracts.
arXiv Detail & Related papers (2024-01-14T11:39:33Z) - FRAD: Front-Running Attacks Detection on Ethereum using Ternary
Classification Model [3.929929061618338]
Front-running attacks, a unique form of security threat, pose significant challenges to the integrity of blockchain transactions.
In these attack scenarios, malicious actors monitor other users' transaction activities, then strategically submit their own transactions with higher fees.
We introduce a novel detection method named FRAD (Front-Running Attacks Detection on using Ternary Classification Model)
Our experimental validation reveals that the Multilayer Perceptron (MLP) classifier offers the best performance in detecting front-running attacks, achieving an impressive accuracy rate of 84.59% and F1-score of 84.60%.
arXiv Detail & Related papers (2023-11-24T14:42:29Z) - PTTS: Zero-Knowledge Proof-based Private Token Transfer System on Ethereum Blockchain and its Network Flow Based Balance Range Privacy Attack Analysis [0.0]
We propose a Private Token Transfer System (PTTS) for the public blockchain.
For the proposed framework, zero-knowledge based protocol has been designed using Zokrates and integrated into our private token smart contract.
In the second part of the paper, we provide security and privacy analysis including the replay attack and the balance range privacy attack.
arXiv Detail & Related papers (2023-08-29T09:13:31Z) - Blockchain Large Language Models [65.7726590159576]
This paper presents a dynamic, real-time approach to detecting anomalous blockchain transactions.
The proposed tool, BlockGPT, generates tracing representations of blockchain activity and trains from scratch a large language model to act as a real-time Intrusion Detection System.
arXiv Detail & Related papers (2023-04-25T11:56:18Z) - ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep
Neural Network and Transfer Learning [80.85273827468063]
Existing machine learning-based vulnerability detection methods are limited and only inspect whether the smart contract is vulnerable.
We propose ESCORT, the first Deep Neural Network (DNN)-based vulnerability detection framework for smart contracts.
We show that ESCORT achieves an average F1-score of 95% on six vulnerability types and the detection time is 0.02 seconds per contract.
arXiv Detail & Related papers (2021-03-23T15:04:44Z) - BLOCKEYE: Hunting For DeFi Attacks on Blockchain [14.036894994367598]
Decentralized finance, i.e., DeFi, has become the most popular type of application on many public blockchains.
We propose a real-time attack detection system for DeFi projects on the blockchain.
arXiv Detail & Related papers (2021-03-04T07:41:12Z) - Detecting Malicious Accounts showing Adversarial Behavior in
Permissionless Blockchains [4.506782035297339]
Malicious activities have been flagged in multiple permissionless blockchains such as bitcoin.
We aim at automatically flagging blockchain accounts that originate such malicious exploitation of accounts of other participants.
We identify a robust supervised machine learning (ML) algorithm that is resistant to any bias induced by an over representation of certain malicious activity.
arXiv Detail & Related papers (2021-01-28T10:33:50Z) - Quantum Multi-Solution Bernoulli Search with Applications to Bitcoin's
Post-Quantum Security [67.06003361150228]
A proof of work (PoW) is an important cryptographic construct enabling a party to convince others that they invested some effort in solving a computational task.
In this work, we examine the hardness of finding such chain of PoWs against quantum strategies.
We prove that the chain of PoWs problem reduces to a problem we call multi-solution Bernoulli search, for which we establish its quantum query complexity.
arXiv Detail & Related papers (2020-12-30T18:03:56Z) - Regulation conform DLT-operable payment adapter based on trustless -
justified trust combined generalized state channels [77.34726150561087]
Economy of Things (EoT) will be based on software agents running on peer-to-peer trustless networks.
We give an overview of current solutions that differ in their fundamental values and technological possibilities.
We propose to combine the strengths of the crypto based, decentralized trustless elements with established and well regulated means of payment.
arXiv Detail & Related papers (2020-07-03T10:45:55Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.