基于机器学习的诈骗网站检测激励分散社区贡献的共识协议

Vo Truong Trung Hieu, Truong Thi Hoang Hao, Le Xuan Hoang, Doan Minh Trung, Phan The Duy, V. Pham
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引用次数: 0

摘要

网络钓鱼和诈骗网站的激增已成为对互联网用户安全的重大威胁。准确发现此类网站对于减轻其负面影响至关重要。虽然存在各种检测网络钓鱼和诈骗网站的技术,但基于机器学习的方法近年来由于其有希望的结果而获得了极大的关注。然而,确保用于训练模型的大型数据集的真实性是具有挑战性的。本文提出了一种基于区块链和ml的解决方案,该解决方案采用了一种名为“反诈骗证明”(PoSS)的共识算法,通过透明的激励机制鼓励和验证社区成员的数据贡献。我们的实验表明,VGG16与ML算法高度兼容,可以准确地对钓鱼网站进行分类,并且PoAS共识机制可以在大规模网络中很好地工作。本文还强调了使用区块链技术来激励数据贡献以更有效地检测网络钓鱼和诈骗网站的潜在好处。
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A Consensus Protocol for Incentivizing Contribution from Decentralized Community for Machine Learning-based Scamming Website Detection
The increasing proliferation of phishing and scamming websites has become a significant threat to the safety and security of internet users. Accurately detecting such websites is crucial in mitigating their negative impact. While various techniques for detecting phishing and scamming websites exist, machine learning-based approaches have gained significant attention in recent years due to their promising results. However, ensuring the authenticity of the large datasets used to train the models is challenging. This paper proposes a blockchain and ML-based solution with a consensus algorithm named The Proof of Anti-Scam (PoSS) that encourages and verifies data contributions from community members through a transparent incentivizing mechanism. Our experiments indicate that VGG16 is highly compatible with ML algorithms for accurately classifying phishing websites, and the PoAS consensus mechanism can work well in a large-scale network. This paper also highlights the potential benefits of using blockchain technology to incentivize data contributions to detect phishing and scamming websites more effectively.
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