A Consensus Protocol for Incentivizing Contribution from Decentralized Community for Machine Learning-based Scamming Website Detection

RESEARCH CREW
17:54 08/06/2023

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 (PoAS) 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.

TIN LIÊN QUAN
In recent times, there has been a growing utilization of Machine Learning (ML) in the realm of malware detection. The Adversarial Example (AE) attack, which is widely acknowledged for undermining ML in diverse contexts, has demonstrated its effectiveness in evading or deceiving ML-based systems designed for malware detection. By ensuring...