Blockchain and Machine Learning Based Approach to Prevent Phishing Attacks

Abstract

Communication using Emails, SMS, and various social media platforms have become an important part of life when dealing professionally and socially. Due to their large uses, these platforms also have gained the attention of hackers to carry out sophisticated attacks by sending out messages that contains Malicious content (Generally URL). Huge numbers of Phishing emails are sent daily. Over the past few years, various Machine Learning based techniques were introduced to identify Phishing Attacks still, the count and loss due to Phishing is increasing daily. Blockchain technology is gaining a lot of attention in Security Domain over the past few years, in this state of art authors have proposed a blockchain-based system integrated with a Machine Learning model to identify and prevent Phishing content that is sent out on various messaging platforms. For implementation purposes Ethereum Based platform and from a Machine Learning perspective Classification based Gradient Boost Algorithm and Support Vector Machine Algorithm was used. The proposed systems talk about, sender while sending out a message to a recipient should pay some ETH (cryptocurrency) and if after content validation through ML models the message is found to be legitimate, the ETH value that the sender had paid will be refunded back, else if ML models identify the content as Phishing, then there will be no refund. Even though after validation through the ML model if the recipient marks the email as SPAM or reports the same as Suspicious then also there will be no refund. This eventually will reduce the traffic and will make hackers rethink when sending Phishing Messages. Authors were able to Create a PoC illustrating the same. API endpoints that were created in this state-of-art executed within 1000 ms & the accuracy obtained from the Machine Learning model was also high.