Networking phishing susceptibility prediction method based on eye motion tracking and social worker parts

Abstract

The invention discloses a phishing susceptibility prediction method based on eye motion tracking and social worker parts, and belongs to the field of social engineering. The method specifically comprises the following steps: firstly, collecting subject attributes of social worker parts of each user, and recording and cleaning eye motion data of each user browsing a phishing website; meanwhile, each user scores the trust degree of phishing and the transaction intention according to the user; training a support SVR model by using the collected data of each user; dividing the users into different susceptibility grades by using a K-Means clustering algorithm; and when a new user actually browses the phishing website, collecting subject attributes and eye motion data of the new user, inputting the subject attributes and the eye motion data into the SVR model, calculating susceptibility values by using output data, and dividing the susceptibility values into corresponding grades for prediction. According to the method, the trained SVR model is utilized to predict the susceptibility of the user to the phishing, and then a corresponding targeted defense method is made according to the strength of the susceptibility, so that the user experience is enhanced, and all-around protection is provided.

Description

technical field [0001] The invention is a phishing susceptibility prediction method based on eye movement tracking and social engineering elements, which belongs to the field of social engineering. Background technique [0002] Phishing is a kind of network fraud attack. Attackers use disguised emails or phishing websites that are very similar to legitimate websites to make users let down their vigilance, intending to influence users to click links or open attachments in emails, and further lure users in Entering personal information such as user names and passwords on fake websites is an attack method in which attackers use social engineering techniques to illegally obtain key information of victims. [0003] In recent years, with the rapid development of the communication industry and Internet-related technologies, people use the Internet more and more frequently, and there are more and more online activities. While people are enjoying the convenience brought by the Inter...

AI Technical Summary

Problems solved by technology

However, even with these tools, phishing attacks still have a high success rate

The problem is that users often ignore the tool’s warnings. The reason for this problem is that the anti-phishing tool only predicts whether an email or website is a phishing attack, but does not predict the user’s sensitivity to phishing from the user’s perspective.

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