A Risk-Scoring Feedback Model for Webpages and Web Users Based onn Browsing Behavior

摘要

It has been claimed thatmany security breaches are often caused by vulnerable (naive) employees within the organization [Ponemon Institute LLC 2015a]. Thus, the weakest link in security is often not the technology itself but rather the people who use it [Schneier 2003]. In this article, we propose a machine learning scheme for detecting risky webpages and risky browsing behavior, performed by naive users in the organization. The scheme analyzes the interaction between two modules: one represents