Carnegie Mellon Researchers Use Mobile Users Behavior to Predict Exposure to Malicious Websites
Researchers with Carnegie Mellon University have developed an accurate system for predicting user exposure to malicious websites based on three categories of user behavior: contextual information, i.e. information on an active browsing session; past browsing behavior; and survey information reported by the user. The system enabled the researchers to predict a user’s exposure to a malicious website seconds in advance. In addition, the system could detect malicious websites before they had been blacklisted.
These findings are very promising because they highlight new possibilities for a proactive approach to cyber defense. As one of the researchers explained: “Now we can use the predictions to proactively protect users, thus adding a complementary line of defense to the existing reactive defenses.”