Abstract-Traditional authentication methods based on user browsing behaviors consider relatively one-snidely on user browsing habits. They mainly research on the relationships between the sequences of websites or contents without considering user habits comprehensively. So the accuracy when they distinguish different users' web browsing behaviors cannot ensure enough safety, which can be further optimized. This paper introduces a new method which studies from favorite websites, contents and periods of browsing time. It uses Apriori algorithm to mine user's frequent itemsets along with the text classification method and normal distribution to calculate access periods of time. Logic regression algorithm is applied onto user authentication. Experiment shows that detection rate can reach 92.7% while false alarm rate is 6.4%.Index Terms-Identity authentication, user behavior, web browsing features, frequent itemset.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.