Phishing emails risk increases progressively, which pose a real threat to users of computers, organizations and lead to significant financial losses. Fighting zero day phishing emails using content based server side classifiers is considered as the best method to detect such attacks. This technique which is based on machine learning algorithms is trained by the set of phishing email features an...

Phishing attacks are a significant threat to users of the Internet, causing tremendous economic loss every year. In combating phish, industry relies heavily on manual verification to achieve a low false positive rate, which, however, tends to be slow in responding to the huge volume of unique phishing URLs created by toolkits. Our goal here is to combine the best aspects of human verified black...

In this paper, we perform a thorough study on the risks imposed by the globally accessible Android Clipboard. Based on the risk assessment, we formulate a series of attacks and categorize them into two groups, i.e., manipulation and stealing. Clipboard data manipulation may lead to common code injection attacks, like JavaScript injection and command injection. Furthermore, it can also cause phi...

In a phishing attack, an unsuspecting victim is lured, typically via an email, to a web site designed to steal sensitive information such as bank/credit card account numbers, login information for accounts, etc. Each year Internet users lose billions of dollars to this scourge. In this paper, we present a general semantic feature selection method for text problems based on the statistical t-tes...