A novel bio-inspired predictive model for spam filtering based on dendritic cell algorithm

Electronic mail has become the most popular, frequently-used and powerful medium for quicker personal and business communications. However, one of the common security issues and annoying problems faced by email users and organizations is receiving a large number of unsolicited email messages, known as spam emails, every day. A traditional countermeasure in most email systems nowadays is simple filtering mechanisms that can block or quarantine unwanted emails based on some keywords defined by the user. These filters require continual effort to keep them relevant and current with some extensions proposed to improve their performance. However, due to the gigantic volumes of received emails and the continual change in spamming techniques to bypass the implemented solutions, novel automated ideas and countermeasures need to be investigated. This paper explores a novel algorithm inspired by the immune system called dendritic cell algorithm (DCA). This algorithm is evaluated on a number of benchmark datasets to detect spam emails. The results demonstrate that this approach can be a promising solution for email classification and spam filtering.