Shih Dong‐Her, Chiang Hsiu‐Sen, Chan Chun‐Yuan and Binshan Lin
New malicious e‐mails are created at the rate of thousands a year and pose a serious security threat. Especially, new, unseen Internet worms and virus often are arriving as e‐mail…
Abstract
New malicious e‐mails are created at the rate of thousands a year and pose a serious security threat. Especially, new, unseen Internet worms and virus often are arriving as e‐mail attachments. In this paper, Bayesian probabilistic network is examined to detect new malicious e‐mail viruses through anomaly detection. Experimental results show a better malicious e‐mail detection using Bayesian probabilistic networks. Managerial implications on how companies can protect their e‐mails and develop their own e‐mail security plan are addressed as well.