Internet security: malicious e‐mails detection and protection (original) (raw)

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[ Shih Dong‐Her ](/insight/search?q=Shih Dong‐Her) (Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, Republic of China)

[ Chiang Hsiu‐Sen ](/insight/search?q=Chiang Hsiu‐Sen) (Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, Republic of China)

[ Chan Chun‐Yuan ](/insight/search?q=Chan Chun‐Yuan) (Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan, Republic of China)

[ Binshan Lin ](/insight/search?q=Binshan Lin) (College of Business Administration, Louisiana State University in Shreveport, Shreveport, Louisiana, USA)

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.

Keywords

Citation

[Dong‐Her, S.](/insight/search?q=Shih Dong‐Her "Shih Dong‐Her"), [Hsiu‐Sen, C.](/insight/search?q=Chiang Hsiu‐Sen "Chiang Hsiu‐Sen"), [Chun‐Yuan, C.](/insight/search?q=Chan Chun‐Yuan "Chan Chun‐Yuan") and [Lin, B.](/insight/search?q=Binshan Lin "Binshan Lin") (2004), "Internet security: malicious e‐mails detection and protection", Industrial Management & Data Systems, Vol. 104 No. 7, pp. 613-623. https://doi.org/10.1108/02635570410550278

Publisher

Emerald Group Publishing Limited