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      A New Generic Taxonomy on Hybrid Malware Detection Technique

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          Abstract

          Malware is a type of malicious program that replicate from host machine and propagate through network. It has been considered as one type of computer attack and intrusion that can do a variety of malicious activity on a computer. This paper addresses the current trend of malware detection techniques and identifies the significant criteria in each technique to improve malware detection in Intrusion Detection System (IDS). Several existing techniques are analyzing from 48 various researches and the capability criteria of malware detection technique have been reviewed. From the analysis, a new generic taxonomy of malware detection technique have been proposed named Hybrid Malware Detection Technique (Hybrid MDT) which consists of Hybrid Signature and Anomaly detection technique and Hybrid Specification based and Anomaly detection technique to complement the weaknesses of the existing malware detection technique in detecting known and unknown attack as well as reducing false alert before and during the intrusion occur.

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          Most cited references6

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          Secure program execution via dynamic information flow tracking

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            Malware Pattern Scanning Schemes Secure Against Black-box Analysis

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              Using dynamic information flow analysis to detect attacks against applications

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                Author and article information

                Journal
                26 September 2009
                Article
                0909.4860
                111ae26d-9fb8-466d-8c03-59d62a62a809

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                ISSN 1947 5500
                Robiah Y, Siti Rahayu S., Mohd Zaki M, Shahrin S., Faizal M. A., Marliza R., International Journal of Computer Science and Information Security, IJCSIS, Vol. 5, No. 1, pp. 56-61, September 2009, USA
                6 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS 2009, ISSN 1947 5500, Impact Factor 0.423, http://sites.google.com/site/ijcsis/
                cs.CR

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