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dc.contributor.advisorDr. Bambang Sugiantoro, M.T.
dc.contributor.advisorAhmad Luthfi, S.Kom., M.Kom
dc.contributor.authorMuhammad, Abdul Haris
dc.date.accessioned2018-01-03T16:08:37Z
dc.date.available2018-01-03T16:08:37Z
dc.date.issued2017-04-15
dc.identifier.urihttps://dspace.uii.ac.id/handle/123456789/5061
dc.description.abstractMalware analysis requires special skills to make the detection and understand the workings of the malware. Malicious programs or malware becomes a threat or a problem that is difficult for researchers, there is no computing platform or environment that is immune to the threat. The increased complexity makes the researchers have to work hard and take time to understand how the malware There are two basic techniques that are often used to perform analysis of malware is static and dynamic analysis, and research conducted during the malware is still focused on the analysis of the behavior of the success of the method depends on the model of the malware. The use of signature-based technique is highly dependent on the behavior of malware that were analyzed, the analysis becomes difficult when it was discovered a new malware that uses a technique to complicate analysis system. Based on the description of the facts presented, it is necessary to build an ontology in the analysis of malware that can be used as a development, knowledge mapping as well as identifyingQ malware. In this study, the proposed method is the development of methods of Malware Analysis Body of Knowledge, where this method works on a specific domain to map and classify the characteristics of a type of malware that will be discussed. In this study focuses on the ontology as a knowledge base and more discussion to map the characteristics and classification of malware, by using protégé as tools for modeling ontology malwareen_US
dc.publisherUniversitas Islam Indonesiaid
dc.subjectMalwareen_US
dc.subjectDigital Forensicsen_US
dc.subjectOntologyen_US
dc.subjectDevelopmenten_US
dc.subjectCharacteristicsen_US
dc.subjectClassificationen_US
dc.titleMetode Klasifikasi dan Analisis Karakteristik Malware Menggunakan Konsep Ontologiid
dc.typeThesisen_US


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