DETEKSI MALWARE DALAM FILE PORTABLE DOCUMENT FORMAT (PDF) MENGGUNAKAN SUPPORT VECTOR MACHINE DAN RANDOM DECISION FOREST
| Main Author: | Charim, Abdachul |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/47758/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/47758/2/BAB%20I.pdf http://eprints.umm.ac.id/47758/3/BAB%20II.pdf http://eprints.umm.ac.id/47758/4/BAB%20III.pdf http://eprints.umm.ac.id/47758/5/BAB%20IV.pdf http://eprints.umm.ac.id/47758/6/BAB%20V.pdf http://eprints.umm.ac.id/47758/7/LAMPIRAN.pdf http://eprints.umm.ac.id/47758/ |
Daftar Isi:
- Portable Document Format is a very powerful file type for spreading malware because it takes a lot of people, so this can not be considered trivial. Malware embedded PDF files can be Javascript, URL access, malware infected media, etc. There are various actions that can help to spread, for example in this study using the classification method between the files are clear or not. Two methods that can be used are Machine Vector and Random Forest Support. There are 500 datasets consisting of 2 classes of malicious and notmalicius and 21 malicius PDF features as the material for the classification process.