Research Article
Modified Decision Tree Technique for Ransomware Detection at Runtime through API Calls
| | Input: | | | Dataset = malicious and benign files | | | C: | | | c: | | | N: | | | attribute_list: | | | test_attribute: | | | k | | | Output: | | | vector feature | | | Function selection of features (RW dataset) | | | 1. For i = 0 to N do | | | 2. Replace Sample_set = c | | | 3. Create node N | | | 4. Call tree(N) | | | 5. End for | | | 6. Createtree(n) | | | 7. IF N = attribute_list then | | | 8. Return(N) | | | 9. Else | | | 10. Select from vector feature | | | 11. Select vector feature F. | | | 12. For i = 0 to k do | | | 13. Set sample N to C, where C is features = match vectors calltree (N) | | | 14. End for | | | 15. End if | | | End Function |
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