| safe-graph/DGFraud |
432 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| A Deep Graph-based Toolbox for Fraud Detection |
| CERT-Polska/mquery |
395 |
|
0 |
0 |
about 2 years ago |
0 |
|
26 |
agpl-3.0 |
Python |
| YARA malware query accelerator (web frontend) |
| AbertayMachineLearningGroup/network-threats-taxonomy |
70 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
gpl-3.0 |
TeX |
| Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats. In this project we attempt at solving this problem by presenting two taxonomies |
| Veridax/privapi |
25 |
|
0 |
0 |
about 5 years ago |
0 |
|
1 |
apache-2.0 |
Python |
| Detect Sensitive REST API communication using Deep Neural Networks |
| anoopmsivadas/android-malware-detection |
18 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Android Malware Detection Using Machine Learning Classifiers ( Using Permissions requested by Apps) |
| mittalgovind/fifty |
7 |
|
0 |
0 |
about 5 years ago |
1 |
September 12, 2019 |
4 |
apache-2.0 |
Python |
| FiFTy: Large-scale File Fragment Type Identification using Neural Networks |
