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Merge pull request #41 from CN-TU/felixig-patch-2
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felixig authored Feb 5, 2020
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229 changes: 229 additions & 0 deletions v2_papers/2017/vinayakumar_applying.json
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{
"version": "v3.0.0",
"reference": {
"title": "Applying Convolutional Neural Network for Network Intrusion Detection",
"authors": [
"Vinayakumar, R.",
"Soman, K.P.",
"Poornachandran, Prabaharan"
],
"publication_name": "international conference on advances in computing, communications and informatics",
"publication_type": "peer_reviewed_conference",
"year": 2017,
"organization_publishers": [
"ieee"
],
"pages_number_of": 7,
"bibtex": {
"pages": "1222--1228",
"type": "inproceedings"
},
"curated_by": "iglesias, f.",
"curated_last_revision": "02-02-2020",
"curated_revision_number": 1,
"access_open": false
},
"data": {
"datasets": [
{
"name": "kddcup-1999",
"availability": "public",
"format": "packet",
"types": [
"ipv4"
],
"generation": "altered_captured",
"generation_year": 1998,
"covered_period": "weeks",
"details": [
"preprocessed"
],
"subsets": [
"none"
],
"anonymized": "missing"
},
{
"name": "nsl-kdd-2008",
"availability": "public",
"format": "packet",
"types": [
"ipv4"
],
"generation": "altered_captured",
"generation_year": 1999,
"covered_period": "weeks",
"details": [
"preprocessed"
],
"subsets": [
"none"
],
"anonymized": "missing"
}
]
},
"preprocessing": {
"performed_feature_selection": false,
"flow_analysis_oriented": false,
"flow_aggregation_analysis_oriented": false,
"tools": "none",
"normalization_type": "no",
"transformations": [
"time_series"
],
"final_data_format": "mixed_vectors",
"feature_selections": "none",
"packets": [
{
"selection": "in_dataset",
"role": "main",
"main_goal": "attack_classification"
}
],
"flows": "none",
"flow_aggregations": "none",
"packet_analysis_oriented": true
},
"analysis_method": {
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"semisupervised_learning": false,
"anomaly_detection": false,
"tools": [
{
"name": "tensorflow",
"detail": "r0.12.0",
"availability": "public"
}
],
"algorithms": [
{
"family": "neural_networks",
"detail": "convolutional neural network",
"learning": "supervised",
"role": "main",
"type": "classification",
"metric/decision_criteria": "missing",
"tools": [
{
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"availability": "public"
}
],
"source": "referenced",
"parameters_provided": "partially"
},
{
"family": "neural_networks",
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"role": "competitor",
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"tools": [
{
"name": "tensorflow",
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"availability": "public"
}
],
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},
{
"family": "neural_networks",
"detail": "long short-term memory",
"learning": "supervised",
"role": "intermediate",
"type": "classification",
"metric/decision_criteria": "missing",
"tools": [
{
"name": "tensorflow",
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}
],
"source": "referenced",
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},
{
"family": "neural_networks",
"detail": "gated recurrent units",
"learning": "supervised",
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"tools": [
{
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}
],
"source": "referenced",
"parameters_provided": "partially"
},
{
"family": "neural_networks",
"detail": "recurrent neural network",
"learning": "supervised",
"role": "intermediate",
"type": "classification",
"metric/decision_criteria": "missing",
"tools": [
{
"name": "tensorflow",
"detail": "r0.12.0",
"availability": "public"
}
],
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}
],
"supervised_learning": true
},
"evaluation": {
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"dpi-based_validation": false,
"port-based_validation": false,
"pre-knowledge-based_validation": false,
"manual_verification": false,
"implementation_in_real_scenario": false,
"methods": [
{
"name": "normal classification metrics",
"type": "external",
"metrics": [
"accuracy",
"false_positive_rate",
"false_negative_rate",
"roc/auc"
],
"source": "popular"
},
{
"name": "t-sne-visualization",
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}
],
"algorithm_comparison": true,
"external_validation": true,
"train_test_separation": true
},
"result": {
"main_goal": "detect_attacks",
"subgoals": [
"attack_classification"
],
"focus_main": "algorithm",
"claimed_improvements": [
"improved_detection_rates"
],
"reproducibility": "replicable"
}
}
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