Datasets:

anonymizeddb
/

CAD-CICIDS2018

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
source: string
task_id_column: string
orderings: list<item: struct<name: string, task_sequence: list<item: string>>>
  child 0, item: struct<name: string, task_sequence: list<item: string>>
      child 0, name: string
      child 1, task_sequence: list<item: string>
          child 0, item: string
rai:hasSyntheticData: bool
rai:dataSocialImpact: string
conformsTo: list<item: string>
  child 0, item: string
@context: struct<@language: string, @vocab: string, citeAs: string, column: string, conformsTo: string, cr: st (... 615 chars omitted)
  child 0, @language: string
  child 1, @vocab: string
  child 2, citeAs: string
  child 3, column: string
  child 4, conformsTo: string
  child 5, cr: string
  child 6, rai: string
  child 7, data: struct<@id: string, @type: string>
      child 0, @id: string
      child 1, @type: string
  child 8, dataType: struct<@id: string, @type: string>
      child 0, @id: string
      child 1, @type: string
  child 9, dct: string
  child 10, equivalentProperty: string
  child 11, examples: struct<@id: string, @type: string>
      child 0, @id: string
      child 1, @type: string
  child 12, extract: string
  child 13, field: string
  child 14, fileProperty: string
  child 15, fileObject: string
  child 16, fileSet: string
  child 17, format: string
  child 18, includes: string
  child 19, isLiveDataset: string
  child 20, jsonPath: string
  child 21, key: string
  child 22, md5: string
  child 23, parentField: string
  child 24, path: string
  child 
...
hild 0, @id: string
                  child 1, extract: struct<column: string>
                      child 0, column: string
              child 5, references: struct<field: struct<@id: string>>
                  child 0, field: struct<@id: string>
                      child 0, @id: string
              child 6, repeated: bool
      child 5, key: struct<@id: string>
          child 0, @id: string
      child 6, data: list<item: struct<orderings/name: string, orderings/task_sequence: list<item: string>>>
          child 0, item: struct<orderings/name: string, orderings/task_sequence: list<item: string>>
              child 0, orderings/name: string
              child 1, orderings/task_sequence: list<item: string>
                  child 0, item: string
name: string
rai:personalSensitiveInformation: string
license: string
version: string
citeAs: string
distribution: list<item: struct<@type: string, @id: string, name: string, description: string, contentSize: string (... 62 chars omitted)
  child 0, item: struct<@type: string, @id: string, name: string, description: string, contentSize: string, contentUr (... 50 chars omitted)
      child 0, @type: string
      child 1, @id: string
      child 2, name: string
      child 3, description: string
      child 4, contentSize: string
      child 5, contentUrl: string
      child 6, encodingFormat: string
      child 7, sha256: string
description: string
prov:wasGeneratedBy: string
keywords: list<item: string>
  child 0, item: string
to
{'@context': {'@language': Value('string'), '@vocab': Value('string'), 'citeAs': Value('string'), 'column': Value('string'), 'conformsTo': Value('string'), 'cr': Value('string'), 'rai': Value('string'), 'data': {'@id': Value('string'), '@type': Value('string')}, 'dataType': {'@id': Value('string'), '@type': Value('string')}, 'dct': Value('string'), 'equivalentProperty': Value('string'), 'examples': {'@id': Value('string'), '@type': Value('string')}, 'extract': Value('string'), 'field': Value('string'), 'fileProperty': Value('string'), 'fileObject': Value('string'), 'fileSet': Value('string'), 'format': Value('string'), 'includes': Value('string'), 'isLiveDataset': Value('string'), 'jsonPath': Value('string'), 'key': Value('string'), 'md5': Value('string'), 'parentField': Value('string'), 'path': Value('string'), 'recordSet': Value('string'), 'references': Value('string'), 'regex': Value('string'), 'repeated': Value('string'), 'replace': Value('string'), 'samplingRate': Value('string'), 'sc': Value('string'), 'separator': Value('string'), 'source': Value('string'), 'subField': Value('string'), 'transform': Value('string')}, '@type': Value('string'), 'name': Value('string'), 'description': Value('string'), 'conformsTo': List(Value('string')), 'citeAs': Value('string'), 'creator': {'@type': Value('string'), 'name': Value('string')}, 'inLanguage': Value('string'), 'keywords': List(Value('string')), 'license': Value('string'), 'prov:wasDerivedFrom': Value('string'), 'prov:wasGeneratedBy': Value('string'), 'rai:dataBiases': Value('string'), 'rai:dataLimitations': Value('string'), 'rai:dataSocialImpact': Value('string'), 'rai:dataUseCases': List(Value('string')), 'rai:hasSyntheticData': Value('bool'), 'rai:personalSensitiveInformation': Value('string'), 'url': Value('string'), 'version': Value('string'), 'distribution': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'contentSize': Value('string'), 'contentUrl': Value('string'), 'encodingFormat': Value('string'), 'sha256': Value('string')}), 'recordSet': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'field': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'dataType': Value('string'), 'source': {'fileObject': {'@id': Value('string')}, 'extract': {'column': Value('string')}}, 'references': {'field': {'@id': Value('string')}}, 'repeated': Value('bool')}), 'key': {'@id': Value('string')}, 'data': List({'orderings/name': Value('string'), 'orderings/task_sequence': List(Value('string'))})}), 'datePublished': Value('timestamp[s]')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              source: string
              task_id_column: string
              orderings: list<item: struct<name: string, task_sequence: list<item: string>>>
                child 0, item: struct<name: string, task_sequence: list<item: string>>
                    child 0, name: string
                    child 1, task_sequence: list<item: string>
                        child 0, item: string
              rai:hasSyntheticData: bool
              rai:dataSocialImpact: string
              conformsTo: list<item: string>
                child 0, item: string
              @context: struct<@language: string, @vocab: string, citeAs: string, column: string, conformsTo: string, cr: st (... 615 chars omitted)
                child 0, @language: string
                child 1, @vocab: string
                child 2, citeAs: string
                child 3, column: string
                child 4, conformsTo: string
                child 5, cr: string
                child 6, rai: string
                child 7, data: struct<@id: string, @type: string>
                    child 0, @id: string
                    child 1, @type: string
                child 8, dataType: struct<@id: string, @type: string>
                    child 0, @id: string
                    child 1, @type: string
                child 9, dct: string
                child 10, equivalentProperty: string
                child 11, examples: struct<@id: string, @type: string>
                    child 0, @id: string
                    child 1, @type: string
                child 12, extract: string
                child 13, field: string
                child 14, fileProperty: string
                child 15, fileObject: string
                child 16, fileSet: string
                child 17, format: string
                child 18, includes: string
                child 19, isLiveDataset: string
                child 20, jsonPath: string
                child 21, key: string
                child 22, md5: string
                child 23, parentField: string
                child 24, path: string
                child 
              ...
              hild 0, @id: string
                                child 1, extract: struct<column: string>
                                    child 0, column: string
                            child 5, references: struct<field: struct<@id: string>>
                                child 0, field: struct<@id: string>
                                    child 0, @id: string
                            child 6, repeated: bool
                    child 5, key: struct<@id: string>
                        child 0, @id: string
                    child 6, data: list<item: struct<orderings/name: string, orderings/task_sequence: list<item: string>>>
                        child 0, item: struct<orderings/name: string, orderings/task_sequence: list<item: string>>
                            child 0, orderings/name: string
                            child 1, orderings/task_sequence: list<item: string>
                                child 0, item: string
              name: string
              rai:personalSensitiveInformation: string
              license: string
              version: string
              citeAs: string
              distribution: list<item: struct<@type: string, @id: string, name: string, description: string, contentSize: string (... 62 chars omitted)
                child 0, item: struct<@type: string, @id: string, name: string, description: string, contentSize: string, contentUr (... 50 chars omitted)
                    child 0, @type: string
                    child 1, @id: string
                    child 2, name: string
                    child 3, description: string
                    child 4, contentSize: string
                    child 5, contentUrl: string
                    child 6, encodingFormat: string
                    child 7, sha256: string
              description: string
              prov:wasGeneratedBy: string
              keywords: list<item: string>
                child 0, item: string
              to
              {'@context': {'@language': Value('string'), '@vocab': Value('string'), 'citeAs': Value('string'), 'column': Value('string'), 'conformsTo': Value('string'), 'cr': Value('string'), 'rai': Value('string'), 'data': {'@id': Value('string'), '@type': Value('string')}, 'dataType': {'@id': Value('string'), '@type': Value('string')}, 'dct': Value('string'), 'equivalentProperty': Value('string'), 'examples': {'@id': Value('string'), '@type': Value('string')}, 'extract': Value('string'), 'field': Value('string'), 'fileProperty': Value('string'), 'fileObject': Value('string'), 'fileSet': Value('string'), 'format': Value('string'), 'includes': Value('string'), 'isLiveDataset': Value('string'), 'jsonPath': Value('string'), 'key': Value('string'), 'md5': Value('string'), 'parentField': Value('string'), 'path': Value('string'), 'recordSet': Value('string'), 'references': Value('string'), 'regex': Value('string'), 'repeated': Value('string'), 'replace': Value('string'), 'samplingRate': Value('string'), 'sc': Value('string'), 'separator': Value('string'), 'source': Value('string'), 'subField': Value('string'), 'transform': Value('string')}, '@type': Value('string'), 'name': Value('string'), 'description': Value('string'), 'conformsTo': List(Value('string')), 'citeAs': Value('string'), 'creator': {'@type': Value('string'), 'name': Value('string')}, 'inLanguage': Value('string'), 'keywords': List(Value('string')), 'license': Value('string'), 'prov:wasDerivedFrom': Value('string'), 'prov:wasGeneratedBy': Value('string'), 'rai:dataBiases': Value('string'), 'rai:dataLimitations': Value('string'), 'rai:dataSocialImpact': Value('string'), 'rai:dataUseCases': List(Value('string')), 'rai:hasSyntheticData': Value('bool'), 'rai:personalSensitiveInformation': Value('string'), 'url': Value('string'), 'version': Value('string'), 'distribution': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'contentSize': Value('string'), 'contentUrl': Value('string'), 'encodingFormat': Value('string'), 'sha256': Value('string')}), 'recordSet': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'description': Value('string'), 'field': List({'@type': Value('string'), '@id': Value('string'), 'name': Value('string'), 'dataType': Value('string'), 'source': {'fileObject': {'@id': Value('string')}, 'extract': {'column': Value('string')}}, 'references': {'field': {'@id': Value('string')}}, 'repeated': Value('bool')}), 'key': {'@id': Value('string')}, 'data': List({'orderings/name': Value('string'), 'orderings/task_sequence': List(Value('string'))})}), 'datePublished': Value('timestamp[s]')}
              because column names don't match

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CAD-CICIDS2018

Dataset Summary

CAD-CICIDS2018 is a single-source continual anomaly detection benchmark scenario for network intrusion detection. It is derived from CSE-CIC-IDS2018 and converts the original tabular network-intrusion data into a sequence of concept-grouped tasks.

The dataset contains 2,590,771 samples, 5 tasks, and has a reported 28.04% anomaly ratio in the test set.

The dataset is anonymized for double-blind NeurIPS review. Author names, institutional affiliations, project acknowledgements, and non-anonymous paper references are intentionally omitted.

Intended Use

This dataset is intended for research on:

continual anomaly detection;
continual learning for tabular data;
network intrusion detection;
robustness under distribution shift;
task ordering in continual-learning benchmarks;
forgetting and knowledge transfer across related network-traffic concepts;
benchmarking anomaly detectors under sequential task exposure.

The intended use is defensive machine learning research. The dataset should not be used to support offensive cybersecurity activity.

Dataset Source

CSE-CIC-IDS2018: https://www.unb.ca/cic/datasets/ids-2018.html

Dataset Files

The repository contains the following files:

File	Description
`data.csv`	Main tabular dataset file.
`orderings.json`	Predefined task orderings for continual-learning evaluation.
`croissant.json`	Croissant metadata describing the dataset.

Dataset Structure

The main file is:

data.csv

The dataset contains task metadata, binary labels, and numerical flow-level features.

Core Columns

Column	Type	Description
`task_id`	integer	Numeric identifier of the continual-learning task.
`task_name`	string	Name of the task, e.g. `cicids2018_0`.
`task_split`	string	Split assignment for the row.
`label`	integer	Binary anomaly label. Conventionally, `0` denotes benign/normal traffic and `1` denotes anomalous/attack traffic.

Task Identifiers

The dataset contains the following task identifiers:

cicids2018_0, cicids2018_1, cicids2018_2, cicids2018_3, cicids2018_4

Feature Columns

The remaining columns are numerical network-flow features, including packet-count, byte-count, flag-count, duration, inter-arrival-time, and aggregate flow-statistics features. Representative examples include:

Dst Port
Protocol
Flow Duration
Tot Fwd Pkts
Tot Bwd Pkts
TotLen Fwd Pkts
TotLen Bwd Pkts
Fwd Pkt Len Mean
Bwd Pkt Len Mean
Flow Byts/s
Flow Pkts/s
Flow IAT Mean
Fwd IAT Mean
Bwd IAT Mean

For the complete schema, see croissant.json.

Task Orderings

The dataset provides six predefined orderings in orderings.json. These orderings define different continual-learning evaluation regimes over the same task set.

Ordering	Task sequence
`curriculum_asc`	`cicids2018_3` → `cicids2018_4` → `cicids2018_2` → `cicids2018_1` → `cicids2018_0`
`curriculum_desc`	`cicids2018_0` → `cicids2018_1` → `cicids2018_2` → `cicids2018_4` → `cicids2018_3`
`generalization_desc`	`cicids2018_2` → `cicids2018_3` → `cicids2018_0` → `cicids2018_1` → `cicids2018_4`
`generalization_asc`	`cicids2018_4` → `cicids2018_1` → `cicids2018_0` → `cicids2018_3` → `cicids2018_2`
`smooth_drift`	`cicids2018_2` → `cicids2018_0` → `cicids2018_1` → `cicids2018_3` → `cicids2018_4`
`abrupt_drift`	`cicids2018_1` → `cicids2018_2` → `cicids2018_3` → `cicids2018_0` → `cicids2018_4`

These orderings are intended to expose complementary continual-learning dynamics, including curriculum-like adaptation, generalization-oriented ordering, smooth drift, and abrupt drift.

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Total file size:

1.18 GB