ml-ids-api/api-spec.yaml at master · cstub/ml-ids-api · GitHub

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swagger: "2.0"
info:
  description: "The public REST API of the ML-IDS classifier."
  version: "1.0.0"
  title: "ML-IDS API"
basePath: "/api"
tags:
- name: "predictions"
  description: "Request classification predictions for network flows"
schemes:
- "http"
paths:
  /predictions:
    post:
      tags:
      - "predictions"
      summary: "Request classification predictions for an arbitrary number of network flows"
      description: ""
      operationId: "requestPrediction"
      consumes:
      - "application/json; format=pandas-split"
      produces:
      - "application/json"
      parameters:
      - in: "body"
        name: "body"
        description: "Network flows to classify as Pandas DataFrame in JSON 'split' format."
        required: true
        schema:
          $ref: "#/definitions/PredictionRequest"
      responses:
        200:
          description: "Successful operation. Response contains the predicitions in the order of the input network flows."
          schema:
            $ref: "#/definitions/PredictionResponse"
        400:
          description: "Invalid input"
        415:
          description: "Unsupported media type"

definitions:
  PredictionRequest:
    type: "object"
    description: "Pandas DataFrame serialized as JSON in the Pandas 'split' format."
    required:
    - "columns"
    - "data"
    properties:
      columns:
        type: "array"
        items:
          type: "string"
        example: ["dst_port","protocol","timestamp","flow_duration","tot_fwd_pkts","tot_bwd_pkts","totlen_fwd_pkts","totlen_bwd_pkts","fwd_pkt_len_max","fwd_pkt_len_min","fwd_pkt_len_mean","fwd_pkt_len_std","bwd_pkt_len_max","bwd_pkt_len_min","bwd_pkt_len_mean","bwd_pkt_len_std","flow_byts_s","flow_pkts_s","flow_iat_mean","flow_iat_std","flow_iat_max","flow_iat_min","fwd_iat_tot","fwd_iat_mean","fwd_iat_std","fwd_iat_max","fwd_iat_min","bwd_iat_tot","bwd_iat_mean","bwd_iat_std","bwd_iat_max","bwd_iat_min","fwd_psh_flags","bwd_psh_flags","fwd_urg_flags","bwd_urg_flags","fwd_header_len","bwd_header_len","fwd_pkts_s","bwd_pkts_s","pkt_len_min","pkt_len_max","pkt_len_mean","pkt_len_std","pkt_len_var","fin_flag_cnt","syn_flag_cnt","rst_flag_cnt","psh_flag_cnt","ack_flag_cnt","urg_flag_cnt","cwe_flag_count","ece_flag_cnt","down_up_ratio","pkt_size_avg","fwd_seg_size_avg","bwd_seg_size_avg","fwd_byts_b_avg","fwd_pkts_b_avg","fwd_blk_rate_avg","bwd_byts_b_avg","bwd_pkts_b_avg","bwd_blk_rate_avg","subflow_fwd_pkts","subflow_fwd_byts","subflow_bwd_pkts","subflow_bwd_byts","init_fwd_win_byts","init_bwd_win_byts","fwd_act_data_pkts","fwd_seg_size_min","active_mean","active_std","active_max","active_min","idle_mean","idle_std","idle_max","idle_min"]
        description: "Array containing the column names of the Pandas DataFrame."
      data:
        type: "array"
        items:
          type: "array"
          items:
            type: "object"
        example: [[80,17,"21\\/02\\/2018 10:15:06",119759145,75837,0,2426784,0,32,32,32.0,0.0,0,0,0.0,0.0,20263.87212,633.2460039,1579.1859130859,31767.046875,920247,1,120000000,1579.1859130859,31767.046875,920247,1,0,0.0,0.0,0,0,0,0,0,0,606696,0,633.2460327148,0.0,32,32,32.0,0.0,0.0,0,0,0,0,0,0,0,0,0,32.0004234314,32.0,0.0,0,0,0,0,0,0,75837,2426784,0,0,-1,-1,75836,8,0.0,0.0,0,0,0.0,0.0,0,0]]
        description: "Nested array containing the data rows. Each data row is represented as a separate array."

  PredictionResponse:
    type: "array"
    items:
      type: "number"
    example: [1.0, 0.0]
    description: "Predictions for the submitted network flows in the same order as the input rows [0=Benign, 1=Attack]."