Times Series Forecasting

3min
The below parameters are for various time series forecasting attack types. To know more about the different attack input parameters see Time Series Forecasting﻿. 
The values presented below are examples taken from the reference implementation. It is important to customize these values to achieve the best performance for your particular model.
Extraction
{
            "attack_type": "blackbox",
            "defense_bestonly": "no",
            "encryption_strategy": "0",
            "input_dimensions": "100,6",
            "model_api_details": "na",
            "model_framework": "tensorflow",
            "number_of_attack_queries": "10000",
            "use_model_api": "no",
            "vulnerability_threshold": "0"
}

{
            "attack_type": "blackbox",
            "defense_bestonly": "no",
            "encryption_strategy": "0",
            "input_dimensions": "100,6",
            "model_api_details": "na",
            "model_framework": "tensorflow",
            "number_of_attack_queries": "10000",
            "use_model_api": "no",
            "vulnerability_threshold": "0"
}
﻿
POST
Request
Path Params
model_id
String
required
Header Parameters
Org_id
String
required
Enter your organization id
x-api-key
String
required
Enter your API key
Python
Curl
Node.js
JS
import requests

modelID="<< Enter Model ID >>"
url = "https://api.aws.boschaishield.com/prod/api/ais/v1.5/model_analyse/"+modelID+""

# please select proper payload for your usecase for extraction, evasion or poisoning.
payload={
    # <<Enter Payload Data>>
}
headers = {
   'Accept': 'application/json',
   'x-api-key': '########################################',
   'Org-Id': '####################################################################################################'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)
import requests

modelID="<< Enter Model ID >>"
url = "https://api.aws.boschaishield.com/prod/api/ais/v1.5/model_analyse/"+modelID+""

# please select proper payload for your usecase for extraction, evasion or poisoning.
payload={
    # <<Enter Payload Data>>
}
headers = {
   'Accept': 'application/json',
   'x-api-key': '########################################',
   'Org-Id': '####################################################################################################'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)
Responses
200
401
400
412
// 412 precondition failed: Returns an error message if access to the target resource has been denied. (For example- if any of the parameter value is incorrect or license has expired)
// 412 precondition failed: Returns an error message if access to the target resource has been denied. (For example- if any of the parameter value is incorrect or license has expired)
﻿
Note: In the response, copy job_id. This value is required to trigger the GET APIs. See <GET> Job Metadata﻿.

The "job_id" is used to retrieve model analysis metadata and check the processing status of the request. It is also used for generating reports for the analyzed model. Copy the dashboard link from the response and open it in a new tab. This allows users to monitor the job progress and download reports.
﻿
For using Nodejs sample code, install npm package request
Given ample code for python is tested for Python version 3.7
Given Sample code for nodejs and javascript is tested for Node V20LTS 
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Time Series
Text