Brief introduction
The Anti-Fraud (Wool Shield) API is a technology solution for identifying and preventing all kinds of fraud. It can be integrated into various applications and platforms to detect anomalies through mobile phone numbers and mobile phone IPs to prevent fraudulent acts such as malicious registration, false reviews, and fake transactions.
This article mainly introduces the working principle of the Anti-Fraud (Wool Shield) API, its application in the fields of user behavior analysis technology, geolocation recognition technology, etc., and how it helps the platform identify fraudulent activities such as malicious registrations, fake reviews, and fake transactions.
How it works
We can visually understand how the Anti-Fraud (Wool Shield) API works with the following diagram:
Identify the results
By entering the mobile phone number and mobile phone IP address, the following results can be identified by anti-fraud (wool shield).
- Suspected spam traffic: Combined with the historical data performance of the device and account, it is judged that the account/device has historically used Internet services to commit evil acts, and the Internet behavior generated by the account is cheating or garbage traffic for other services;
- Suspected new customers: whether the account Internet behavior (social, browsing, etc.) is abnormal, it is judged to be a small number or code receiving platform account;
- Suspected zombie number: It is judged to be a zombie account through the abnormal social behavior of the account;
- Suspected number maintenance: through the abnormal social behavior of the account, it is judged to be the number in the malicious maintenance number of the black production team;
- Dyeing garbage trumpet: offline graph algorithm aggregation identification of black production slot;
- Suspected real and fake users: According to some data performance of the device, we determine that it is a group control device;
- Suspected fake machine: According to some data performance of the device, we determine that it is an emulator or a fake device ID;
- Suspected fake behavior of real user: Based on the user usage of the device, we determine that the user has cheated behaviors such as using scripts, plugins, and viruses.
Application of technology in user behavior analysis
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Application of geolocation recognition technology
Anti-fraud (wool shield) API use cases
In different scenarios such as e-commerce platforms, financial services, social media, and game platforms, the Anti-Fraud (Wool Shield) API can automatically identify and filter out fraudulent behaviors such as false reviews and false transactions by identifying user behavior, establishing user portraits, and monitoring abnormal behaviors, so as to improve the accuracy and efficiency of anti-fraud.
Anti-Fraud (Wool Shield) API usage tutorial
APISpace is a large API supply platform in China, providing a variety of API interfaces, including mobile phone number attribution query API, weather forecast query API, mobile phone in network status API, anti-fraud (wool shield) API and the current more popular AI painting API, etc., interested partners can go to the official website to experience.
1. Request a free trial of the API
After registering and logging in to APISpace, you can see the [Free Trial] button on the Anti-Fraud (Wool Shield) API details page, and you can click to get the corresponding free times.
2. Test the API with one click
Click the Test button, the API key will be populated by default on the test page of APISpace, enter the corresponding parameters, and click the Send button
Access Address:
https://www.apispace.com/eolink/api/wool/introduction?utm_source=tth&utm_content=high019&utm_term=yangmaodun
3. Code access to API
After testing, copy the following Python sample code directly and put it in your own program
import http.client
conn = http.client.HTTPSConnection("eolink.o.apispace.com")
payload = "mobile=&ip="
headers = {
"X-APISpace-Token":"",
"Authorization-Type":"apikey",
"Content-Type":"application/x-www-form-urlencoded"
}
conn.request("POST","/wool/wcheck", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))
If you need sample code in other languages, you can click [Access Guide] to view it.
4. Return to the example
{
"chargeStatus": 1,
"message": "成功",
"data": {
"mobile": "1328*******",
"tag": "",
"tradeNo": "22082210533674120",
"status": "B2"
},
"code": "200000"
}