Contoh pendeteksi infotype kustom

Protokol

Objek JSON sampel di halaman ini adalah beberapa contoh detektor infoType kustom Sensitive Data Protection yang dapat Anda gunakan selama inspeksi dan de-identifikasi.

Untuk mengetahui informasi selengkapnya tentang berbagai jenis detektor infoType kustom dan cara membuatnya, lihat Membuat detektor infoType kustom.

Contoh konten customInfoTypes

JSON yang diberikan dalam tabel berikut dapat dimasukkan ke dalam definisi tugas inspeksi atau anonimisasi, di dalam atribut "customInfoTypes". Permintaan JSON lengkap berikut, yang mengirim string pendek ke Sensitive Data Protection, menyertakan definisi detektor infoType kustom yang menentukan format nomor rekam medis.

Input JSON:

POST https://dlp.googleapis.com/v2/projects/[PROJECT_ID]/content:inspect?key={YOUR_API_KEY}

{
  "item":{
    "value":"Patients MRN 444-5-22222"
  },
  "inspectConfig":{
    "customInfoTypes":[
      {
        "infoType":{
          "name":"C_MRN"
        },
        "regex":{
          "pattern":"[1-9]{3}-[1-9]{1}-[1-9]{5}"
        },
        "likelihood":"POSSIBLE"
      }
    ]
  }
}
Contoh deskripsi Pendeteksi infoType kustom
ID alfanumerik generik 
{
  "infoType":{
    "name":"GENERIC_ID2"
  },
  "regex":{
    "pattern":"\\b(([0-9]|([a-zA-Z()]{1,2}[0-9]{1}))[0-9-\\[\\]:(), ._]+)[0-9]{1}"
  },
  "likelihood":"POSSIBLE"
}
Mata uang umum 
{
  "infoType":{
    "name":"GENERIC_CURRENCY"
  },
  "regex":{
    "pattern":"((\\p{Sc}{1})( ){0,1}[0-9,()]+)(.){0,1}[0-9]{0,}"
  },
  "likelihood":"VERY_LIKELY"
}
Persentase umum 
{
  "infoType":{
    "name":"GENERIC_PERCENT"
  },
  "regex":{
    "pattern":"\\b([0-9,.()]+)( ){0,1}(%){1}"
  },
  "likelihood":"VERY_LIKELY"
}
Satuan pengukuran umum 
{
  "infoType":{
    "name":"GENERIC_MEASURE"
  },
  "regex":{
    "pattern":"(?i)([0-9])([0-9,.]+)( ){0,1}(?i)(°C|°F|K|°Ré|°N|°Ra|m³|dm³|cm³|l|dl|cl|ml|fl oz|in³|ft³|yd³|gal|bbl|pt|km|m|dm|cm|mm|mi|in|ft|yd|nautical mile|kg|hg|g|dg|cg|mg|µg|mcg|carat|grain|oz|lb|cwt|ton|km²|m²|dm²|cm²|mm²|ha|ca|mile²|in²|yd²|ft²|acre|nautical mile²|kmph|mps|mph|knot|km/h|m/s|mi/h|Hz|KHz|MHz|GHz|atm|bar|mbar|Pa|hPa|Psi|Torr|J|KJ|cal|kcal|Wh|kWh|BTU|thm|ft-lb|degrees|Celsius|Fahrenheit|Kelvin|Reaumur|Newton|Rankine|cubic |liter|deciliter|centiliter|milliliter|fluid ounce|gallon|petroleum barrel|pint|kilometer|meter|decimeter|centimeter|millimeter|mile|inch|foot|yard|nautical mile|tonne|kilogram|hectogram|gram|decigram|centigram|milligram|microgram|carat|grain|ounce|pound|square|hectare|centiare|square mile|square inch|square yard|square foot|acre|square nautical mile|kilometer|meter|mile per hour|knot|Hertz|Kilohertz|Megahertz|Gigahertz|Atmosphère|Bar|Millibar|Pascal|Hectopascal|Torr|Joule|Kilojoule|Calorie|Kilocalorie|Watt-hour|Kilowatt-hour|Foot-Pound|mpg){1}(s){0,1}\\b"
  },
  "likelihood":"VERY_LIKELY"
}
ID Permintaan Komentar (RFC) generik 
{
  "infoType":{
    "name":"GENERIC_RFC"
  },
  "regex":{
    "pattern":"\\b(?i)(rfc)( ){0,1}(20|768|783|791|792|793|826|854|855|862|863|864|868|903|937|951|959|1034|1035|1036|1055|1058|1059|1087|1119|1149|1157|1176|1305|1321|1350|1436|1441|1459|1730|1777|1855|1918|1939|1945|1948|1950|1951|1952|1964|2080|2119|2131|2177|2195|2228|2230|2246|2251|2252|2253|2254|2255|2256|2326|2327|2328|2351|2362|2397|2407|2408|2409|2427|2453|2460|2549|2555|2570|2595|2606|2740|2743|2744|2810|2811|2812|2813|2853|2865|2866|2974|3022|3031|3053|3056|3080|3162|3207|3261|3284|3286|3315|3339|3376|3401|3402|3403|3404|3405|3492|3501|3530|3550|3711|3720|3730|3783|3801|3830|3977|4122|4213|4217|4271|4287|4251|4291|4353|4408|4422|4541|4575|4579|4634|4646|4655|4787|4880|4960|5023|5321|5322|5533|5545|5849|5880|5881|5905|5969|6238|6265|6409|6455|6508|6726|6749|6797|6805|7230|7231|7232|7233|7234|7235|7301|7348|7469|7540|7541|7567|7725|7871|8391){0,1}"
  },
  "likelihood":"LIKELY"
}
ID konektor jaringan RJ45 generik 
{
  "infoType":{
    "name":"GENERIC_RJ_NETWORK"
  },
  "regex":{
    "pattern":"\\b(?i)(rj)(-){0,1}(?i)(A1X|A2X|A3X|2MB|11|12|13|14|15C|18|21X|25|26X|27X|31X|32X|33X|34X|35X|38X|41S|45S|45|48C|48S|48X|49C|61X|71C)"
  },
  "likelihood":"VERY_LIKELY"
}
Ukuran data generik 
{
  "infoType":{
    "name":"GENERIC_DATA_SIZE"
  },
  "regex":{
    "pattern":"\\b([0-9,. ]+)(?i)(byte|Kilobyte|KiB|Kilobit|kbit|bit|Megabyte|MiB|Megabit|Mbit|meg|Gigabyte|GiB|Gigabit|Gbit|gig|Terabyte|TiB|Terabit|Tbit|Petabyte|PiB|Petabit|Pbit|Exabyte|EiB|Exabit|Ebit|Zettabyte|ZiB|Zettabit|Zbit|Yottabyte|YiB|Yottabit|Ybit|KB|MB|GB|TB|PB|EB|ZB|YB)(p){0,1}(s){0,1}"
  },
  "likelihood":"VERY_LIKELY"
}
ID numerik 
{
  "infoType":{
    "name":"GENERIC_ID1"
  },
  "regex":{
    "pattern":"\\w*[0-9][0-9-()\\[\\].:/]+[0-9]\\w*"
  },
  "likelihood":"POSSIBLE"
}

Java

Untuk mempelajari cara menginstal dan menggunakan library klien untuk Sensitive Data Protection, lihat library klien Sensitive Data Protection.

Untuk melakukan autentikasi ke Sensitive Data Protection, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal. 


import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.CustomInfoType;
import com.google.privacy.dlp.v2.CustomInfoType.Regex;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.Likelihood;
import com.google.privacy.dlp.v2.LocationName;
import com.google.protobuf.ByteString;
import java.io.IOException;

public class InspectWithCustomRegex {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String textToInspect = "Patients MRN 444-5-22222";
    String customRegexPattern = "[1-9]{3}-[1-9]{1}-[1-9]{5}";
    inspectWithCustomRegex(projectId, textToInspect, customRegexPattern);
  }

  // Inspects a BigQuery Table
  public static void inspectWithCustomRegex(
      String projectId, String textToInspect, String customRegexPattern) throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the type and content to be inspected.
      ByteContentItem byteItem =
          ByteContentItem.newBuilder()
              .setType(BytesType.TEXT_UTF8)
              .setData(ByteString.copyFromUtf8(textToInspect))
              .build();
      ContentItem item = ContentItem.newBuilder().setByteItem(byteItem).build();

      // Specify the regex pattern the inspection will look for.
      Regex regex = Regex.newBuilder().setPattern(customRegexPattern).build();

      // Construct the custom regex detector.
      InfoType infoType = InfoType.newBuilder().setName("C_MRN").build();
      CustomInfoType customInfoType =
          CustomInfoType.newBuilder().setInfoType(infoType).setRegex(regex).build();

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder()
              .addCustomInfoTypes(customInfoType)
              .setIncludeQuote(true)
              .setMinLikelihood(Likelihood.POSSIBLE)
              .build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(LocationName.of(projectId, "global").toString())
              .setItem(item)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      InspectContentResponse response = dlp.inspectContent(request);

      // Parse the response and process results
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    }
  }
}