学习了《正则匹配人名》和《正则匹配电话号码》，如果要一起进行脱敏处理，改怎么做？ 脱敏的，考虑配置规则，进行匹配的方式进行处理：
脱敏规则：
DesensitizationRules
@Data
public class DesensitizationRules {
/**
* 匹配的字段名称
*/
public String fieldName;
/**
* 是否开启匹配 true 是 false 否
*/
public Boolean enabled;
/**
* 匹配的表达式
*/
public String regularExpr;
/**
* 替换的表达式
*/
public String replaceExpr;
}数据模拟：
public static List<DesensitizationRules> mockConfig(){
String data = "[\n" +
"\t{\n" +
"\t\t\"fieldName\": \"staffName\",\n" +
"\t\t\"enabled\": true,\n" +
"\t\t\"regularExpr\": \"(\\\\S)([a-zA-Z0-9_\\\\s\\\\u4e00-\\\\u9fa5]+)\",\n" +
"\t\t\"replaceExpr\": \"$1**\"\n" +
"\t},\n" +
"\t{\n" +
"\t\t\"fieldName\": \"mobile\",\n" +
"\t\t\"enabled\": true,\n" +
"\t\t\"regularExpr\": \"(\\\\d{3})\\\\d{4}(\\\\d{4})\",\n" +
"\t\t\"replaceExpr\": \"$1****$2\"\n" +
"\t},\n" +
"\t{\n" +
"\t\t\"fieldName\": \"tel\",\n" +
"\t\t\"enabled\": false,\n" +
"\t\t\"regularExpr\": \"(\\\\d{3})\\\\d{4}(\\\\d{4})\",\n" +
"\t\t\"replaceExpr\": \"$1****$2\"\n" +
"\t},\n" +
"\t{\n" +
"\t\t\"fieldName\": \"email\",\n" +
"\t\t\"enabled\": true,\n" +
"\t\t\"regularExpr\": \"(\\\\w?)(\\\\w+)(\\\\w)(@\\\\w+\\\\.[a-z]+(\\\\.[a-z]+)?)\",\n" +
"\t\t\"replaceExpr\": \"$1****$3$4\"\n" +
"\t}\n" +
"]";
DesensitizationRules single;
List<DesensitizationRules> rules = new ArrayList<>();
for(Object map: JSONArray.parseArray(data)){
single= JSON.parseObject(JSONObject.toJSONString(map),DesensitizationRules.class);
rules.add(single);
}
return rules;
}测试数据：
FlowStaff
@Data
public class FlowStaff {
private String staffName;
private String phs;
private String email;
private String mobile;
private String tel;
private String orgId;
private String orgName;
private String staffId;
private String staffaName;
private String regionName;
private String regionId;
}模拟数据：
public static List<FlowStaff> mockData(){
String receiveStr = "[\n" +
"\t{\n" +
"\t\t\"staffName\": \"张三飞\",\n" +
"\t\t\"phs\": null,\n" +
"\t\t\"email\": \"13456789@qq.com\",\n" +
"\t\t\"mobile\": \"18920220711\",\n" +
"\t\t\"tel\": \"18920220711,18955462232\",\n" +
"\t\t\"orgName\": \"组织机构/公司领导部门\",\n" +
"\t\t\"staffId\": \"1\",\n" +
"\t\t\"staffaName\": null,\n" +
"\t\t\"regionName\": \"福建\",\n" +
"\t\t\"orgId\": 59\n" +
"\t},\n" +
"\t{\n" +
"\t\t\"staffName\": \"Luck Kevin\",\n" +
"\t\t\"phs\": null,\n" +
"\t\t\"email\": \"12345678@qq.com\",\n" +
"\t\t\"mobile\": \"18920228733\",\n" +
"\t\t\"tel\": \"18920228733,18955462252\",\n" +
"\t\t\"orgName\": \"组织机构/公司领导部门\",\n" +
"\t\t\"staffId\": \"2\",\n" +
"\t\t\"staffaName\": null,\n" +
"\t\t\"regionName\": \"福建\",\n" +
"\t\t\"orgId\": 59\n" +
"\t}\n" +
"]";
System.out.println(receiveStr);
FlowStaff single;
List<FlowStaff> flowStaffs = new ArrayList<>();
for(Object map: JSONArray.parseArray(receiveStr)){
single= JSON.parseObject(JSONObject.toJSONString(map),FlowStaff.class);
flowStaffs.add(single);
}
return flowStaffs;
}处理：
根据规则，先获取配置中enabled 为true，然后对数据进行依次替换脱敏：
public static void main(String args[]) {
List<DesensitizationRules> rules = mockConfig();
List<FlowStaff> receivers = mockData();
// 过滤需要脱敏的enable = true的配置
List<DesensitizationRules> filterRules = ListUtils.emptyIfNull(rules).stream().filter(DesensitizationRules::getEnabled).collect(Collectors.toList());
if(CollectionUtils.isEmpty(filterRules)){
System.out.println("not have the config rule!");
return;
}
String receiversStr = JSONObject.toJSONString(receivers);
for (DesensitizationRules value : filterRules) {
receiversStr = replaceCommon(receiversStr, value.getFieldName(), value.getRegularExpr(), value.getReplaceExpr());
}
System.out.println("============ mask ============ ");
System.out.println(receiversStr);
}
public static String replaceCommon(String aimStr, String key, String regularExpr, String replaceExpr) {
return aimStr.replaceAll( "\""+key+"\""+":\\s*\""+regularExpr+"\"", "\""+key+"\""+":\""+replaceExpr+"\"");
}输出：
[
{
"email": "1****9@qq.com",
"mobile": "189****0711",
"orgId": "59",
"orgName": "组织机构/公司领导部门",
"regionName": "福建",
"staffId": "1",
"staffName": "张**",
"tel": "18920220711,18955462232"
},
{
"email": "1****8@qq.com",
"mobile": "189****8733",
"orgId": "59",
"orgName": "组织机构/公司领导部门",
"regionName": "福建",
"staffId": "2",
"staffName": "L**",
"tel": "18920228733,18955462252"
}
]把tel的配置enabled改成true再执行，输出：
============ mask ============
[
{
"email": "1****9@qq.com",
"mobile": "189****0711",
"orgId": "59",
"orgName": "组织机构/公司领导部门",
"regionName": "福建",
"staffId": "1",
"staffName": "张**",
"tel": "189****0711,189****2232"
},
{
"email": "1****8@qq.com",
"mobile": "189****8733",
"orgId": "59",
"orgName": "组织机构/公司领导部门",
"regionName": "福建",
"staffId": "2",
"staffName": "L**",
"tel": "189****8733,189****2252"
}
]可以看到人名（staffName）和电话号码（mobile），都进行了脱敏。 tel进行设置后，也脱敏了。达到想要的效果
总结：
对数据进行脱敏，可以考虑根据配置规则，这样可以动态修改规则，指定字段内容进行脱敏，会比较方便。 也可以考虑用正则表达式