java敏感词过滤工具类——常用工具

package com.tydic.jtcrm.server.utils;
import java.util.*;

/**
 * Created by liu on 2021/3/24.
 *
 * @Description:
 */
public class BadWordUtil {

    public static Set<String> words;


    public static   List<String> wordText = new ArrayList<>();
    public static   List<String> word= new ArrayList<>();
    public static Map<String,String> wordMap;
    public static Map<String,String> wordMaps;

    public static int minMatchTYpe = 1;      //最小匹配规则
    public static int maxMatchType = 2;      //最大匹配规则
    static{
        BadWordUtil.words = readTxtByLine(wordText,word);
        addBadWordToHashMap(BadWordUtil.words);

    }
    public static Set<String> readTxtByLine(List<String> wordText,List<String> word){
        for (String words:word){
            wordText.add(words);
        }
        Set<String> keyWordSet = new HashSet<String>();
        try{
for (String temp:wordText ){
    keyWordSet.add(temp);
}
        } catch(Exception e){
            e.printStackTrace();
        }
        return keyWordSet;
    }
    /**
     * 检查文字中是否包含敏感字符，检查规则如下：<br>
     * @param txt
     * @param beginIndex
     * @param matchType
     * @return，如果存在，则返回敏感词字符的长度，不存在返回0
     * @version 1.0
     */
    @SuppressWarnings({ "rawtypes"})
    public static int checkBadWord(String txt,int beginIndex,int matchType){
        boolean  flag = false;    //敏感词结束标识位：用于敏感词只有1位的情况
        int matchFlag = 0;     //匹配标识数默认为0
        char word = 0;
        Map nowMap = wordMap;


        for(int i = beginIndex; i < txt.length() ; i++){
            word = txt.charAt(i);

            nowMap = (Map) nowMap.get(word);     //获取指定key
            if(nowMap != null){     //存在，则判断是否为最后一个
                matchFlag++;     //找到相应key，匹配标识+1
                if("1".equals(nowMap.get("isEnd"))){       //如果为最后一个匹配规则,结束循环，返回匹配标识数
                    flag = true;       //结束标志位为true
                    if(minMatchTYpe == matchType){    //最小规则，直接返回,最大规则还需继续查找
                        break;
                    }
                }
            }
            else{     //不存在，直接返回
                break;
            }
        }
        /*
         *
         * if(matchFlag < 2 && !flag){
            matchFlag = 0;
        }*/
        if(!flag){
            matchFlag = 0;
        }
        return matchFlag;
    }

    /**
     * 判断文字是否包含敏感字符
     * @param txt  文字
     * @param matchType  匹配规则 1：最小匹配规则，2：最大匹配规则
     * @return 若包含返回true，否则返回false
     * @version 1.0
     */
    public static boolean isContaintBadWord(String txt,int matchType){
        boolean flag = false;
        for(int i = 0 ; i < txt.length() ; i++){
            int matchFlag = checkBadWord(txt, i, matchType); //判断是否包含敏感字符
            if(matchFlag > 0){    //大于0存在，返回true
                flag = true;
            }
        }
        return flag;
    }

    /**
     * 替换敏感字字符
     * @param txt
     * @param matchType
     * @param replaceChar 替换字符，默认*
     * @version 1.0
     */
    public static String replaceBadWord(String txt,int matchType,String replaceChar){
        String resultTxt = txt;
        Set<String> set = getBadWord(txt, matchType);     //获取所有的敏感词
        Iterator<String> iterator = set.iterator();
        String word = null;
        String replaceString = null;
        while (iterator.hasNext()) {
            word = iterator.next();
            replaceString = getReplaceChars(replaceChar, word.length());

            resultTxt = resultTxt.replaceAll(word, replaceString);
        }

        return resultTxt;
    }
    /**
     * 获取文字中的敏感词
     * @param txt 文字
     * @param matchType 匹配规则 1：最小匹配规则，2：最大匹配规则
     * @return
     * @version 1.0
     */
    public static Set<String> getBadWord(String txt , int matchType){
        Set<String> sensitiveWordList = new HashSet<String>();

        for(int i = 0 ; i < txt.length() ; i++){
            int length = checkBadWord(txt, i, matchType);    //判断是否包含敏感字符
            if(length > 0){    //存在,加入list中
                sensitiveWordList.add(txt.substring(i, i+length));
                i = i + length - 1;    //减1的原因，是因为for会自增
            }
        }

        return sensitiveWordList;
    }

    /**
     * 获取替换字符串
     * @param replaceChar
     * @param length
     * @return
     * @version 1.0
     */
    private static String getReplaceChars(String replaceChar,int length){
        String resultReplace = replaceChar;
        for(int i = 1 ; i < length ; i++){
            resultReplace += replaceChar;
        }

        return resultReplace;
    }

    /**
     * TODO 将我们的敏感词库构建成了一个类似与一颗一颗的树，这样我们判断一个词是否为敏感词时就大大减少了检索的匹配范围。
     * @param keyWordSet 敏感词库
     */
    @SuppressWarnings({ "unchecked", "rawtypes" })
    public static void addBadWordToHashMap(Set<String> keyWordSet) {
        wordMap = new HashMap(keyWordSet.size());     //初始化敏感词容器，减少扩容操作
        String key = null;
        Map nowMap = null;
        Map<String, String> newWorMap = null;
        //迭代keyWordSet
        Iterator<String> iterator = keyWordSet.iterator();
        while(iterator.hasNext()){
            key = iterator.next();    //关键字
            nowMap = wordMap;
            for(int i = 0 ; i < key.length() ; i++){
                char keyChar = key.charAt(i);       //转换成char型
                Object wordMap = nowMap.get(keyChar);       //获取

                if(wordMap != null){        //如果存在该key，直接赋值
                    nowMap = (Map) wordMap;
                }
                else{     //不存在则，则构建一个map，同时将isEnd设置为0，因为他不是最后一个
                    newWorMap = new HashMap<String,String>();
                    newWorMap.put("isEnd", "0");     //不是最后一个
                    nowMap.put(keyChar, newWorMap);
                    nowMap = newWorMap;
                }

                if(i == key.length() - 1){
                    nowMap.put("isEnd", "1");    //最后一个
                }
            }
        }
    }


    public static void main(String[] args) {
          List<String> wordText = new ArrayList<>();
         List<String> word= new ArrayList<>();
          word.add("组织");
          word.add("必须");
          word.add("部门");
          //在实际需要调用需要脱敏处理的业务处需要改动，下面有例子。word相当于你配置的敏感词
        Set<String> strings = BadWordUtil.readTxtByLine(wordText, word);
        BadWordUtil.addBadWordToHashMap(strings);
        System.out.println("敏感词的数量：" + BadWordUtil.wordMap.size());
        String string = "这里是必要组织，高级部门，必须";
        System.out.println("待检测语句字数：" + string.length());
        long beginTime = System.currentTimeMillis();
        Set<String> set = BadWordUtil.getBadWord(string, 2);
        long endTime = System.currentTimeMillis();
        System.out.println("语句中包含敏感词的个数为：" + set.size() + "。包含：" + set);
        String s1 = BadWordUtil.replaceBadWord(string, 2, "*");
        System.out.println("脱敏后的语句为："+s1);
        System.out.println("总共消耗时间为：" + (endTime - beginTime));
    }
}

下面是我在自己项目中具体调用的案例，可参考修改：

                            String prodInstName = StringUtil.getString(prodOrderItem.get("prodInstName"));//需要脱敏的字段
                            if(NullUtil.isNotNull(prodInstName)){
                                List<String> wordText = new ArrayList<>();
                                List<String> word= new ArrayList<>();
                           /*     word.add("军队");
                                word.add("武");*/
                                List<String> paramValue = qryOrderItemDao.qryForeParam();//paramValue 为我配置在数据库表中的敏感词
                                 word.addAll(paramValue);//将查出来的配置的敏感词赋值给我们敏感词集合
                                Set<String> strings = BadWordUtil.readTxtByLine(wordText, word);
                                BadWordUtil.addBadWordToHashMap(strings);
                                String prodInstNames = BadWordUtil.replaceBadWord(prodInstName, 2, "*");//将需要脱敏的字用*代替。
    prodInstName =  prodInstNames  //用脱敏后的替换                       
                            }