一：敏感词汇文件放置位置
二：说明：如果txt文件不能编译，pom文件添加下面配置
三：简单的内存缓存敏感词汇类
public class Cache { /** * 键值对集合 */ private final static ConcurrentHashMap<String, List<String>> MAP = new ConcurrentHashMap<>(); /** * 添加缓存 */ public synchronized static void put(String key, List<String> data) { //清除原键值对 Cache.remove(key); //不设置过期时间 MAP.put(key, data); } /** * 读取缓存 */ public static List<String> get(String key) { return MAP.get(key); } /** * 清除缓存 */ public synchronized static void remove(String key) { MAP.remove(key); }}四：敏感词汇过滤替换为*
package cloud.exec.common.wordfilterutils;import lombok.extern.slf4j.Slf4j;import org.apache.commons.collections.CollectionUtils;import org.apache.commons.lang3.StringUtils;import org.springframework.core.io.DefaultResourceLoader;import org.springframework.core.io.Resource;import java.io.BufferedReader;import java.io.InputStream;import java.io.InputStreamReader;import java.nio.charset.StandardCharsets;import java.util.*;/** * 敏感词汇过滤替换为* * 说明：部分代码来源于互联网 */@Slf4jpublic class WordFilter { private final static String WORDS = "WORDS"; private final static String REPLACE_CHAR = "*"; private static HashMap sensitiveWordMap; /** * 最小匹配规则 */ private static int minMatchTYpe = 1; /** * 最大匹配规则 */ private static int maxMatchType = 2; /** * 敏感词汇过滤替换为* * * @param text 待检测文字 * @return 替换后文字 */ public static String replaceWords(String text) { if (StringUtils.isBlank(text)) { return text; } //缓存获取敏感词汇原记录 List<String> words = Cache.get(WORDS); if (CollectionUtils.isEmpty(words)) { //读取敏感词汇文件，存入缓存 words = readWordsFile(); Cache.put(WORDS, words); } if (CollectionUtils.isEmpty(words)) { return text; } //屏蔽敏感词汇 return WordFilter.replaceSensitiveWord(words, text, WordFilter.minMatchTYpe); } /** * 读取敏感词汇文件 */ private static List<String> readWordsFile() { List<String> list = new ArrayList<>(); InputStream inputStream = null; InputStreamReader inputStreamReader = null; BufferedReader bufferedReader = null; try { Resource resource = new DefaultResourceLoader().getResource("classpath:words.txt"); inputStream = resource.getInputStream(); inputStreamReader = new InputStreamReader(inputStream, StandardCharsets.UTF_8); bufferedReader = new BufferedReader(inputStreamReader); String txt = ""; while (StringUtils.isNotBlank(txt = bufferedReader.readLine())) { list.addAll( Arrays.asList( StringUtils.split( StringUtils.deleteWhitespace(StringUtils.replace(txt, "，", ",")), "," ) ) ); } bufferedReader.close(); inputStreamReader.close(); inputStream.close(); } catch (Exception e) { log.error("读取敏感词汇文件出错", e); } finally { try { if (bufferedReader != null) { bufferedReader.close(); } if (inputStreamReader != null) { inputStreamReader.close(); } if (inputStream != null) { inputStream.close(); } } catch (Exception e) { log.error("读取敏感词汇文件出错", e); } } return list; } /** * 替换敏感字字符 * * @param data 敏感字集合 * @param txt 待检查文本 * @param matchType 匹配规则 */ private static String replaceSensitiveWord(List<String> data, String txt, int matchType) { if (sensitiveWordMap == null) { addSensitiveWord(data); } String resultTxt = txt; //获取所有的敏感词 List<String> set = getSensitiveWord(txt, matchType); Iterator<String> iterator = set.iterator(); while (iterator.hasNext()) { resultTxt = resultTxt.replaceAll(iterator.next(), REPLACE_CHAR); } return resultTxt; } /** * 读取敏感词库，将敏感词放入HashSet中，构建一个DFA算法模型： * 说明：该方法来源于互联网 */ private static void addSensitiveWord(List<String> datas) { sensitiveWordMap = new HashMap(datas.size()); Iterator<String> iterator = datas.iterator(); Map<String, Object> now = null; Map now2 = null; while (iterator.hasNext()) { now2 = sensitiveWordMap; String word = iterator.next().trim(); //敏感词 for (int i = 0; i < word.length(); i++) { char key_word = word.charAt(i); Object obj = now2.get(key_word); if (obj != null) { //存在 now2 = (Map) obj; } else { //不存在 now = new HashMap<String, Object>(); now.put("isEnd", "0"); now2.put(key_word, now); now2 = now; } if (i == word.length() - 1) { now2.put("isEnd", "1"); } } } } /** * 获取内容中的敏感词 *说明：该方法来源于互联网 * @param text 内容 * @param matchType 匹配规则 1=不最佳匹配，2=最佳匹配 * @return */ private static List<String> getSensitiveWord(String text, int matchType) { List<String> words = new ArrayList<String>(); Map now = sensitiveWordMap; int count = 0; //初始化敏感词长度 int start = 0; //标志敏感词开始的下标 for (int i = 0; i < text.length(); i++) { char key = text.charAt(i); now = (Map) now.get(key); if (now != null) { //存在 count++; if (count == 1) { start = i; } if ("1".equals(now.get("isEnd"))) { //敏感词结束 now = sensitiveWordMap; //重新获取敏感词库 words.add(text.substring(start, start + count)); //取出敏感词，添加到集合 count = 0; //初始化敏感词长度 } } else { //不存在 now = sensitiveWordMap;//重新获取敏感词库 if (count == 1 && matchType == 1) { //不最佳匹配 count = 0; } else if (count == 1 && matchType == 2) { //最佳匹配 words.add(text.substring(start, start + count)); count = 0; } } } return words; } public WordFilter() { super(); }}五：测试