Java Web敏感词过滤算法

爱被打了一巴掌 2022-05-21 01:05 322阅读 0赞

1.DFA算法

DFA算法的原理可以参考 [这里][Link 1] ，简单来说就是通过Map构造出一颗敏感词树，树的每一条由根节点到叶子节点的路径构成一个敏感词，例如下图：

![EfAR3i.png_web][]

代码简单实现如下：

public class TextFilterUtil {
      //日志
      private static final Logger LOG = LoggerFactory.getLogger(TextFilterUtil.class);
      //敏感词库
      private static HashMap sensitiveWordMap = null;
      //默认编码格式
      private static final String ENCODING = "gbk";
      //敏感词库的路径
      private static final InputStream in = TextFilterUtil.class.getClassLoader().getResourceAsStream("sensitive/keyWords.txt");
      /**
       * 初始化敏感词库
       */
      private static void init() {
        //读取文件
        Set<String> keyWords = readSensitiveWords();
        //创建敏感词库
        sensitiveWordMap = new HashMap<>(keyWords.size());
        for (String keyWord : keyWords) {
          createKeyWord(keyWord);
        }
      }
      /**
       * 构建敏感词库
       *
       * @param keyWord
       */
      private static void createKeyWord(String keyWord) {
        if (sensitiveWordMap == null) {
          LOG.error("sensitiveWordMap 未初始化!");
          return;
        }
        Map nowMap = sensitiveWordMap;
        for (Character c : keyWord.toCharArray()) {
          Object obj = nowMap.get(c);
          if (obj == null) {
            Map<String, Object> childMap = new HashMap<>();
            childMap.put("isEnd", "false");
            nowMap.put(c, childMap);
            nowMap = childMap;
          } else {
            nowMap = (Map) obj;
          }
        }
        nowMap.put("isEnd", "true");
      }
      /**
       * 读取敏感词文件
       *
       * @return
       */
      private static Set<String> readSensitiveWords() {
        Set<String> keyWords = new HashSet<>();
        BufferedReader reader = null;
        try {
          reader = new BufferedReader(new InputStreamReader(in, ENCODING));
          String line;
          while ((line = reader.readLine()) != null) {
            keyWords.add(line.trim());
          }
        } catch (UnsupportedEncodingException e) {
          LOG.error("敏感词库文件转码失败!");
        } catch (FileNotFoundException e) {
          LOG.error("敏感词库文件不存在!");
        } catch (IOException e) {
          LOG.error("敏感词库文件读取失败!");
        } finally {
          if (reader != null) {
            try {
              reader.close();
            } catch (IOException e) {
              e.printStackTrace();
            }
            reader = null;
          }
        }
        return keyWords;
      }
      /**
       * 检查敏感词
       *
       * @return
       */
      private static List<String> checkSensitiveWord(String text) {
        if (sensitiveWordMap == null) {
          init();
        }
        List<String> sensitiveWords = new ArrayList<>();
        Map nowMap = sensitiveWordMap;
        for (int i = 0; i < text.length(); i++) {
          Character word = text.charAt(i);
          Object obj = nowMap.get(word);
          if (obj == null) {
            continue;
          }
          int j = i + 1;
          Map childMap = (Map) obj;
          while (j < text.length()) {
            if ("true".equals(childMap.get("isEnd"))) {
              sensitiveWords.add(text.substring(i, j));
            }
            obj = childMap.get(text.charAt(j));
            if (obj != null) {
              childMap = (Map) obj;
            } else {
              break;
            }
            j++;
          }
        }
        return sensitiveWords;
      }
    }

2.TTMP算法

TTMP算法由网友原创，关于它的起源可以查看 [这里][Link 2] ，TTMP算法的原理是将敏感词拆分成“脏字”的序列，只有待比对字符串完全由“脏字”组成时，才去判断它是否为敏感词，减少了比对次数。这个算法的简单实现如下：

public class TextFilterUtil {
      //日志
      private static final Logger LOG = LoggerFactory.getLogger(TextFilterUtil.class);
      //默认编码格式
      private static final String ENCODING = "gbk";
      //敏感词库的路径
      private static final InputStream in = TextFilterUtil.class.getClassLoader().getResourceAsStream("sensitive/keyWords.txt");
      //脏字库
      private static Set<Character> sensitiveCharSet = null;
      //敏感词库
      private static Set<String> sensitiveWordSet = null;
      /**
       * 初始化敏感词库
       */
      private static void init() {
        //初始化容器
        sensitiveCharSet = new HashSet<>();
        sensitiveWordSet = new HashSet<>();
        //读取文件 创建敏感词库
        readSensitiveWords();
      }
      /**
       * 读取本地的敏感词文件
       *
       * @return
       */
      private static void readSensitiveWords() {
        BufferedReader reader = null;
        try {
          reader = new BufferedReader(new InputStreamReader(in, ENCODING));
          String line;
          while ((line = reader.readLine()) != null) {
            String word = line.trim();
            sensitiveWordSet.add(word);
            for (Character c : word.toCharArray()) {
              sensitiveCharSet.add(c);
            }
          }
        } catch (UnsupportedEncodingException e) {
          LOG.error("敏感词库文件转码失败!");
        } catch (FileNotFoundException e) {
          LOG.error("敏感词库文件不存在!");
        } catch (IOException e) {
          LOG.error("敏感词库文件读取失败!");
        } finally {
          if (reader != null) {
            try {
              reader.close();
            } catch (IOException e) {
              e.printStackTrace();
            }
            reader = null;
          }
        }
        return;
      }
      /**
       * 检查敏感词
       *
       * @return
       */
      private static List<String> checkSensitiveWord(String text) {
        if (sensitiveWordSet == null || sensitiveCharSet == null) {
          init();
        }
        List<String> sensitiveWords = new ArrayList<>();
        for (int i = 0; i < text.length(); i++) {
          Character word = text.charAt(i);
          if (!sensitiveCharSet.contains(word)) {
            continue;
          }
          int j = i;
          while (j < text.length()) {
            if (!sensitiveCharSet.contains(word)) {
              break;
            }
            String key = text.substring(i, j + 1);
            if (sensitiveWordSet.contains(key)) {
              sensitiveWords.add(key);
            }
            j++;
          }
        }
        return sensitiveWords;
      }
    }

注：以上代码实现仅用于展示思路，在实际使用中还有很多地方可以优化。

个人技术分享微信公众号，欢迎关注一起交流。

![20171225154508004][]

[Link 1]: http://blog.csdn.net/chenssy/article/details/26961957
[EfAR3i.png_web]: http://img0.tuicool.com/EfAR3i.png!web
[Link 2]: http://www.cnblogs.com/sumtec/archive/2008/02/01/1061742.html
[20171225154508004]: /images/20220521/6ed2c13d3be1401cb8ab349cd9c4da78.png