数据库密态等值查询概述及操作-数据库组成

一、密态等值查询概述

随着企业数据上云，数据的安全隐私保护面临越来越严重的挑战。密态数据库将解决数据整个生命周期中的隐私保护问题，涵盖网络传输、数据存储以及数据运行态;更进一步，密态数据库可以实现云化场景下的数据隐私权限分离，即实现数据拥有者和实际数据管理者的数据读取能力分离。密态等值查询将优先解决密文数据的等值类查询问题。密态等值查询目前支持客户端工具 gsql 和 JDBC。接下来分别介绍如何使用客户端工具执行密态等值查询的相关操作。

二、使用 gsql 操作密态数据库

操作步骤

以操作系统用户 omm 登录主节点。

执行以下命令打开密态开关，连接密态数据库。

gsql -p PORT postgres -r -C

这里，PORT需要替换为实际值。

创建客户端主密钥 CMK 和列加密密钥 CEK。

--创建客户端加密主密钥(CMK)
openGauss=# CREATE CLIENT MASTER KEY ImgCMK1 WITH (KEY_STORE = localkms, KEY_PATH = "key_path_value1", ALGORITHM = RSA_2048);
openGauss=# CREATE CLIENT MASTER KEY ImgCMK WITH (KEY_STORE = localkms, KEY_PATH = "key_path_value2", ALGORITHM = RSA_2048);
openGauss=# CREATE COLUMN ENCRYPTION KEY ImgCEK1 WITH VALUES (CLIENT_MASTER_KEY = ImgCMK1, ALGORITHM  = AEAD_AES_256_CBC_HMAC_SHA256);
CREATE COLUMN ENCRYPTION KEY
openGauss=# CREATE COLUMN ENCRYPTION KEY ImgCEK WITH VALUES (CLIENT_MASTER_KEY = ImgCMK, ALGORITHM  = AEAD_AES_256_CBC_HMAC_SHA256);
CREATE COLUMN ENCRYPTION KEY

查询存储密钥信息的系统表结果如下：

openGauss=# SELECT * FROM gs_client_global_keys;
 global_key_name | key_namespace | key_owner | key_acl |        create_date
-----------------+---------------+-----------+---------+----------------------------
 imgcmk1         |          2200 |        10 |         | 2021-04-21 11:04:00.656617
 imgcmk          |          2200 |        10 |         | 2021-04-21 11:04:05.389746
(2 rows)
openGauss=# SELECT column_key_name,column_key_distributed_id ,global_key_id,key_owner  FROM gs_column_keys;
 column_key_name | column_key_distributed_id | global_key_id | key_owner
-----------------+---------------------------+---------------+-----------
 imgcek1         |                 760411027 |         16392 |        10
 imgcek          |                3618369306 |         16398 |        10
(2 rows)

创建加密表：

openGauss=# CREATE TABLE creditcard_info (id_number    int, name         text encrypted with (column_encryption_key = ImgCEK, encryption_type = DETERMINISTIC),
credit_card  varchar(19) encrypted with (column_encryption_key = ImgCEK1, encryption_type = DETERMINISTIC));
NOTICE:  The 'DISTRIBUTE BY' clause is not specified. Using 'id_number' as the distribution column by default.
HINT:  Please use 'DISTRIBUTE BY' clause to specify suitable data distribution column.
CREATE TABLE

查询表的详细信息如下，Modifiers 值为 encrypted 则表示该列是加密列。

openGauss=# \d creditcard_info
        Table "public.creditcard_info"
   Column    |       Type        | Modifiers
-------------+-------------------+------------
 id_number   | integer           |
 name        | text              |  encrypted
 credit_card | character varying |  encrypted

向加密表插入数据并进行等值查询。

openGauss=# INSERT INTO creditcard_info VALUES (1,'joe','6217986500001288393');
INSERT 0 1
openGauss=# INSERT INTO creditcard_info VALUES (2, 'joy','6219985678349800033');
INSERT 0 1
openGauss=# select * from creditcard_info where name = 'joe';
 id_number | name |     credit_card
-----------+------+---------------------
         1 | joe  | 6217986500001288393
(1 row)
注意：使用非密态客户端查看该加密表数据时是密文
openGauss=# select id_number,name from creditcard_info;
 id_number |                                                                         name
-----------+------------------------------------------------------------------------------------------------------------------------------------------------------
         1 | \x011aefabd754ded0a536a96664790622487c4d366d313aecd5839e410a46d29cba96a60e4831000000ee79056a114c9a6c041bb552b78052e912a8b730609142074c63791abebd0d38
         2 | \x011aefabd76853108eb406c0f90e7c773b71648fa6e2b8028cf634b49aec65b4fcfb376f3531000000f7471c8686682de215d09aa87113f6fb03884be2031ef4dd967afc6f7901646b
(2 rows)

（可选）对加密表进行 alter 和 update 操作。

openGauss=# ALTER TABLE creditcard_info ADD COLUMN age int ENCRYPTED WITH (COLUMN_ENCRYPTION_KEY = ImgCEK, ENCRYPTION_TYPE = DETERMINISTIC);
ALTER TABLE
openGauss=# \d creditcard_info
        Table "public.creditcard_info"
   Column    |       Type        | Modifiers
-------------+-------------------+------------
 id_number   | integer           |
 name        | text              |  encrypted
 credit_card | character varying |  encrypted
 age         | integer           |  encrypted
openGauss=# ALTER TABLE creditcard_info DROP COLUMN age;
ALTER TABLE
openGauss=# update creditcard_info set credit_card = '80000000011111111' where name = 'joy';
UPDATE 1
openGauss=# select * from creditcard_info  where name = 'joy';
 id_number | name |    credit_card
-----------+------+-------------------
         2 | joy  | 80000000011111111
(1 row)

三、使用 JDBC 操作密态数据库

连接密态数据库

连接密态数据库需要使用驱动包 gsjdbc4.jar，具体 JDBC 连接参数参考基于 JDBC 开发章节介绍。JDBC 支持密态数据库相关操作，需要设置

enable_ce=1，示例如下：

public static Connection getConnect(String username, String passwd)
    {
        //驱动类。
        String driver = "org.postgresql.Driver";
        //数据库连接描述符。
        String sourceURL = "jdbc:postgresql://10.10.0.13:8000/postgres?enable_ce=1";
        Connection conn = null;
        
        try
        {
            //加载驱动。
            Class.forName(driver);
        }
        catch( Exception e )
        {
            e.printStackTrace();
            return null;
        }
        
        try
        {
             //创建连接。
            conn = DriverManager.getConnection(sourceURL, username, passwd);
            System.out.println("Connection succeed!");
        }
        catch(Exception e)
        {
            e.printStackTrace();
            return null;
        }
        
        return conn;
    };

说明：

【建议】使用 JDBC 操作密态数据库时，一个数据库连接对象对应一个线程，否则，不同线程变更可能导致冲突。
【建议】使用 JDBC 操作密态数据库时，不同 connection 对密态配置数据有变更，由客户端调用 isvalid 方法保证连接
能够持有变更后的密态配置数据，此时需要保证参数 refreshClientEncryption 为 1 （默认值为 1），在单客户端操作密态数据场景下，refreshClientEncryption 参数可以设置为 0。

调用 isValid 方法刷新缓存示例

// 创建客户端主密钥
Connection conn1 = DriverManager.getConnection("url","user","password");

// conn1通过调用isValid刷新缓存
try {
 if (!conn1.getConnection().isValid(60)) {
  conn1.getFileWriter().writeLine("isValid Failed for connection 1");
 }
} catch (SQLException e) {
 conn1.getFileWriter().writeLine("isValid Failed with error");
 e.printStackTrace();
}

执行密态等值查询相关的创建密钥语句

// 创建客户端主密钥
Connection conn = DriverManager.getConnection("url","user","password");
Statement stmt = conn.createStatement();
int rc = stmt.executeUpdate("CREATE CLIENT MASTER KEY ImgCMK1 WITH ( KEY_STORE = gs_ktool, KEY_PATH = \"gs_ktool/1\", ALGORITHM = AES_256_CBC;"); 
int rc = stmt.executeUpdate("CREATE CLIENT MASTER KEY ImgCMK1 WITH ( KEY_STORE = localkms, KEY_PATH = \"key_path_value\" , ALGORITHM = RSA_2048);

说明：创建密钥之前需要使用 gs_ktool 工具提前生成密钥，才能创建 CMK 成功。

// 创建列加密密钥
int rc2 = stmt.executeUpdate("CREATE COLUMN ENCRYPTION KEY ImgCEK1 WITH VALUES (CLIENT_MASTER_KEY = ImgCMK1, ALGORITHM  = AEAD_AES_256_CBC_HMAC_SHA256);");

执行密态等值查询相关的创建加密表的语句

int rc3 = stmt.executeUpdate("CREATE TABLE creditcard_info (id_number    int, name  varchar(50) encrypted with (column_encryption_key = ImgCEK1, encryption_type = DETERMINISTIC),credit_card  varchar(19) encrypted with (column_encryption_key = ImgCEK1, encryption_type = DETERMINISTIC));");
// 插入数据
int rc4 = stmt.executeUpdate("INSERT INTO creditcard_info VALUES (1,'joe','6217986500001288393');");
// 查询加密表
ResultSet rs = null;
rs = stmt.executeQuery("select * from creditcard_info where name = 'joe';");
// 关闭语句对象
stmt.close();

执行加密表的预编译 SQL 语句

// 调用Connection的prepareStatement方法创建预编译语句对象。
PreparedStatement pstmt = con.prepareStatement("INSERT INTO creditcard_info VALUES (?, ?, ?);");
// 调用PreparedStatement的setShort设置参数。
pstmt.setInt(1, 2);
pstmt.setString(2, "joy");
pstmt.setString(3, "6219985678349800033");
// 调用PreparedStatement的executeUpdate方法执行预编译SQL语句。
int rowcount = pstmt.executeUpdate();
// 调用PreparedStatement的close方法关闭预编译语句对象。
pstmt.close();

执行加密表的批处理操作

// 调用Connection的prepareStatement方法创建预编译语句对象。
Connection conn = DriverManager.getConnection("url","user","password");
PreparedStatement pstmt = conn.prepareStatement("INSERT INTO batch_table (id, name, address) VALUES (?,?,?)");
// 针对每条数据都要调用setShort设置参数，以及调用addBatch确认该条设置完毕。
int loopCount = 20;
 for (int i = 1; i < loopCount + 1; ++i) {
      statemnet.setInt(1, i);
      statemnet.setString(2, "Name " + i);
      statemnet.setString(3, "Address " + i);
      // Add row to the batch.
      statemnet.addBatch();
}
// 调用PreparedStatement的executeBatch方法执行批处理。
int[] rowcount = pstmt.executeBatch();
// 调用PreparedStatement的close方法关闭预编译语句对象。
pstmt.close();