DAS模型中的数据库加密与密文检索研究
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摘要
DAS(Database as a Service)模型是云存储中的一种新型数据库应用体系。在DAS模型中,数据所有者将数据交由数据库服务提供商(Database Service Provider, DBSP)托管,数据库以服务的形式提供。DBSP负责用户数据的存取、管理和查询服务,这意味着DBSP可在无访问控制的情况下获取用户数据,因此,DAS模型的最大安全威胁来自于内部的数据管理者,而并非数据库的外部攻击。在这种服务器端不可信的环境中,使用数据库加密可以充分保障数据安全,但在检索时需对密文逐一解密,导致检索性能急剧下降。对结构化数据库而言,由于数据库加密破坏了原有数据的有序性、数值大小、模糊匹配等固有特征,数据库的范围检索和模糊检索变得异常困难；对非结构化数据库而言,其非结构化特性导致了加密粒度难以控制、密文检索效率低等问题；同时,由于DAS模型的服务器端不可信,传统的密钥管理机制无法保障密钥安全性,HSM(Hardware Security Module)策略虽可保障密钥安全性,但密钥存储空间有限,目前为止,DAS模型的密钥管理还未有较成熟的解决方法。
针对上述问题,本文基于结构化数据库和非结构化数据库的结构特征,在DAS模型环境下,分别针对关系型数据库和XML数据库,提出数据库的加密策略和密文检索模型,并通过安全性分析和实验仿真证明了加密策略的安全性和密文检索的高效性,在此基础上,提出一种适用于DAS模型的密钥管理策略,能够克服密钥存储的数量限制,也保障了密钥的安全性和使用效率。
本文的主要研究工作如下：
(1)针对关系型数据库加密中存在的安全问题,提出一种适用于DAS模型的数据库加密策略,该策略通过初始化向量变换改变密文分布,而不需存储初始化向量,避免了基于频率的数据库攻击,也不会产生较多的数据冗余；在此基础上,针对数值型密文的范围检索问题,提出一种数据库密文检索模型,该模型根据检索条件,通过数值顺序置换动态划定数据库的数值范围,由此范围直接提取符合检索条件数据库密文,从而实现对范围检索的支持,也避免了检索过程中不必要的数据传输和加密/解密,通过实验证明,这种方式缩短了密文检索中的数据传输和加密/解密时间,显著提高了数据库密文检索效率。
(2)针对关系型数据库中字符型密文的模糊检索问题,提出一种字符型数据的加密与密文检索模型。对CHAR或VARCHAR数据类型,提出一种基于特征提取的双重过滤算法,由数据的字符集和字符位置关系提取特征值,并根据此特征值将大部分不符合特征的数据库记录过滤,在检索时只需传输和解密较少的数据,进而提高密文检索效率。这种特征值的提取基于字符加密,只有持有密钥者才能进行字符特征的提取和比对,因而保障了数据库加密的安全性,经实验证明,双重过滤算法可将大部分不符合关键词字符特征的记录剔除,提高了密文检索性能；针对CLOB数据类型,提出一种字符位置信息分组加密的策略,该策略将所有字符转换为对应位置信息,并将此位置信息先进行分组,然后对每一组数据分别加密,因此,数据库检索时只需解密一组或多组密文数据。这种策略有效减少了解密数据量,提高了密文检索效率,同时这种分组的方式隐藏了明文数据的频率分布,避免了基于频率的数据库攻击。
(3)针对XML数据库加密粒度难以控制、密文检索效率低等问题,提出一种基于曲线插值变换的XML数据库加密与密文检索模型,在此模型中,提出一种XML节点的隐藏机制,通过这种机制可将加密粒度细化为XML节点、XML节点间的关系、XML子树,灵活地控制了XML数据的加密粒度,并利用曲线插值变换改变XML数据的密文分布,可有效抵御各类针对XML数据库的攻击,也能支持数值范围检索。在此基础上建立XQuery检索翻译器,将客户端明文的XQuery语句转换为服务器端的对应密文语句,检索过程只需解密少数密文,避免了不必要的XML数据传输和解密。经证明,加密模型具备足够安全性,以Oracle XML DB为例进行实验,结果显示密文检索效率能够达到无索引XML明文检索的65%。
(4)针对DAS模型密钥管理中安全保障困难、存储空间受限等问题,提出基于哈希查询的密钥管理策略,采用一种多叉树结构建立密钥字典,该方法能够同时适用于关系数据库和XML数据库,并提出基于哈希算法的密钥字典查询模型,将多叉树路径的哈希值存储于密钥字典中,通过哈希值的快速匹配提取二级密钥信息,经实验验证,这种策略有效提高了密钥的提取效率。在安全性方面,HSM的存储方式杜绝了在服务器端获得主密钥或工作密钥的可能,密钥字典将二级密钥信息存储于服务器端,解除了密钥存储数量的限制,多叉树路径哈希值的存储策略隐藏了二级密钥信息和数据库密文的链接,保障了密钥的安全性。
DAS (Database as a Service) is a novel database application architecture of Cloud Storage. In DAS model, data owner outsource data to a DBSP(Database Service Provider), and database is provided as a service. Database server provides the services of storage, access, management and query of data. This means DBSP can gain the data of data owner easily. Therefore, instead of the external database attack, the biggest threat in security is from data administrator. In the untrusted database server, database encryption is a natural solution. However, due to the wasted time in decryption, the query performance will be lost. For the structured database, range query and fuzzy query is inefficient because the ordering, similarity, comparability is destroyed by encryption; for the unstructured database, encryption granularity is difficult to control owing to the unstructured property. Simultaneously, the conventional key management method cannot ensure security in untrusted database server. HSM is a secure strategy but the storage space of HSM is limited. There's not an appropriate method in the key management of DAS so far.
To address these problems, for relational database and XML database, the different encryption method and ciphtext query model are proposed based on the structure of database. This model can improve the performance of ciphtext query on the premise of ensuring the security of database. Furthermore, a key management strategy is presented, by which the quantity of key will not be limited, and the utilization efficiency of key can be improved.
The main work and contributions of the paper are as follows:
(1) To address the security problem of database encryption of relational database, a database encryption strategy applied to DAS is introduced. This strategy changes the distribution of ciphertext of database by the translation of initialization vector. There's no need to store the initialization vectors in our strategy. The frequency-based attack can be avoided, and the data redundancy will not be caused. On this basis, to the problem of ciphertext query of numeric data, a ciphertext query model is proposed.This model determines the range of numeric data dynamically by the order replacement of numerical value, and the needed ciphertext can be extracted. Range query is supported by this model, in which the unnecessary data transmission and encryption/decryption will be avoided. The experimental results show that the time of data transmission and encryption/decryption is saved and the efficiency of ciphertext query is improved remarkably.
(2) To the fuzzy query of encrypted character data in relational database, an encryption and ciphertext query model is proposed. For the CHAR or VARCHAR data type, a double filtration method based on feature extraction is presented. The characteristic value is extracted from the character set and the positions of character data, by which most of the nonmatched data will be filtered. Therefore, the time wasted on transmission and encryption reduced greatly. As a result, the retrieval speed is improved. Only key holder can extract the characteristic value and match it with that of keyword in that the extraction is based on encryption algorithm.So the security is ensured in database encryption. The experimental results show that the double filtration algorithm eliminated most of nonmatched records in database. Naturally, the performance of ciphertext query was improved. To CLOB data type, we store and encrypt these positions group by group instead of the original data. In other words, the original character data will be abandoned because they can be generated by the positions. When the query of database is executing, we only decrypt one or more group and the character matching translates into the numerical comparison. The amount of decryption is reduced efficiently. As a result, the query efficiency of database will be improved remarkably. Furthermore, this strategy confused the distribution of plaintext, which avoids the frequency-based attack.
(3) To address the problem of the coarse granularity in encryption and the inefficiency in ciphertext query, an approach based on curve interpolation is presented. Firstly, more flexible encryption granularity can be obtained through a XML node-hide mechanism; secondly, more efficiency to resist various kinds of database attack due to the changing of ciphertext distribution and data size. A XMLQuery (XQuery) is established. The proposed model offers greater security, and the ciphertext query performance can amount to 65% of the plaintext query based on the result of experimental simulation.
(4) To address the difficulty of security insurance and limited storage space in key management, the key management strategy based on the query of hash values is proposed. The key dictionary is established in multiway tree structure. This strategy can be applied in relational database and XML database. Simultaneously, the key dictionary query model is presented. The hash value of each path in multiway tree structure is stored in key dictionary. The secondary key can be extracted by matching hash values. The experimental results show that the efficiency of key extraction is improved. Furthermore, due to the adoption of HSM(Hardware Security Module), it is difficult to obtain the primary key or working key in database server. The secondary key information is stored in database server, by which the quantity of key will not be limited. The linkage between the secondary key information and database records is concealed by the hash values of multiway tree structure. As a result, the security is obtained.
针对上述问题,本文基于结构化数据库和非结构化数据库的结构特征,在DAS模型环境下,分别针对关系型数据库和XML数据库,提出数据库的加密策略和密文检索模型,并通过安全性分析和实验仿真证明了加密策略的安全性和密文检索的高效性,在此基础上,提出一种适用于DAS模型的密钥管理策略,能够克服密钥存储的数量限制,也保障了密钥的安全性和使用效率。
本文的主要研究工作如下：
(1)针对关系型数据库加密中存在的安全问题,提出一种适用于DAS模型的数据库加密策略,该策略通过初始化向量变换改变密文分布,而不需存储初始化向量,避免了基于频率的数据库攻击,也不会产生较多的数据冗余；在此基础上,针对数值型密文的范围检索问题,提出一种数据库密文检索模型,该模型根据检索条件,通过数值顺序置换动态划定数据库的数值范围,由此范围直接提取符合检索条件数据库密文,从而实现对范围检索的支持,也避免了检索过程中不必要的数据传输和加密/解密,通过实验证明,这种方式缩短了密文检索中的数据传输和加密/解密时间,显著提高了数据库密文检索效率。
(2)针对关系型数据库中字符型密文的模糊检索问题,提出一种字符型数据的加密与密文检索模型。对CHAR或VARCHAR数据类型,提出一种基于特征提取的双重过滤算法,由数据的字符集和字符位置关系提取特征值,并根据此特征值将大部分不符合特征的数据库记录过滤,在检索时只需传输和解密较少的数据,进而提高密文检索效率。这种特征值的提取基于字符加密,只有持有密钥者才能进行字符特征的提取和比对,因而保障了数据库加密的安全性,经实验证明,双重过滤算法可将大部分不符合关键词字符特征的记录剔除,提高了密文检索性能；针对CLOB数据类型,提出一种字符位置信息分组加密的策略,该策略将所有字符转换为对应位置信息,并将此位置信息先进行分组,然后对每一组数据分别加密,因此,数据库检索时只需解密一组或多组密文数据。这种策略有效减少了解密数据量,提高了密文检索效率,同时这种分组的方式隐藏了明文数据的频率分布,避免了基于频率的数据库攻击。
(3)针对XML数据库加密粒度难以控制、密文检索效率低等问题,提出一种基于曲线插值变换的XML数据库加密与密文检索模型,在此模型中,提出一种XML节点的隐藏机制,通过这种机制可将加密粒度细化为XML节点、XML节点间的关系、XML子树,灵活地控制了XML数据的加密粒度,并利用曲线插值变换改变XML数据的密文分布,可有效抵御各类针对XML数据库的攻击,也能支持数值范围检索。在此基础上建立XQuery检索翻译器,将客户端明文的XQuery语句转换为服务器端的对应密文语句,检索过程只需解密少数密文,避免了不必要的XML数据传输和解密。经证明,加密模型具备足够安全性,以Oracle XML DB为例进行实验,结果显示密文检索效率能够达到无索引XML明文检索的65%。
(4)针对DAS模型密钥管理中安全保障困难、存储空间受限等问题,提出基于哈希查询的密钥管理策略,采用一种多叉树结构建立密钥字典,该方法能够同时适用于关系数据库和XML数据库,并提出基于哈希算法的密钥字典查询模型,将多叉树路径的哈希值存储于密钥字典中,通过哈希值的快速匹配提取二级密钥信息,经实验验证,这种策略有效提高了密钥的提取效率。在安全性方面,HSM的存储方式杜绝了在服务器端获得主密钥或工作密钥的可能,密钥字典将二级密钥信息存储于服务器端,解除了密钥存储数量的限制,多叉树路径哈希值的存储策略隐藏了二级密钥信息和数据库密文的链接,保障了密钥的安全性。
DAS (Database as a Service) is a novel database application architecture of Cloud Storage. In DAS model, data owner outsource data to a DBSP(Database Service Provider), and database is provided as a service. Database server provides the services of storage, access, management and query of data. This means DBSP can gain the data of data owner easily. Therefore, instead of the external database attack, the biggest threat in security is from data administrator. In the untrusted database server, database encryption is a natural solution. However, due to the wasted time in decryption, the query performance will be lost. For the structured database, range query and fuzzy query is inefficient because the ordering, similarity, comparability is destroyed by encryption; for the unstructured database, encryption granularity is difficult to control owing to the unstructured property. Simultaneously, the conventional key management method cannot ensure security in untrusted database server. HSM is a secure strategy but the storage space of HSM is limited. There's not an appropriate method in the key management of DAS so far.
To address these problems, for relational database and XML database, the different encryption method and ciphtext query model are proposed based on the structure of database. This model can improve the performance of ciphtext query on the premise of ensuring the security of database. Furthermore, a key management strategy is presented, by which the quantity of key will not be limited, and the utilization efficiency of key can be improved.
The main work and contributions of the paper are as follows:
(1) To address the security problem of database encryption of relational database, a database encryption strategy applied to DAS is introduced. This strategy changes the distribution of ciphertext of database by the translation of initialization vector. There's no need to store the initialization vectors in our strategy. The frequency-based attack can be avoided, and the data redundancy will not be caused. On this basis, to the problem of ciphertext query of numeric data, a ciphertext query model is proposed.This model determines the range of numeric data dynamically by the order replacement of numerical value, and the needed ciphertext can be extracted. Range query is supported by this model, in which the unnecessary data transmission and encryption/decryption will be avoided. The experimental results show that the time of data transmission and encryption/decryption is saved and the efficiency of ciphertext query is improved remarkably.
(2) To the fuzzy query of encrypted character data in relational database, an encryption and ciphertext query model is proposed. For the CHAR or VARCHAR data type, a double filtration method based on feature extraction is presented. The characteristic value is extracted from the character set and the positions of character data, by which most of the nonmatched data will be filtered. Therefore, the time wasted on transmission and encryption reduced greatly. As a result, the retrieval speed is improved. Only key holder can extract the characteristic value and match it with that of keyword in that the extraction is based on encryption algorithm.So the security is ensured in database encryption. The experimental results show that the double filtration algorithm eliminated most of nonmatched records in database. Naturally, the performance of ciphertext query was improved. To CLOB data type, we store and encrypt these positions group by group instead of the original data. In other words, the original character data will be abandoned because they can be generated by the positions. When the query of database is executing, we only decrypt one or more group and the character matching translates into the numerical comparison. The amount of decryption is reduced efficiently. As a result, the query efficiency of database will be improved remarkably. Furthermore, this strategy confused the distribution of plaintext, which avoids the frequency-based attack.
(3) To address the problem of the coarse granularity in encryption and the inefficiency in ciphertext query, an approach based on curve interpolation is presented. Firstly, more flexible encryption granularity can be obtained through a XML node-hide mechanism; secondly, more efficiency to resist various kinds of database attack due to the changing of ciphertext distribution and data size. A XMLQuery (XQuery) is established. The proposed model offers greater security, and the ciphertext query performance can amount to 65% of the plaintext query based on the result of experimental simulation.
(4) To address the difficulty of security insurance and limited storage space in key management, the key management strategy based on the query of hash values is proposed. The key dictionary is established in multiway tree structure. This strategy can be applied in relational database and XML database. Simultaneously, the key dictionary query model is presented. The hash value of each path in multiway tree structure is stored in key dictionary. The secondary key can be extracted by matching hash values. The experimental results show that the efficiency of key extraction is improved. Furthermore, due to the adoption of HSM(Hardware Security Module), it is difficult to obtain the primary key or working key in database server. The secondary key information is stored in database server, by which the quantity of key will not be limited. The linkage between the secondary key information and database records is concealed by the hash values of multiway tree structure. As a result, the security is obtained.
引文
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