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Secure privacy-preserving computing applications on cloud using homomorphic cryptography

机译:使用同态加密技术在云上保护隐私保护计算应用程序

摘要

The advancement of cloud computing technologies has provided users and business organisations with various cloud-based options to store and access information externally, across multiple platforms and geographic locations. The cloud also has the ability to deliver scalable and high-performance computing services on demand and in a cost-effective manner while helping users to avoid the trouble of maintaining large data centres and complex computing facilities. The economies of scale increase revenue for cloud providers and lower costs for cloud users. The resulting on-demand model of computing allows providers to achieve better resource utilization through statistical multiplexing, and enables users to avoid the costs of resource over-provisioning through dynamic scaling. However, there are major security and privacy concerns when data is stored in external cloud storage systems. For example, when personal information is stored in unencrypted formats on the cloud, service providers can learn many details about the users such as their preferences, past behaviours and biometric identities. The widely distributed nature of cloud architectures means that server farms can be located in many countries or geographic locations that might be under different laws and regulations regarding user privacy. Furthermore, cloud service providers may encrypt data in-transit, but not while user data is stored on their servers, causing the reluctance of many business organisations to outsource the storage of their sensitive and valuable data, which can be major targets for attacks coming from both outside attackers and insiders. Therefore, encrypting the data when it is stored on the cloud is an important task to guarantee the confidentiality and privacy of users data. However, traditional cryptographic techniques make it difficult for processing tasks such as searching, updating or checking the integrity of encrypted data without asking clients to download and decrypt large amounts of data from the cloud. To realise the full potential of cloud computing, better cryptographic schemes are required. They should enable the cloud to perform various computing operations on encrypted data and return encrypted results to customers. Another desirable feature is how a cryptographic scheme can allow different parties to combine their encrypted data and perform some computing tasks on the cloud without compromising the confidentiality and privacy of the data of each party. Recently, homomorphic cryptography has increasingly been the focus of researchers because this technology has a great potential to provide the desirable features described above. Homomorphic encryption can be implemented either as a symmetric or a public-private asymmetric key paradigm. This technique allows many types of computing operations to be performed on ciphertext and output encrypted results which, when decrypted, are found to be identical to the results of the same operations performed on plaintext data. With a homomorphic cryptosystem, many computational circuits can now be homomorphically evaluated, producing programs that might be run on encryptions of their inputs to produce an encryption of their output. Since the inputs of such programs are encrypted, a computation task can be performed on an untrusted cloud without revealing any inputs and internal states. In this thesis, we focus the design and implementation of various application models of homomorphic cryptography so that the cloud can be used more effective and securely to store and process sensitive customer data. Our research works throughout many chapters of this thesis also provide valuable information regarding the security of homomorphic cryptography in many use case scenarios. We illustrate how homomorphic cryptography can be applied effectively with all of its flexibility, power and usefulness in many applications ranging from smart grid, e-commerce to secret sharing. In this thesis, we also propose approaches to enhance the efficiency and effectiveness of homomorphic cryptography, so that these cryptographic schemes can be applied not only in current cloud-based application, but also in larger, more mission-critical applications in the future.
机译:云计算技术的进步为用户和企业组织提供了各种基于云的选项,可以跨多个平台和地理位置从外部存储和访问信息。云还具有按需以经济高效的方式提供可扩展的高性能计算服务的能力,同时帮助用户避免了维护大型数据中心和复杂计算设施的麻烦。规模经济可增加云提供商的收入,并降低云用户的成本。由此产生的按需计算模型使提供商可以通过统计复用来更好地利用资源,并使用户可以通过动态扩展避免资源超额配置的成本。但是,将数据存储在外部云存储系统中时,存在主要的安全和隐私问题。例如,当个人信息以未加密的格式存储在云中时,服务提供商可以了解有关用户的许多详细信息,例如他们的偏好,过去的行为和生物特征。云架构的广泛分布特性意味着服务器场可以位于许多国家或地区,这些国家或地区可能受到有关用户隐私的不同法律和法规的约束。此外,云服务提供商可以对传输中的数据进行加密,但不能在用户数据存储在其服务器上的同时进行加密,这导致许多业务组织不愿将其敏感和有价值的数据外包,这可能是来自以下来源的攻击的主要目标外部攻击者和内部人员。因此,对存储在云中的数据进行加密是确保用户数据的机密性和隐私性的重要任务。但是,传统的加密技术很难在不要求客户端从云中下载和解密大量数据的情况下处理诸如搜索,更新或检查加密数据的完整性之类的任务。为了充分发挥云计算的潜力,需要更好的加密方案。他们应该使云能够对加密数据执行各种计算操作,并将加密结果返回给客户。另一个理想的功能是密码方案如何允许不同的参与者组合他们的加密数据并在云上执行一些计算任务,而又不损害每一方数据的机密性和隐私性。近来,同态密码术越来越成为研究人员的焦点,因为该技术具有提供上述理想功能的巨大潜力。同态加密可以实现为对称或公私非对称密钥范例。该技术允许对密文执行多种类型的计算操作,并输出加密的结果,该结果在解密后会发现与对明文数据执行的相同操作的结果相同。使用同态密码系统,现在可以对许多计算电路进行同态评估,从而生成可以对输入进行加密以对输出进行加密的程序。由于此类程序的输入已加密,因此可以在不显示任何输入和内部状态的情况下在不受信任的云上执行​​计算任务。在本文中,我们着重于同态密码学的各种应用模型的设计和实现,以便可以更有效,更安全地使用云来存储和处理敏感的客户数据。在本文的许多章节中,我们的研究工作还为许多用例场景中的同态密码学的安全性提供了有价值的信息。我们说明了同态密码技术如何以其所有的灵活性,功能和实用性有效地应用于从智能电网,电子商务到秘密共享的许多应用中。在本文中,我们还提出了提高同态密码学效率和有效性的方法,以便这些密码学方案不仅可以应用于当前基于云的应用程序中,而且可以应用于未来更大,更关键任务的应用程序中。

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